Advanced Strength and Conditioning
Becoming an effective strength and conditioning practitioner requires the
development of a professional skills set and a thorough understanding of the
scientific basis of best practice. Aimed at advanced students and novice-toexpert practitioners, in this book the authors explore the latest scientific
evidence and apply it to exercise selection and programming choices across
the full range of areas in strength and conditioning, from strength and
power, speed and agility, to aerobic conditioning.
Since the first edition of this text was written extensive research has
expanded the supporting evidence base that provides the theoretical
foundation for each chapter. In addition, some areas that were previously
under-researched have now been expanded and some key concepts have
been further challenged. Each chapter is written by experts with experience
in a wide variety of sports, including both applied and research experience,
ensuring this concise but sophisticated textbook is the perfect bridge from
introductory study to effective professional practice.
While advanced concepts are explored within the book, the coach must
not forget that consistency in the application of the basic principles of
strength and conditioning is the foundation of athletic development.
Advanced Strength and Conditioning: An Evidence-based Approach is a
valuable resource for all advanced students and practitioners of strength and
conditioning and fitness training.
Anthony N. Turner is Associate Professor in Strength and Conditioning
and the Director of Programmes for postgraduate studies in sport at the
London Sport Institute, Middlesex University. Anthony is a consultant to
numerous sports teams as well as the British Military. Anthony is Associate
Editor for the Strength and Conditioning Journal, has published over 100
peer-reviewed journal articles and numerous book chapters, and has edited
two textbooks.
Paul Comfort is Reader in Strength and Conditioning at the University of
Salford (UK), where he leads the master’s degree in Strength and
Conditioning. He is Adjunct Professor at Edith Cowan University
(Australia) and an honorary research fellow at Leeds Beckett University
(UK). He regularly consults with numerous professional rugby and soccer
teams and is a founder member and accredited member of the United
Kingdom Strength and Conditioning Association (UKSCA). Paul is an
editorial board member for the European Journal of Sport Science and
Sports Biomechanics, Associate Editor for the Strength and Conditioning
Journal, Senior Associate Editor of the Journal of Strength and
Conditioning Research, and has edited three textbooks.
“Advanced Strength and Conditioning: An Evidence-based Approach is a
fantastic core text which students in particular should read. It covers all the
key areas relating to developing your athlete, programming and monitoring
your athletes and of course, coaching your athlete, which provides a great
blend of theory and practice with a fantastic author line-up adding to the
credibility of this book.
”Chris Bishop, Programme Leader: MSc in Strength and
Conditioning, Middlesex University, UK
Advanced Strength and Conditioning
An Evidence-based Approach
Second Edition
Edited by
Anthony N. Turner and Paul Comfort
Cover image credit: vm / Getty Images
Second edition published 2022
by Routledge
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© 2022 Taylor & Francis
The right of Anthony N. Turner and Paul Comfort to be identified as the
authors of the editorial material, and of the authors for their individual
chapters, has been asserted in accordance with sections 77 and 78 of the
Copyright, Designs and Patents Act 1988.
All rights reserved. No part of this book may be reprinted or reproduced or
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registered trademarks, and are used only for identification and explanation
without intent to infringe.
First edition published by Routledge 2017
Library of Congress Cataloging-in-Publication Data
Names: Turner, Anthony (Anthony N.), editor. | Comfort, Paul, editor.
Title: Advanced strength and conditioning : an evidence-based approach /
edited by Anthony Turner and Paul Comfort.
Description: Second edition. | New York, N.Y. : Routledge, 2022. |
Includes bibliographical references and index.
Identifiers: LCCN 2021045906 (print) | LCCN 2021045907 (ebook) |
ISBN 9780367491369 (hardback) | ISBN 9780367491352 (paperback) |
ISBN 9781003044734 (ebook)
Subjects: LCSH: Physical education and training. | Muscle strength. |
Physical fitness–Physiological aspects.
Classification: LCC GV711.5 .A37 2022 (print) |
LCC GV711.5 (ebook) | DDC 613.7/13–dc23
LC record available at https://lccn.loc.gov/2021045906
LC ebook record available at https://lccn.loc.gov/2021045907
ISBN: 978-0-367-49136-9 (hbk)
ISBN: 978-0-367-49135-2 (pbk)
ISBN: 978-1-003-04473-4 (ebk)
DOI: 10.4324/9781003044734
Typeset in Baskerville
by Newgen Publishing UK
Access the Support Material: www.routledge.com/9780367491352
Contents
List of figures
List of tables
List of contributors
Introduction
1 Strength and conditioning: coach or scientist?
PERRY STEWART, PAUL COMFORT AND ANTHONY N.
TURNER
PART I
Developing your athlete
2 Developing muscular strength and power
TIMOTHY J. SUCHOMEL AND PAUL COMFORT
3 Stretch-shortening cycle and muscle–tendon stiffness
JOHN J. MCMAHON
4 Understanding and developing aerobic fitness
RICHARD C. BLAGROVE
5 Repeat sprint ability: physiological basis and implications for
training
ANTHONY N. TURNER AND DAVID BISHOP
6 Concurrent training
RODRIGO ASPE, RICHARD CLARKE, GARETH HARRIS AND
JONATHAN HUGHES
PART II
Programming and monitoring for your athlete
7 Periodisation
SHYAM CHAVDA, ANTHONY N. TURNER AND PAUL
COMFORT
8 Strategies to enhance athlete recovery
VINCENT KELLY, PATRICK HOLMBERG AND DAVID
JENKINS
9 Priming match-day performance: strategies for team sports players
MARK RUSSELL, NATALIE BROWN, SAMUEL P. HILLS AND
LIAM P. KILDUFF
10 Fitness testing and data analysis
JOHN J. MCMAHON, PAUL COMFORT AND ANTHONY N.
TURNER
11 Analysis and presentation of fitness test results
JOHN J. MCMAHON, ANTHONY N. TURNER AND PAUL
COMFORT
12 Eccentric training: scientific background and practical applications
MELLISSA HARDEN, PAUL COMFORT AND G. GREGORY
HAFF
13 Cluster sets: scientific background and practical applications
G. GREGORY HAFF AND MELLISSA HARDEN
PART III
Coaching your athlete
14 Movement screening: a systematic approach to assessing movement
quality
LOUIS HOWE AND CHRIS BISHOP
15 Technical demands of strength training
TIMOTHY J. SUCHOMEL AND PAUL COMFORT
16 Weightlifting for sports performance
TIMOTHY J. SUCHOMEL AND PAUL COMFORT
17 Plyometric training
CHRISTOPHER J. SOLE, CHRISTOPHER R. BELLON AND
GEORGE K. BECKHAM
18 Training for change of direction and agility
THOMAS DOS’SANTOS AND PAUL JONES
19 Speed and acceleration training
PEDRO JIMÉNEZ-REYES AND JEAN-BENOÎT MORIN
20 Applied coaching science
NICK WINKELMAN
21 Developing as a coach: leadership, culture, and purpose
BRIAN GEARITY AND CHRISTOPH SZEDLAK
Index
Figures
1.1
2.1
2.2
2.3
2.4
2.5
2.6
2.7
3.1
3.2
3.3
3.4
Integration of coaching and applied science principles. S&C, strength
and conditioning; TL, training load
Comparison of countermovement jump kinetic and temporal
variables between stronger and weaker athletes. RFD, rate of force
development
Medial gastrocnemius (MG) fascicle length (dashed line) and MG
pennation angle (θ), as measured between the superficial (A) and
deep (B) MG aponeuroses
Four sarcomeres in parallel
Four sarcomeres in series
Example emphasis change during a periodised training programme
(phase potentiation). 1RM, one repetition maximum
Back squat exercise using variable resistance with chains
Bench press exercise using variable resistance with elastic bands
An example of an object that obeys Hooke’s law and the equation to
calculate stiffness (k), where ∆F = change in force and ∆x = change
in length
An example of the torsional spring model and how it corresponds to
the human body
An example of the joint moment–joint angular displacement
relationship during loaded flexion and extension
An example of how joint touchdown angles influence leg and joint
stiffness values
3.5
An example of the spring–mass model and how it corresponds to the
human body
3.6
A schematic illustrating how the legs change from being more
compliant (opposite of stiff) to more stiff for a range of stretchshortening cycle tasks. DJ, drop jump
4.1
Relationship between intensity and oxygen uptake response during an
incremental test
4.2
Maximal oxygen uptake values for male and female elite endurance
athletes, elite athletes from selected intermittent sports, and healthy
individuals (20–40 years old) from the population (50th-percentile
values from several studies shown; Kaminsky, Arena, and Myers,
2016)
Factors that influence an athlete’s exercise economy with examples
Physiological profile and training zones for an elite male endurance
runner
Oxygen uptake kinetics during moderate- (dotted line), heavy(dashed line), and severe-intensity (hatched-line) exercise
Training strategies and recommended exercise prescription to
develop aerobic fitness components for various categories of sports.
%HRmax, percentage of maximum heart rate; V̇O2max, maximal
oxygen uptake
Endurance training intensity distribution for three common
approaches adopted by endurance sport athletes
How modes of training differ between moderate-intensity continuous
training (MICT), high-intensity interval training (HIIT) and sprint
interval training (SIT). HR max, maximum heart rate; V̇O2max,
maximal oxygen uptake
Putative adaptive pathways in response to the concurrent
programming of endurance and resistance exercises in a training
program
4.3
4.4
4.5
4.6
4.7
5.1
6.1
6.2
The recommended decision-making process during periods of
concurrent training. SIT, sprint interval training
7.1
(a) Distribution of training load; (b) distribution of training modes in
Olympic fencers
Relationship between volume, intensity and training specificity over
the three main phases of training. GPT, general physical training;
SSPT, sport-specific physical training; Comp, competition
Basic components of a periodised plan. GPT, general physical
training; SSPT, sport-specific physical training
7.2
7.3
7.4
Soon ripe, soon rotten. Training intensity is inversely correlated with:
(1) the time a performance peak can be maintained; (2) the height of
that performance peak; and (3) the rate of detraining
7.5
7.6
The 3:1 loading paradigm, illustrating the increase and then
dissipation of excessive fatigue
The general adaptation syndrome (GAS) model
7.7
7.8
The stimulus–fatigue–recovery–adaptation (SFRA) concept.
The fitness–fatigue paradigm
7.9 Athlete preparedness based on the specific form of fatigue
7.10 The principle of diminishing returns
7.11 Basic model of periodisation entailing little variation and relatively
flat workloads
7.12 The traditional, undulating approach to the design of periodised
training, which is attributed to the work of Matveyev (1977). Note the
3:1 loading method within each mesocycle
7.13 The conjugate sequence system pioneered by Yuri Verkhoshansky
(1986)
7.14 Schematic representation of the three principal tapering strategies
7.15 Schematic representation of the two-phase taper
8.1 Flow chart detailing factors to consider when determining the
implementation of recovery methods
9.1
10.1
11.1
11.2
11.3
11.4
11.5
12.1
Model of implementing the performance-enhancing strategies
Example of correctly identifying the unweighting, braking and
propulsive phases of a countermovement jump force–time curve
(solid grey line) by overlaying the velocity–time curve (dotted black
line). The dotted grey line represents zero centre of mass velocity
A typical normal data distribution curve with z-scores and the
corresponding percentage of data that they comprise
A typical normal data distribution curve with z-scores, corresponding
standard ten (STEN), t-score and percentile values and integrated
traffic-light system example
Example results of a pre-season fitness-testing battery conducted
within rugby league and presented as a radar chart using a
standardised t-score scale and integrated traffic-light system
Example results from force platform assessments that were conducted
as part of a pre-season fitness-testing battery within rugby league
presented as a radar chart using a standardised t-score scale and an
integrated traffic-light system
Example results from a countermovement jump assessment that was
conducted using a force platform as part of a pre-season fitnesstesting battery within rugby league presented as a radar chart using a
standardised t-score scale and an integrated traffic-light system
Schematic diagram illustrating an approach to tempo training
12.2
Schematic diagram illustrating augmented eccentric training using
weight releasers, with a total of 80% 1RM as an example
12.3
Schematic diagram illustrating augmented eccentric training during
back squats using weight releasers, with a total of 80% 1RM as an
example
Schematic diagram illustrating accentuated eccentric training using
weight releasers
12.4
12.5
Schematic diagram illustrating accentuated eccentric training using
weight releasers
12.6
Schematic diagram illustrating accentuated eccentric training using
weight releasers
12.7
Schematic diagram illustrating accentuated eccentric training using
weight releasers
13.1
Example set structures used in resistance training
13.2
13.3
Example undulating, wave, ascending, and descending cluster sets
Example cluster set repetition modifications
13.4
Suggested exercise alignments for cluster sets
13.5
Suggested training target / goal set type alignments
13.6
13.7
Cluster sets: set and repetition examples
Inter-repetition and intra-set rest interval alignments with training
phase
13.8
13.9
Partner cluster sets
Set alignments with phases of a periodised training plan
14.1
Model to establish the cause(s) of movement fault(s)
15.1
Ground reaction forces (orange arrow) and local coordinate frames
(blue arrows) during a sprint acceleration
15.2
Scenario requiring weightlifting alternatives for the snatch: (a) range
of motion must be reduced and the bar raised for the start of the lift;
(b) if planning to use a catching variation in subsequent phases a
catching variation at 80–95% 1RM may be advantageous to reinforce
technique; (c) if the athlete cannot catch (e.g. due to injury or limited
range of motion) and/or higher loads (≥100% 1RM power snatch) are
desired pulling derivatives may be advantageous
Scenario requiring weightlifting alternatives for the hang power clean
15.3
16.1
Hook grip – (a) thumb wraps under the bar with (b) the fingers
wrapped around the thumb and bar
16.2
16.3
Clean (top) and snatch (bottom) grip spacing
Starting position for (left) the snatch and (right) clean
16.4
The end of the first pull for (left) the snatch and (right) clean
16.5
Mid-thigh position side view for (left) the snatch and (right) clean
16.6
16.7
Second pull of (left) the snatch and (right) clean
Catch position of the snatch (left) and clean (right)
16.8
Power snatch (left) and power clean (right) catch positions
16.9 Recovery position for the snatch (left) and clean (right)
16.10 Starting position for a jerk variation
16.11 Completion of the dip phase of the jerk
16.12 The drive phase of the jerk
16.13 Split jerk receiving position
16.14 Power jerk receiving position
16.15 Jerk recovery
16.16 Force–velocity curve for weightlifting exercises. 1RM, one repetition
maximum; HPC, hang power clean; PC, power clean
16.17 Sequenced progressions of speed and strength-power development
with the weightlifting derivatives that may be used within each phase.
CM, countermovement
17.1
17.2
17.3
18.1
18.2
(a) Mechanical and (b) neurophysiological models of stretchshortening cycle potentiation. SEC, series elastic component; CC,
contractile component; PEC, parallel elastic component; MS, muscle
spindles; EF, extrafusal fibers
The force–time histories of two 40-centimeter drop jumps performed
by the same athlete within the same training session: the athlete was
instructed to perform a compliant or “soft” landing (dashed line) or a
stiff “spring-like” landing (solid line)
Plyometric tier progression with example exercises. CMJ,
countermovement jump; COD, change of direction
Model summarizing factors that underpin successful agility
performance
Braking strategy and technique requirements for different directional
changes. FFC, final-foot contact; PFC, penultimate-foot contact;
XOC, crossover cut
18.3
Summary of the biomechanical differences between side-step,
crossover, and split-step cutting techniques. Side-step manoeuvres
present higher knee joint loads and thus, potential knee injury risk,
but can be performed from a faster approach compared to a split step
and are effective for sharp directional changes. Crossover cuts are
ideal when velocity maintenance is required to shallow cutting
angles. Split-steps are ideal to avoid opponents and can achieve sharp
directional changes, but from relatively slow approaches. GCT,
ground contact time; VM, vastus medius; GM, gluteus medius; XOC,
crossover cut
18.4
Change of direction (COD) underpinned by the interaction between
velocity, deceleration, mechanics, and physical capacity. PFC,
penultimate-foot contact
18.5
Summary of biomechanical factors associated with peak knee
abduction moments based on literature. GRF, ground reaction force
18.6
Side-step cutting model to mediate the performance–injury conflict.
PFC, penultimate-foot contact
Important physical preparation considerations for change-of-direction
(COD) actions: developing physical capacity for load tolerance
18.7
18.8
Mixed multicomponent programmes for change-of-direction (COD)
speed and agility development. SSGs, small-sided games
18.9
Change-of-direction (COD) speed and agility development
framework. XOC, crossover cut
The resultant or “total” ground reaction force (FTot) during sprinting
support phase can be split and illustrated as the vectorial sum of
antero-posterior horizontal (FH) and vertical (VH) components. FV,
force–velocity; RF, ratio of forces
19.1
19.2
Ratio of forces (RF) and decrease in the ratio of forces (DRF). In this
typical example (sprinter performing a maximal acceleration over 60
m from the starting blocks) ground reaction force was assessed at
each step on a force plate instrumented track (Morin et al., 2019). The
DRF is −7.42%, which means that the athlete’s mechanical
effectiveness (RF) decreases on average by 7.42% for each meter per
second of speed increase. The dashed black and grey lines illustrate a
more and less efficient athlete, with similar first-step RF. Range of
DRF values reported is ~−5 to −14%, from elite sprinters to nonspecialists
19.3
Force–velocity–power profile of Usain Bolt’s world record. The input
data used are the athlete’s body mass and running speed–time data
20.1
Newell (1986) Interacting Constraints Model
Tables
1.1
2.1
2.2
2.3
3.1
5.1
5.2
5.3
5.4
6.1
6.2
6.3
7.1
The definition of scientific disciplines in relation to potential strength
and conditioning (S&C) coach roles
Muscle architectural adaptations in response to different training
stimuli
Neurological adaptations in response to different training stimuli
Relative power outputs for male athletes during various exercises
Summary of studies that have determined the effects of training
interventions on global lower-limb stiffness measures
Comparison of SIT vs HIIT vs. MICT protocols on peripheral muscle
adaptations and central adaptations
Effective training systems to enhance aerobic fitness (Helgerud,
Hoydal, Wang, Karlsen, Berg, & Bjerkaas, 2007): * significantly (p <
0.001) different from pre- to post-training
Interval distances for high-intensity interval training using maximal
aerobic speed (MAS), and calculated using a 1.5-mile run time of 10
min (Baker, 2011)
High-intensity interval training (HIIT) based on each energy system
Typical training week
Programming for concurrent training over an 8-week block
Mean (±SD) values for performance measures conducted in elite
women’s rugby players pre- and post-8 weeks of concurrent training
interventions
The main phases and sub-phases of periodisation
7.2
Exercise deletion and representation
7.3
Example sessions used as part of a basic periodised model
7.4
Two example strength sessions and two example power sessions,
which can be implemented as part of an intermediate periodised
programme
A practical example for applying and adapting the conjugate system
7.5
7.6
7.7
7.8
8.1
8.2
8.3
8.4
11.1
11.2
11.3
12.1
12.2
12.3
Example microcycle completed as part of a non-traditional
periodisation strategy
Summary of performance gains following a taper
Effect of training variables on the effect size of taper-induced
performance adaptations
Practical recommendations for recovery strategies
Example of a 12-week periodized training plan for college soccer and
recommendations for use of water immersion therapy
Example of an in-season week for American football and
recommendations for use of water immersion therapy
Practical recommendations to improve sleep
Example performance test results, corresponding z-scores and total
score of athleticism
Corresponding percentile, standard ten (STEN) and t-score values for
a given z-score
Example performance test results and corresponding individual and
average percentiles
Four eccentric training modalities and specificities underpinning each
modality
Summary of the physiological responses to eccentric training regimes
and the role of these responses in developing muscle hypertrophy,
strength, and power output
Examples of different isoweight eccentric training methods and
application examples for different-level athletes
13.1
13.2
Traditional training emphasis alignments with repetition ranges
Example training session employing cluster sets
13.3
14.1
Example loading patterns for cluster sets
Example movement screens, including standardisation procedures
14.2
Performance criteria for each example screen, including a brief
underpinning rationale
Key considerations to improve reliability when screening movement
quality
14.3
14.4
Example task manipulations for an overhead squat screen that can be
applied at stage 3 of the investigation process
14.5
14.6
Isolated assessments for mobility testing
Movement screen findings and associated investigatory process for
an international distance runner
15.1
15.2
15.3
Potential training effects of partial and deep squat variations
Rest interval length to achieve specific training goals
Cluster set rest interval length to achieve specific training goals
17.1
17.2
Plyometric focus within a periodized annual training plan
Plyometric tiers
17.3
17.4
Athlete A
Athlete B
18.1
A technical framework for a side-step cutting manoeuvre from a
running approach
A technical framework for a 180° pivot from a running approach
18.2
18.3
18.4
18.5
Summary of important physical qualities for successful change-ofdirection performance
Side-step cutting technique checklist
Example multi-component training programme to reduce change-ofdirection (COD) biomechanical characteristics associated with
increased anterior cruciate ligament (ACL) injury risk
19.1
21.1
Sprint running phase mechanics, corresponding key muscle actions
and suggestions for training. These are indicative points (not
exhaustive rules) based on published research evidence
Summary of coaching philosophies and applied suggestions to
promote servant (SL) and transformational leadership (TL)
behaviours in strength and conditioning coaching
Contributors
Rodrigo Aspe is Lecturer in Applied Sport and Exercise Science at Robert
Gordon University. He previously held academic posts at Abertay
University, University of Gloucestershire, and Hartpury University. He
obtained an MSc in Strength and Conditioning at the University of
Edinburgh and is an accredited strength and conditioning coach with
the United Kingdom Strength and Conditioning Association
(UKSCA). In addition to his academic career, Rodrigo continues to
work as an applied coach with Aberdeen Grammar Rugby in the
Scottish Premiership. He previously held positions with Scottish
Hockey and the Talented Athlete Scholarship Scheme (TASS).
George K. Beckham is Assistant Professor at California State University,
Monterey Bay. He holds a PhD in Sports Physiology and Performance
from East Tennessee State University.
Christopher R. Bellon is Assistant Professor in the Department of Health
and Human Performance at The Citadel, Military College of South
Carolina. He earned his doctoral degree in Sport Physiology and
Performance at East Tennessee State University. He is also a certified
strength and conditioning specialist with the National Strength and
Conditioning Association (NSCA).
Chris Bishop is Senior Lecturer in Strength and Conditioning at the London
Sport Institute, Middlesex University, where he is also the Programme
Leader for the MSc Strength and Conditioning degree. Chris has been
accredited with the UKSCA since 2011 and served on the Board of
Directors for the association from 2017 to 2021, with the last three
years as Chair of the Board. Chris has published extensively, with over
140 peer-reviewed journal articles and three book chapters to date; his
main areas of research are focused on inter-limb asymmetry and
athlete profiling through fitness testing and movement screening.
David Bishop has more than 20 years of experience as both a researcher and
an applied sport scientist working with elite athletes. He was the
inaugural research leader at the Institute of Health and Sport (iHeS),
Victoria University, Australia, and also leads the skeletal muscle and
training research group. His team is interested in optimising skeletal
muscle adaptation to exercise training, so as to improve health and
performance. He is known for his many highly cited articles on
repeated sprint ability. A more recent focus of his research group is to
examine how diet, exercise, and genes interact to regulate skeletal
muscle mitochondrial content and function. Professor Bishop has
written more than 280 peer-reviewed articles and ten book chapters in
the area of exercise and sport science. His research is currently funded
by the Australian Research Council (ARC), the National Health and
Medicine Research Council (NHMRC), and the Australian Defence
Force. He is also the past president of Exercise and Sport Science
Australia (ESSA), and Assistant Editor of Medicine and Science in
Sports and Exercise (MSSE). In the three years prior to the 2000
Sydney Olympics, he worked with Australian hockey, water polo,
netball, beach volleyball, and kayak teams. Professor Bishop has also
gained invaluable experience consulting with professional teams such
as the Fremantle Football Club.
Richard C. Blagrove is Lecturer in Physiology and the Programme Leader
for the MSc in Strength and Conditioning at Loughborough University.
He previously worked at Birmingham City University as Senior
Lecturer in Sport and Exercise Science and at St Mary’s University as
Programme Director for the BSc Strength and Conditioning Science
course, where he also managed the sport science support to The Royal
Ballet Company in London. Richard’s research investigates the
physiological factors that underpin performance in endurance running
and how strength-training exercise can be used as a tool to improve the
metabolic cost of exercise. He is also interested in health-related issues
associated with endurance sports, particularly the consequences of low
energy availability on bone health. Richard is an accredited strength
and conditioning coach and previously a director of the UKSCA. He
has provided strength and conditioning coaching support to numerous
athletes over the last 12 years, including endurance runners who have
competed in finals at the last three Olympic Games.
Natalie Brown is a research assistant for the Welsh Institute of Performance
Science working in collaboration with Sport Wales.
Shyam Chavda is the programme lead for the MSc in Strength and
Conditioning distance education at the London Sport Institute,
Middlesex University. He is also the performance scientist for British
Weightlifting and the head coach at Middlesex University
Weightlifting Club.
Richard Clarke is an accredited strength and conditioning coach with the
UKSCA, having served as a director of the association. Richard has a
strong history of athletic performance delivery to elite athletes working
in professional football, rugby, and basketball. Richard has also had a
track record of working in higher education, previously leading and
teaching on degrees at undergraduate and postgraduate level at the
University of Gloucestershire and Birmingham City University.
Thomas Dos’Santos is Lecturer in Strength and Conditioning at Manchester
Metropolitan University. He was awarded his bachelor’s degree,
master’s degree, and PhD from the University of Salford.
Brian T. Gearity is Director and Associate Professor of Sport Coaching and
online sport graduate certificate programmes at the University of
Denver. In addition to over 50 peer-reviewed publications, he coedited the book, Coach Education and Development in Sport:
Instructional Strategies and co-authored Understanding Strength and
Conditioning as Sport Coaching: Bridging the Biophysical,
Pedagogical and Sociocultural Foundations of Practice. He is Editorin-Chief for the NSCA practitioner journal NSCA Coach, a fellow of
the NSCA, and is on the editorial board for Sport Coaching Review,
International Sport Coaching Journal, Qualitative Research in Sport,
Exercise, and Health, and Strength & Conditioning Journal.
G. Gregory Haff is Professor of Strength and Conditioning at Edith Cowan
University (Perth, Western Australia) and an honorary professor at the
University of Salford, UK. He is a past president of the NSCA (2015–
2018). Professor Haff was the 2021 NSCA Impact Award winner for
his contributions to the strength and conditioning profession. In 2014,
he was named the UKSCA Strength & Conditioning Coach of the Year
– Education and Research. Additionally, Professor Haff was the 2011
NSCA’s William J. Kraemer Sport Scientist of the Year award winner.
He is also a Certified Strength and Conditioning Specialist with
Distinction, a Fellow of the NSCA, and an accredited member of the
UKSCA.
Mellissa Harden is a teaching and learning fellow at the University of
Salford, UK. She completed her PhD in eccentric training at
Northumbria University, funded by Great Britain Cycling, while
working as a strength coach with the cyclists.
Gareth Harris is Head of Athletic Performance at Bristol Bears Women’s
Rugby Club. He has an extensive applied background, having worked
with athletes across the performance spectrum from junior golfers to
university scholars and elite international athletes. Gareth completed
his education at the University of Gloucestershire, achieving an MSc
in Sports Strength and Conditioning with distinction.
Samuel P. Hills is Lecturer in Sports Science at Bournemouth University,
having achieved his PhD from Leeds Trinity University in 2020. He
has contributed to more than 20 peer-reviewed publications and
presented internationally on the topic of team sports preparation.
Patrick Holmberg has over 15 years of experience working as a collegiate
strength and conditioning coach and athletics administrator. He holds
an EdD in Higher Education Leadership. Patrick is a certified strength
and conditioning specialist and registered strength and conditioning
coach with distinction through the NSCA. He has worked with
multiple National Collegiate Athletic Association (NCAA) team and
individual national champions across a range of sports. Patrick is
currently a PhD student at Queensland University of Technology.
Louis Howe has been a strength and conditioning coach since 2007, having
helped prepare numerous athletes for the British Athletics
Championships, European Athletics Championships, Pan American
Games, Commonwealth Games, and Olympic Games. Louis currently
lectures at the University of Essex, having previously held positions at
Edge Hill University, University of Cumbria, and St Mary’s
University. Louis is an accredited strength and conditioning coach with
the UKSCA, and has a PhD in investigating compensatory movement
strategies derived from ankle dorsiflexion range of motion restrictions.
Jonathan Hughes is Academic Course Leader for the MSc in Sports
Strength and Conditioning at the University of Gloucestershire, UK.
Jonathan has applied experience of delivery across both team and
individual sports spanning 20 years; he is currently Head of Physical
Performance for the Italian Lacrosse National team. having fulfilled a
similar role for the Great Britain Women’s Ice Hockey team. Jonathan
is an accredited strength and conditioning coach with the UKSCA and
serves on its Research and Community Grants Panel. Jonathan has
published over 35 peer-reviewed journal articles and is currently
supervising six PhD students, all linked to high-performance sport
research.
David Jenkins is Professor of Sport and Exercise Science in the School of
Health and Behavioural Sciences at The University of the Sunshine
Coast. He also holds an adjunct appointment at The University of
Queensland, where he worked for 30 years prior to 2020. Professor
Jenkins is an exercise physiologist with an international reputation in
researching physiological responses to acute and chronic high-intensity
intermittent exercise. Many of his 180 peer-reviewed published papers
have described the acute and chronic responses to sprint, multiple
sprint, and interval exercise across different populations and groups.
Pedro Jiménez-Reyes is Lecturer at the Faculty of Sport of the Catholic
University of San Antonio, USA.
Paul Jones is Lecturer in Sports Biomechanics & Strength and Conditioning
at the University of Salford, UK. Paul earned a BSc(Hons) and MSc in
Sports Science, both from Liverpool John Moores University, and a
PhD in Sports Biomechanics at the University of Salford. He is a
certified strength and conditioning specialist, recertified with
distinction (CSCS*D) with the NSCA, an accredited sports and
exercise scientist with the British Association of Sports and Exercise
Sciences (BASES), and a chartered scientist (CSci) with The Science
Council. Paul has over 20 years’ experience in biomechanics and
strength and conditioning support to athletes and teams, working in
sports such as athletics, football, and rugby, and was a former sports
science support coordinator for UK disability athletics (2002–2006).
Paul has authored/co-authored over 90 peer-reviewed journal articles,
mainly in the areas of change-of-direction biomechanics, assessment
and development of speed, change-of-direction speed, and agility and
strength diagnostics. Paul has co-edited a book, Performance
Assessment in Strength and Conditioning, published by Routledge, and
is a member of the BASES accreditation committee.
Vincent Kelly is Associate Professor of Strength and Conditioning and
Sport Science at the School of Exercise and Nutrition Sciences,
Queensland University of Technology. His areas of research interest
include fatigue and recovery in athletes, strength and conditioning in
high-performance sport, mental fatigue in sport and exercise,
resistance-training priming, quantification and management of athlete
training load, the neuromuscular and hormonal adaptations to exercise,
and ergogenic aids and sport nutrition supplementation. He has over 20
years’ experience in elite sport, working in high-performance, sport
science, and strength and conditioning roles with professional football
teams, the Queensland Academy of Sport, and individual athletes. He
is a member of the National Rugby League (NRL) Research
Committee and a member of several committees with Exercise and
Sport Science Australia.
Liam P. Kilduff obtained his PhD from Glasgow University examining the
effects of creatine supplementation in sport, health, and disease. He
has worked for the last 18 years as Professor of Performance Science
at Swansea University, where his research interests focus on elite
athlete preparation strategies. He is currently Head of the Applied
Sports, Technology, Exercise and Medicine Research Centre (ASTEM) and chairs both the Research Steering Group and Strategic
Management Board of the Welsh Institute of Performance Science. He
has published in excess of 180 peer-reviewed papers and has secured
over £3m in research income. He sits on the editorial board of three
sports science journals.
John J. McMahon is Lecturer in Sports Biomechanics and Strength and
Conditioning at the University of Salford. He received his PhD in
sports biomechanics from the University of Salford in 2015 following
his research into dynamic muscle–tendon stiffness and stretchshortening cycle function. John has been an accredited strength and
conditioning coach with both the NSCA and UKSCA since 2010 and
has worked as a strength and conditioning coach across several team
sports. He has also co-authored 70 peer-reviewed journal articles
relating to athletic performance assessment and is currently
researching how to develop force plate-testing batteries across
different sports to help inform athletes’ training priorities. John is also
a co-editor of a book titled, Performance Assessment in Strength and
Conditioning, published by Routledge.
Jean-Benoît (JB) Morin is Full Professor at the University of Saint-Etienne
(France), and a member of the Interuniversity Laboratory of Human
Movement Biology (LIBM). He is also associate researcher with the
Sports Research Institute New Zealand (SPRINZ) at Auckland
University of Technology, and visiting Professor in Locomotion
Biomechanics at the School of Sport, Exercise and Health Science at
Loughborough University. He obtained a Track and Field Coach
National Diploma in 1998 and a PhD in Human Locomotion and
Performance in 2004 under the joint supervision of Professor Alain
Belli (University of Saint-Etienne, France) and Professor Pietro di
Prampero (University of Udine, Italy). JB’s field of research is mainly
human locomotion and performance, with specific interest in running
biomechanics and maximal-power movements (sprint, jumps). He has
edited a textbook (Biomechanics of Training and Testing, published by
Springer in 2018) and published over 150 peer-reviewed scientific
papers. He is also a consultant for professional sports groups in soccer,
rugby, sprint, and other power-speed sports. He practised soccer for ten
years, practised and coached track and field (middle distance and
400m hurdles) for eight years, and he now enjoys trail running and
triathlon.
Mark Russell is Professor of Performance Nutrition and Applied Exercise
Physiology at Leeds Trinity University. As a result of his research,
Professor Russell has published over 90 peer-reviewed articles and
book chapters, presented at international conferences, and led multiple
industry-funded contract research projects from inception to
completion. Professor Russell currently leads the Enhancing Human
Performance research theme at Leeds Trinity University and has a
special interest in team sport performance enhancement strategies.
Professor Russell works with a range of professional rugby and
football teams and has consulted for a number of English Premier
League football clubs and national and international rugby squads.
Christopher J. Sole PhD is Assistant Professor in the Department of Health
and Human Performance at The Citadel, Military College of South
Carolina. He earned his doctoral degree in Sport Physiology and
Performance at East Tennessee State University. He is also a certified
strength and conditioning specialist with the NSC.
Perry Stewart is a lead academy strength and conditioning coach at Arsenal
Football Club and a visiting lecturer at the London Sport Institute,
Middlesex University. He is an accredited strength and conditioning
coach and chartered sport scientist who has worked with athletes from
a range of sports, including football, tennis, fencing, taekwondo, judo,
karate, and athletics. Perry is currently studying for a PhD at
Loughborough University and was the winner of the UKSCA Strength
and Conditioning Coach of the Year award for Youth Sport in 2020.
Timothy J. Suchomel is Associate Professor of Exercise Science and the
Program Director for the Sport Physiology and Performance Coaching
masters programme at Carroll University. He also serves as the
Director of the Carroll University Sport Performance Institute (CUSPI)
and works as a human performance coach at the university. He has
published over 85 peer-reviewed journal articles on strength and power
development, weightlifting movements and their derivatives, and
athlete monitoring. He is a certified strength and conditioning
specialist (recertified with distinction) and registered strength and
conditioning coach through the NSCA.
Christoph Szedlak is an academic, researcher, and the lead strength and
conditioning coach at the University of Southampton. He has worked
with a variety of different-level athletes, including Olympic and world
champions, for over 13 years. His research focuses on examining the
psychological and social aspects of coaching and their impact on the
development of the athlete. With a specific emphasis on innovative
qualitative methods to present and disseminate findings, his research
has gained international recognition within strength and conditioning
coach development and education.
Nick Winkelman is Head of Athletic Performance and Science for the Irish
Rugby Football Union. His primary role is to oversee the delivery and
development of strength and conditioning and sports science across all
national (Men and Women, XVs, and sevens) and provincial teams
(Leinster, Munster, Connacht, and Ulster). Prior to working for Irish
Rugby, Nick was the director of education and training systems for
EXOS (formerly Athletes’ Performance), located in Phoenix, AZ. As
the director of education, Nick oversaw the development and
execution of all internal and external educational initiatives. As a
performance coach, Nick oversaw the speed and assessment
component of the EXOS National Football League (NFL) Combine
Development Program, and supported many athletes across the NFL,
Major League Baseball (MLB), National Basketball Association
(NBA), national sport organizations, and Military. Nick completed his
PhD through Rocky Mountain University of Health Professions with a
dissertation focus on motor skill learning and sprinting. Nick is an
internationally recognized speaker on human performance and
coaching science and has multiple peer-reviewed publications and
book chapters alongside his own book, The Language of Coaching:
The Art & Science of Teaching Movement.
Introduction
DOI: 10.4324/9781003044734-1
Becoming an effective strength and conditioning practitioner requires the
development of a professional skills set and a thorough understanding of the
scientific basis of best practice. Aimed at advanced students and
practitioners (from novice to expert), the authors explore the latest scientific
evidence and apply it to exercise selection and programming choices across
the full range of areas in strength and conditioning, from strength and
power, speed and agility, to aerobic conditioning.
With coverage of data analysis and feedback on performance
assessments to key stakeholders, both vital skills for the contemporary
strength and conditioning coach, this concise but sophisticated textbook is
the perfect bridge from introductory study to effective professional practice.
Written by experts with experience in a wide variety of sports, including
both applied and research experience, the chapters are enhanced with new
illustrations and address key topics such as:
fitness testing
data analysis and interpretation
weightlifting for sports performance
applied coaching science
strategies for competition priming
eccentric training
the use of cluster sets.
Advanced Strength and Conditioning: An Evidence-based Approach is a
valuable resource for all advanced students and practitioners of strength and
conditioning and fitness training. While advanced concepts are explored
within the book, the coach must not forget that consistency in the
application of the basic principles of strength and conditioning is the
foundation of athletic development.
Since the first edition of this text was written extensive research has
expanded the supporting evidence base that provides the theoretical
foundation for the majority of the chapters. In addition, some areas that
were previously under-researched have now been expanded and some key
concepts further challenged.
Research within the area on the use of weightlifting to enhance sports
performance has expanded noticeably, and as a result, some of the
theoretical concepts and original figures are now out of date. Similarly,
research relating to change-of-direction and agility performance has
expanded substantially since the first edition of this book, with the chapter
now being re-written by two new authors who are currently at the forefront
of research in this area. Fitness testing and data analysis and interpretation
have been divided into two chapters, to permit more detailed and focused
content on this important area.
Some training practices that are seen as being more advanced have
received much more attention by researchers, resulting in the need for
specific chapters to explore these research findings and the appropriate
application: the two new chapters are ‘Eccentric training: scientific
background and practical applications’ and ‘Cluster sets: scientific
background and practical applications’. To complement the ‘Applied
coaching science’ chapter, which has been updated, a further chapter on
‘Developing as a coach’ has also been included, exploring the art of
applying the underpinning science.
1
Strength and conditioning:
coach or scientist?
Perry Stewart, Paul Comfort and Anthony N.
Turner
DOI: 10.4324/9781003044734-2
Introduction
With sport playing an increasingly important role in the rapidly changing
economic, political, cultural and social world, the demand for elite sports
organizations to be successful and profitable is unprecedented. A result of
the growing demand is a rise in the medicalization and scientization of
organizations in the pursuit of a competitive advantage. Subsequently, there
has been an increased presence and reliance on sophisticated sport medicine
and sport science (SM&SS) staff and systems being employed. The support
network for an athlete and/or team has increased exponentially and now
often includes a complex team of support staff, including coaches, assistant
coaches, strength and conditioning (S&C) coaches, physiotherapists,
doctors, sports rehabilitators, soft-tissue therapists, psychologists,
physiologists, biomechanists, nutritionists and performance analysts. Such
support personnel are appointed in the majority of sports and across all
sectors, including government-funded (e.g. national institutes of sport),
educational establishments (e.g. schools, colleges and universities),
professional sport clubs, commercial performance facilities and by
individual athletes (Dawson et al., 2013).
S&C coaches have become a common feature of the modern support
network, especially within elite sport organizations. Fundamentally, the role
of an S&C coach is to test, monitor and enhance athleticism, by typically
utilizing periodized programme designs that include strength, power, speed,
agility and flexibility strategies as part of a holistic model of athletic
development (Ebben and Blackard, 2001; Ebben et al., 2004; Simenz et al.,
2005). However, in reality, the specification of each S&C job role will
likely depend on a number of factors, including specific context (e.g.
competition level, age of athlete), the organizational structure (e.g.
centralized vs. decentralized, hierarchical structure), the financial resources
of the organization (e.g. S&C roles may be merged with other roles to save
money) and the organization’s vision, objectives and training philosophy. It
is also likely that boundaries become blurred as S&C coaches engage in
activities unrelated to their specific discipline, for example, helping with
logistics and operations. Despite some inconsistencies existing in role
specification, one central requirement for most S&C coaches is the need to
integrate and interact with multiple stakeholders such as athletes, coaches,
support staff and management. It is evident that although S&C is a
discipline grounded in the physical preparation of athletes, the role of the
S&C coach is multifaceted with responsibilities extending far beyond that
of designing and implementing training programmes.
It is valuable for all current and aspiring S&C coaches to appreciate the
breadth and depth of knowledge and skills that are typically required to
effectively work in, and excel in, the discipline of S&C. Arguably the role
now is very different to the one carried out as little as 10 years ago, and we
must appreciate its evolution towards a practitioner who is just as much a
scientist as a coach. Therefore, the aim of this introductory chapter is to
review the attributes required to be an effective S&C practitioner within
today’s industry. It is the intention that this will in turn set the context and
significance of each chapter that follows, where all these components are
discussed in far greater detail.
The coach
It is prudent to start this chapter by addressing the foundation of the role,
the (S&C) coach. The role of any coach is simply to improve athletes’
physical, mental and emotional performance, in preparation for sporting
competition (Dorgo, 2009). Previous conceptual models of coaching have
emerged from different theoretical perspectives, including leadership,
expertise, coach–athlete relationships, motivation and education,
highlighting the complexity of a coach’s role – all of which are important.
Cote and Gilbert (2009) define coaching effectiveness as:
The consistent application of integrated professional, interpersonal and
intrapersonal knowledge to improve athletes’ competence, confidence,
connection, and character in specific coaching contexts.
This definition can be better understood when the three components of this
model (knowledge, outcomes and contexts) are considered in more detail.
The coach’s skills, attitudes and behaviours – collectively referred to as
‘knowledge’ – are separated into three interrelated categories.
1. Professional knowledge. Expert knowledge of subject-specific matter.
For example, an S&C coach is likely to have knowledge of competition
demands, applied physiology and biomechanics, principles of planning
and periodizing, dynamic correspondence and testing/monitoring.
2. Interpersonal knowledge. To be successful, coaches have to successfully
interact with their athletes and head and assistant coaches, as well as
other key stakeholders. This refers to the soft skills (sometimes referred
to as emotional intelligence) required to identify, use, understand and
manage interactions.
3. Intrapersonal knowledge. Described as self-awareness and
introspection, this is the ability of a coach to critically reflect. Gilbert
and Trudel’s (2001) research examined good coaches and how they
translate experience into knowledge and skills through reflection.
In summary, for an S&C coach to maximize athletes’ outcomes they must
possess comprehensive professional knowledge and effective interpersonal
skills and also practise continuous introspection, review and revision of
their practice (Cote and Gilbert, 2009). Despite S&C coaches focusing most
of their attention, time and energy towards developing professional
knowledge, it is the aggregate of professional knowledge, the ability to
connect with others (interpersonal skills) and the willingness to engage in
continued learning and self-reflection (intrapersonal skills) that will
determine how effective and successful an S&C coach will be. Previous
research has reported that stressful and dysfunctional relationships between
technical coaches and sport science personnel exist (Soanes and Williams,
2019), and that technical coaches’ perceptions of the relevance,
applicability and language associated with sport science teams vary
(Martindale and Nash, 2013). Martindale and Nash (2013) highlight the
need to practically apply professional knowledge, build effective working
relationships, efficiently disseminate information and apply user-friendly
language.
The second component of effective coaching focuses on ‘athlete
outcomes’, which typically relate to performance improvements (successful
performances and player development) and positive psychological
responses (high level of self-esteem, intrinsic motivation, enjoyment and
satisfaction). Cote and Gilbert (2009) identified four athlete outcomes,
namely: competence, confidence, connection and character/caring. It is
believed that the coach responsible for designing appropriate training
conditions can enhance all of these. These are explained in relation to the
S&C industry below.
Competence. Optimizing an athlete’s physical performance in relation
to their sport.
Confidence. Improved sense of overall positive self-worth. A coach
and athlete should agree achievable objectives and the coach should
design programmes that balance challenge and success.
Connection. Facilitating positive social relationships inside and outside
sport. A coach can encourage communication between athlete and
staff, parents and non-sporting peers.
Character. Encouraging moral attributes such as respect, integrity,
empathy and responsibility. Encourage athletes to take responsibility
for their own environment, personal standards and development.
The third and final component of effective coaching is ‘coaching contexts’,
which refers to the unique settings in which coaches work. Cote and Gilbert
(2009) describe coaching effectiveness and expertise as context-specific,
identifying three classifications: (1) recreational; (2) developmental; and (3)
elite sport. Further to this, the following situational factors should be
considered: (1) context (individual athlete or team sport, male or female,
senior or youth populations); (2) employment type (full- or part-time); (3)
the role (senior position or intern); and (4) the employer
(amateur/professional organization, state-funded or education). The context
alters the focus and attention of the coach and requires a high level of
specificity related to programme design and delivery. For example, an S&C
coach working with a developmental team athlete with a low training age
will plan, deliver and evaluate outcomes differently than if working with an
elite individual athlete in a highly demanding performance environment.
The scientist
It is clear from criteria detailed in job specifications that the responsibilities
of an S&C coach have evolved to include roles from other sport science
disciplines. Before exploring the application of sport science we consider
the definition of science:
pursuit and application of knowledge and understanding, following
systematic methodologies based on evidence
(Science Council, 2021)
Therefore, sport science can be thought of as a scientific process used to
guide the practice of sport, with the ultimate aim of improving sporting
performance (Bishop et al., 2006). The British Association of Sport and
Exercise Sciences (BASES) recognizes that the application of scientific
principles in sport is principally achieved through one of the three branches
of science or through interdisciplinary approaches: biomechanics,
physiology and psychology (Table 1.1). The importance of nutrition in sport
and exercise science is evident and now recognized as an integral role
within the multidisciplinary team, hence its inclusion in this chapter. The
discipline of S&C is fundamentally embedded in sport science with, for
example, the knowledge of programming being underpinned by the
understanding of how the anatomy will adapt (physiology), how changing
movement patterns can impact the kinetic chain and kinematics
(biomechanics), goal setting and motivation (psychology) and advising an
athlete what and when to eat to maximize performance or recovery
(nutrition). As previously mentioned, S&C job roles and responsibilities are
likely to vary based on various constraints (e.g. organizational structure,
working environment, level of athlete); however, it is common to observe
that in addition to the underpinning knowledge that allows S&C
professionals to perform their primary role, coaches are progressively being
expected to perform additional services such as postural, gait and
movement screening, testing using laboratory-based equipment (e.g. force
plates, isokinetic dynamometry, body composition analysis) and monitoring
of physical and physiological responses (e.g. vertical jumps, heart rate,
GPS, rate of perceived exertion, subjective questionnaires, blood and saliva
analyses).
Table 1.1
The definition of scientific disciplines in relation to potential strength and conditioning
(S&C) coach roles
Definition
Source: www.bases.org.uk/About-Sport-and-Exercise-Science.
Relation to S&C
Biomechanics An examination of the causes and
consequences of human movement
Movement analysis
Athlete performance
testing/profiling
Monitoring external training
responses
Physiology
An examination of the way the body
responds to exercise and training
Athlete performance
testing/profiling
Monitoring internal training
responses
Recovery modalities
Psychology
An examination of human behaviour within
exercise science
Profiling
Monitoring (questionnaires,
e.g. Profile of Mood States
(POMS))
Nutrition
An examination and practice of nutrition to
enhance wellbeing and athletic
performance
Fuelling
Hydration
Recovery
Supplementation
Source: www.bases.org.uk/About-Sport-and-Exercise-Science.
It is not suggested that S&C coaches should fill the roles of
biomechanists, physiologists, psychologists or nutritionists; however, it
appears that S&C coaches are expected to have a working understanding of,
or at times even embrace the role of, these professions. This may be a result
of the limited financial and physical resources dedicated by some sporting
organizations. In effect, the role of an S&C coach is like that of an
interdisciplinary sport and exercise scientist who attempts to utilize and
integrate more than one area of sport science to solve real-world problems
(Burwitz et al., 1994). The majority of S&C coaches within the UK hold a
minimum of an undergraduate-level degree within an exercise science
discipline (Hartsthorn et al., 2016), and within the USA, it is essential to
possess a degree for job roles and relevant industry certifications.
Therefore, it is perhaps unsurprising that S&C coaches are expected to
extend themselves to these roles. It is also hard to say whether these
growing responsibilities were academia-led (noting that degrees in S&C
teach would-be coaches these skills as though it is a requirement to
succeed) or a reflection of the economic status of the organization.
However, it is important that S&C coaches recognize their limitations and
only work within their scope of practice.
In addition to having professional knowledge of a broad range of
scientific areas and their practical application, the S&C coach is commonly
expected to perform data analysis. Due to the evidence-based environments
in which S&C coaches work, the ability to run data and statistical analyses
using appropriate platforms (Excel, SPSS, R, etc.), is becoming
increasingly important. Such skills enable the S&C coach to identify the
success or failure of an intervention, to detect meaningful changes and
trends, and to develop models that inform performance. Furthermore, this
information must be interpreted, filtered and communicated to technical
coaches, support staff, athletes and parents in a way that is relevant and
meaningful. This requires the S&C coach to, firstly, be competent at
completing the required analysis and, secondly, have adequate interpersonal
knowledge to communicate the results within the correct sporting context.
Performance lifestyle: non-contact coaching
Since the dawn of professionalization within elite sport, and the subsequent
increased commercial attention and financial incentives (for both athlete
and organization), performance outcomes (success of team/individual,
win/loss ratio, player development) have become of paramount importance.
At any level, athlete development and performance are undeniably
multidimensional components that require dedicated, individualized
approaches. It is now expected that professionals such as S&C coaches
influence performance through the education of athletes, to capitalize on the
non-contact hours; in essence, there is now a need for non-contact coaching
(i.e. the ability to influence athletes’ behaviours and subsequently their
performance when they are away from the training environment). A term
that embraces this concept is ‘marginal gains’. This was coined and
popularized by Sir Dave Brailsford, who sums it up as ‘put simply … how
small improvements in a number of different aspects of what we do can
have a huge impact on the performance of the team’ (Slater, 2012).
Similarly, Clive Woodward describes using a strategy to improve ‘critical
non-essentials’ (CNe). Again, this approach focused on improving the small
details of everything in the preparation for performance. Whilst such
approaches have yielded great success for some athletes and teams, it is
worth noting that such an approach should be reserved for highly developed
athletes who have maximized basic performance-enhancing methods.
Although many of the approaches used within elite sport are outside the
control of S&C coaches (for example, development of technology,
organizational culture, competition schedule, travel arrangements, etc.),
many alterations to daily lifestyle can be prescribed or controlled. These
may include recovery modalities, sleep hygiene, strategies to reduce risk of
infection, ergonomics of equipment and travel, dealing with travelling
across time zones, etc. The aforementioned are concepts rooted in scientific
rationale and are designed and implemented to gain small advantages. The
S&C coach must now be constantly investigating ways to improve physical
outcomes, positive psychology, training environment and performance
lifestyle for athletes to truly gain a competitive edge. However, to reiterate,
the minor advantages achieved via these small modifications are only
meaningful if the S&C coach has successfully implemented key concepts,
such as appropriate analysis, planning, coaching, monitoring and recovery.
Considerations for a modern-day S&C coach
An S&C coach must consider a multitude of factors before commencing a
working relationship with an athlete. Crudely, these can be categorized into
analysis, planning, coaching, monitoring performance, readiness and
recovery (before returning to analysis). Below is a non-exhaustive list of
some of the elements that may need to be considered when working with
athletes.
Analysis (and re-analysis)
Athlete background/objective. Short-, medium-, long-term objectives?
How to monitor success or failure? Injury history? Training
age/history? Biological age? Preferences?
Sport/competition demands. How many games/tournaments?
Frequency of competition? Priority games/tournaments? How long is
the season? Travel demands? Physical demands (how far and fast,
etc.)? Injury prevalence within sport/population, including common
mechanisms of injury?
Postural and movement screening. What type of movement screen?
For what reason are you screening? Are the results meaningful or
confounded by subjectivity? What are the movement dysfunctions?
What drives movement dysfunction? Implications on transfer of force
through the kinetic chain and injury prevalence?
Physical performance testing. Determining successful athletic factors
in the sport? Strength/power/speed/agility/endurance tests? Laboratory
or field-based testing? Reliability and measurement error? Validity of
test? How to interpret and present results?
Planning (within context)
Periodization: block or undulating? How to structure macro-, mesoand micro-cycles? Knowing when to overload and when to taper and
when to rest? How to structure technical sessions?
Exercise programming. Training methods? Associated adaptations?
Exercise selection? Exercise sequence (concurrent or single stimulus)?
Prescription of training loads?
Rehabilitation/prehabilitation. Methods and exercises to tackle highrisk groups/muscles/joints? When to apply prehabilitation strategies?
Return to play/competition strategies? Remedial/preparatory exercise?
Non-contact coaching. Nutritional guidance? Sleep hygiene? Strategies
to reduce the risk of infection? How to prepare for different time zones,
climates, surfaces?
Coaching
Professional knowledge. How to apply fundamental training
principles? Dynamic correspondence of training? Understanding of
sport/competition rules, regulations and physical demands? Knowledge
of skill acquisition and pedagogical theory? Which method of training
and coaching style induces optimal physical and psychological
response (might be different at different times)?
Interpersonal knowledge. How do you communicate with athletes,
coaches and other stakeholders? Awareness of verbal cues (internal vs.
external) and non-verbal communication? How do athletes best retain
information? Are you able to adapt the programme in relation to how
the athlete is feeling?
Intrapersonal knowledge. Do you evaluate sessions? How do you
evaluate? Does it inform future practice? Open and willing to try new
ideas?
Confidence, connection, character. Do you understand what motivates
your athlete/s? How to instil confidence? How to be a role model and
leader? How can you instil good habits that transfer into wider society?
How to create a performance environment?
Monitoring
Monitor training load (TL) and responses to TL. Internal methods?
External methods? Methods to assess response to training?
Performance tests? Physiological markers? Psychological assessments?
Wellbeing? Are the metrics/markers/questions sensitive enough to
detect meaningful changes? Determining differences between
functional overreaching (FO), non-functional overreaching (NFO),
overtraining (OT)? Data analysis? What, how and to whom to report
the information? What actions are required as a result?
Recovery
Do we need to use recovery strategies at this point? What is the aim of
a recovery strategy? What are the best strategies? When to apply?
Should everyone use the same recovery strategy? Are they proactively
planned or reactive to environment? Physiological and pschosocial
response?
Then return to analysis.
Conclusion
The role of an S&C coach is multifaceted and fundamentally requires the
individual to effectively interact and communicate with relevant
stakeholders as well as apply scientific principles in the pursuit of
optimizing sporting performance. Additional skills deemed integral to the
role include organization, administration, athlete motivation, education and
public relations (Kraemer, 1990). In an era when substantial financial
investments and the adoption of strategic approaches to enhancing
performance are commonplace, it is unsurprising that a largely evidencebased culture has evolved. S&C coaches must analyse, interpret and
influence decision making using facts and figures. Hunches and instincts
are becoming increasingly more difficult to justify to technical coaches and
managers, and can rarely promote change. Although traditionally a coach
may value professional knowledge above all else, it is recommended that
equal attention be applied to both the development of interpersonal skills
and reflective practices.
In summary, the discipline of S&C requires the individual to be both an
effective coach and an interdisciplinary sport scientist. (See Figure 1.1 for a
non-exhaustive list of coaching and applied science principles.) These
required skill sets should be embraced and seen as essential if the S&C
coach is to truly be effective. Therefore, due to the breadth and depth of
knowledge and skills required it may be suggested that S&C coaches should
strive to be excellent ‘generalists’ and consider being a ‘specialist’ in a
specific area of expertise once the basics have been mastered. The
following chapters provide a greater in-depth analysis of these areas and are
an important part of appreciating the role of the contemporary S&C coach.
Integration of coaching and applied science principles. S&C, strength and
conditioning; TL, training load.
The chapters will be principally structured in two sections: (1) an
objective and concise review of pertinent literature in the specific subject
area; and (2) a discussion (including applied examples) of context-specific
real-world practical applications.
References
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Burwitz, L., Moore, P.M., & Wilkinson, D.M. 1994. Future directions for
performance-related sports science research: An interdisciplinary
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Côté, J., & Gilbert, W. 2009. An integrative definition of coaching
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without a plan: The career experiences of Australian strength and
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Dorgo, S. 2009. Unfolding the practical knowledge of an expert strength
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Hartshorn, M.D., Read, P.J., Bishop, C., & Turner, A.N. 2016. Profile of a
strength and conditioning coach: Backgrounds, duties, and perceptions.
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Strength & Conditioning Journal, 12(6), 72–73.
Martindale, R., & Nash, C. 2013. Sport science relevance and application:
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(accessed 1 November, 2021).
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practices of National Basketball Association strength and conditioning
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the organizational stressor experiences of sport science and management
staff in elite sport. Journal of Applied Sport Psychology, 31(1), 7–26.
Part I
Developing your athlete
2
Developing muscular strength
and power
Timothy J. Suchomel and Paul Comfort
DOI: 10.4324/9781003044734-4
Introduction
In this chapter we explore the importance of muscular strength and power
to sport performance, discuss the physiological underpinnings, and consider
various methods of improving these qualities in athletes. While basic
concepts of periodisation and programming for improving strength and
power characteristics will be mentioned within this chapter, more thorough
discussions can be found in Chapter 7, as well as Stone et al. (1982),
Bompa and Haff (2009), and DeWeese et al. (2015a, 2015b).
SECTION 1
The importance of muscular strength and power for athletes
Muscular strength is defined as the ability to exert force on an external
resistance (Stone, 1993). Based on the demands of a sport or an event, an
athlete may have to manipulate (e.g., accelerate/decelerate) their own body
mass against gravity (e.g., sprinting, gymnastics, etc.), both their body mass
and an opponent’s body mass (e.g., rugby, wrestling, etc.), or an external
object (e.g., soccer, weightlifting, etc.). Ultimately, the force exerted and the
duration over which it is applied (impulse = force × time) will change the
motion of a body in space. This concept is based on Newton’s second law
(i.e., the law of acceleration), whereby force is equal to the product of mass
and acceleration (force = mass × acceleration). Based on this principle, the
acceleration of a given mass is directly proportional to, and in the same
direction as, the force applied and the duration over which it is applied.
Thus, it appears that muscular strength is the primary factor for producing
an effective and efficient movement of an athlete’s body or an external
object. This concept has been supported throughout the literature as
muscular strength (maximal force production) has been correlated to greater
rate of force development (RFD), power output, jump height, sprinting
speed, change-of-direction performance, sport-specific skills, and postactivation potentiation (PAP) magnitude (Suchomel et al., 2016b).
Previous researchers and practitioners have indicated that RFD and
power output are two of the most important characteristics regarding an
athlete’s performance (Morrissey et al., 1995; Baker, 2001b; Stone et al.,
2002). Given that muscular strength serves as the foundation upon which
other abilities can be enhanced, it should come as no surprise that greater
magnitudes of RFD and power output are by-products of increased strength.
However, it should be noted that when assessing power, changes in
technique alone (e.g., jump strategy during a countermovement jump) can
alter the power output. Ultimately, it is the relative net impulse that
determines acceleration, therefore both the force and time over which it is
generated are key to enhancing performance in athletic tasks.
Rate of force development
RFD may be defined as the change in force divided by the change in time,
with the ability to rapidly produce force being critical given the time
constraints of various tasks. For example, during high-velocity sprinting,
ground contact times are <250 ms, with a progressive decline in contact
time as velocity increases (Weyand et al., 2000; Morin et al., 2012; Haugen
et al., 2018), reaching contact times as low as 80 ms when running at
velocities >11 m·s−1 (Tidow, 1990). The importance of rapid force
production is further supported by the fact that it takes a longer duration
(>300 ms) to produce a maximum force (Aagaard et al., 2002a; Andersen et
al., 2003) compared to the duration of jumping and ground contact time
during sprinting (Andersen and Aagaard, 2006). As mentioned above,
increases in muscular strength enhance an athlete’s ability to increase their
magnitude and RFD. The results of previous research, albeit assessing force
production via single-joint tasks, has demonstrated that resistance training
may enhance an athlete’s RFD characteristics, which may lead to improved
performance (Häkkinen et al., 1985; Aagaard et al., 2002a, 2010). In a
review, Taber et al. (2016) provided evidence that RFD, along with greater
muscular strength, may underpin the development of greater power output
(Figure 2.1). Interestingly, the results of a recent training intervention
indicate that high-load (80–90% 1RM, where 1RM = one repetition
maximum), multi-joint resistance training, which follows moderate-load
training (60–82.5% 1RM), results in superior increases in early multi-joint
force production (force at 50, 100, 150, 200, and 250 ms) assessed via the
isometric mid-thigh pull, compared to the changes observed after moderateload resistance training (Comfort et al., 2020).
Comparison of countermovement jump kinetic and temporal variables
between stronger and weaker athletes. RFD, rate of force development.
Power output
As mentioned above, alongside RFD, power output is considered one of the
most important characteristics regarding an athlete’s performance. Power
output may be defined as the rate of performing work, with any sport task
requiring the completion of a given amount of mechanical work. While the
work performed is important, athletes have limited time to perform these
tasks and, thus, it would seem beneficial to complete the work in the
shortest duration possible. For example, an athlete who completes the
required work of a given task more quickly may be given a competitive
edge compared to their opponent (e.g., rebound in basketball) or may win
the overall competition (e.g., 100-m sprint). The findings of previous
research indicate that power output differs between the playing level of
athletes (Fry and Kraemer, 1991; Baker, 2001a; Hansen et al., 2011) and
between starters and non-starters in various sports . Furthermore,
researchers have noted strong relationships between power output and
performance characteristics such as sprinting (Weyand et al., 2000, 2010),
jumping (Newton et al., 1999; Hori et al., 2008), change of direction
(Nimphius et al., 2010; Spiteri et al., 2012), and throwing velocity (McEvoy
and Newton, 1998; Marques et al., 2011). Given the importance of power
output to an athlete’s success, many strength and conditioning practitioners
have sought to improve these qualities through various training strategies.
Common training strategies that have been used to enhance power output
will be discussed in the second half of this chapter.
Impulse
Impulse may be defined as the amount of force produced over a given time
period (impulse = force × time). This characteristic has been deemed
important due to the fact that relative net impulse ultimately determines
vertical jump performance (Kirby et al., 2011) and may influence
weightlifting performance (Garhammer and Gregor, 1992). Due to its
influence on movement, it is important to understand how muscular
strength characteristics influence the shape of an athlete’s relative net
impulse. For example, McMahon et al. (2017) indicated that senior-level
rugby athletes applied greater relative impulses during the braking and
propulsive phases of a countermovement jump compared to academy-level
athletes, resulting in greater jump heights in the senior athletes. While the
shape of an athlete’s applied impulse may be affected by their jumping
strategy (e.g., shallow versus deep countermovement), it should be noted
that the ability to rapidly apply force during both the braking and propulsive
phases also plays a role. If an athlete is strong enough to tolerate a rapid
countermovement, it is likely that the shape of their impulse will be taller
(higher-force) and skinnier (reduced-duration); however, a weaker athlete
who cannot decelerate momentum as effectively may produce a shorter
(lower-force) and wider impulse (longer-duration) (McMahon et al., 2018).
The component pieces of force production and time are important given the
constraint of time within sports.
Morphological factors affecting strength and power
Cross-sectional area
Researchers have indicated that an increase in an athlete’s muscle crosssectional area (CSA) and work capacity (i.e., force production capacity)
may lead to an enhanced ability to increase their muscular strength (Stone
et al., 1982; Minetti, 2002; Zamparo et al., 2002). Typically, this is achieved
via a resistance-training phase that includes a high volume of work
completed with moderate to moderately high intensity (60–80% 1RM).
Greater detail will be provided in the second half of this chapter.
An increase in muscle fibre CSA results in an increased size of the
overall muscle (hypertrophy). From a physiological perspective, increases
in muscle CSA lead to improved force production capacity due to an
increased number of newly formed sarcomeres (i.e., the smallest contractile
units within muscle cells). Simply put, an increase in the number of
sarcomeres increases the number of potential interactions between actin and
myosin microfilaments (i.e., cross-bridges) which ultimately increases the
force-generating capacity of a muscle. This is supported by research from
Kawakami et al. (1993) indicating that muscle fibre pennation angles are
greater in hypertrophied muscles. A greater pennation angle permits a
greater number of cross-bridge interactions to occur within a given area of
the muscle, due to the packing of muscle fascicles within the area (Figure
2.2).
Medial gastrocnemius (MG) fascicle length (dashed line) and MG pennation
angle (θ), as measured between the superficial (A) and deep (B) MG
aponeuroses.
Another influence on the CSA of muscle fibres is the ratio of type II
fibres to type I fibres. The results of previous research indicated that an
increased CSA following resistance training coincided with a greater type
II:I ratio due to a greater rate of hypertrophy of type II muscle fibres
compared to type I fibres (Campos et al., 2002). Additional research
findings demonstrate that a greater percentage change in type II:I ratio
following 8 weeks of resistance training strongly correlated with the
percentage change of squat jump power (Häkkinen et al., 1981). Thus, it
appears that an increased CSA coinciding with a greater type II:I ratio may
increase the ability to generate power by altering the force–velocity
characteristics of the muscle. However, it should be noted that the training
method will greatly impact which motor units will be recruited and thus
affect which muscle fibres (e.g., type I, IIa, IIx) adapt to the training
stimulus. This concept is discussed in greater detail below (see the section
‘Neuromuscular factors affecting strength and power’).
The training method may also affect how additional sarcomeres are
added. For example, high-force training (i.e., resistance training) may result
in increases in a muscle’s CSA by adding sarcomeres in parallel (Figure
2.3), which may increase the overall force produced by the muscle given
that each sarcomere acts independently. In contrast, high-velocity training
(e.g., plyometrics, discussed in detail in Chapter 17) may add sarcomeres in
series (Figure 2.4), which may increase shortening velocity at the expense
of force production given that the sarcomeres in series pull against each
other (Suchomel et al., 2019b). This concept is important to consider given
the demands of athletes in various sports.
Four sarcomeres in parallel. (Adapted from Stone et al., 2007.)
Four sarcomeres in series. (Adapted from Stone et al., 2007.)
Muscle architecture
While the overall size of the muscle may affect the magnitude of force
produced, additional muscle architecture characteristics may affect muscle
tension. A muscle’s pennation angle may be defined as the angle in which
the fascicles (i.e., bundle of muscle fibres) attach to the superficial or deep
aponeurosis (Figure 2.2). The muscle’s pennation angle will determine the
force–velocity characteristics of the muscle. For example, a greater
pennation angle will allow the muscle to place a greater emphasis on force
due to the ability to pack more muscle fascicles into a given area, leading to
a greater number of cross-bridge interactions and enhanced force
production (Huxley, 1974). In contrast, a smaller pennation angle will place
a greater emphasis on velocity due to the position of the fascicles being
more parallel in relation to the muscle’s aponeuroses, leading to a greater
shortening velocity due to the combined shortening of sarcomeres across
the area of the muscle belly.
Researchers have assessed longitudinal changes in muscle architecture
(i.e., muscle thickness, pennation angle, and fascicle length) following
various resistance-training programmes, illustrating that changes in muscle
architecture may affect performance outcomes. For example, Nimphius et
al. (2012) indicated that moderate increases in fascicle length following
resistance training were strongly correlated with sprint times to first and
second base from home plate in elite softball players. In addition,
Kawakami et al. (1995) and Aagaard et al. (2001) observed increases in
muscle thickness and pennation angles following heavy strength training.
Such adaptations may be favourable when it comes to producing greater
overall magnitudes of force within the muscle. Further research findings
indicated that training with relatively high movement velocity and lighter
loads (<60% 1RM) may produce increases in fascicle length with no
changes in pennation angle (Blazevich et al., 2003; Alegre et al., 2006).
From a practical standpoint, architectural changes of this nature may
increase the overall shortening velocity of the muscle, likely leading to
greater increases in power output. Based on the results of previous
literature, it appears that muscle architectural changes may be specific to
the muscle actions performed (Table 2.1). Additional research comparing
eccentric and concentric muscle action training supports this notion
(Blazevich et al., 2007; Franchi et al., 2014).
Table 2.1
Training
stimulus
Muscle architectural adaptations in response to different training stimuli
CSA Pennation Fascicle Fascicle ↑
↑
angle
length
thickness Sarcomeres Sarcomeres
in series
in parallel
Hypertrophy ↑
↑
↓
↑
No
Yes
Strength
↑
↑
↓
↑
No
Yes
Power
–
↓
↑
–
Yes
No
Eccentric
focus
–
↓
↑
–
Yes
No
CSA, cross-sectional area; ↑ = increase; ↓ = decrease; – = minimal change.
It should be noted that the changes in muscle size and pennation angle
may not be uniform throughout an entire muscle belly (Ema et al., 2013;
Wells et al., 2014). Given the demands of various sport tasks, non-uniform
hypertrophy may result in greater growth proximally or distally depending
on the activation of musculature during training (Wakahara et al., 2012).
For example, the quadriceps muscles of track and field sprinters may
hypertrophy more proximally than track cyclists due to the lower-limb
mechanics required. This idea becomes important when selecting exercises
with the intent of increasing the probability that training-induced
adaptations will transfer to an athlete’s performance.
Neuromuscular factors affecting strength and power
Motor unit recruitment
A motor unit may be defined as an alpha motor neuron and all the muscle
fibres it innervates. The magnitude and rate of force produced coincide with
the number and type of motor units recruited. Classic work from Henneman
and colleagues (1965) indicates that motor units are recruited in a
sequenced manner based on their size (Henneman’s size principle). Motor
units are recruited in order from smallest to largest based on the
neuromuscular requirements of the activity. For example, smaller motor
units that include slow-twitch type I fibres are recruited at low force
magnitudes and are followed by larger motor units that include fast-twitch
type IIa and IIx fibres if higher force and RFD are required. While the size
principle appears to hold true during slow, graded actions as well as
isometric actions (Milner-Brown and Stein, 1975) and ballistic actions
(Desmedt and Godaux, 1977, 1978), it should be noted that motor unit
recruitment thresholds may be lowered during ballistic-type movements due
to a greater RFD demand (van Cutsem et al., 1998). Thus, the ability to
recruit high-threshold motor units during training would be beneficial to the
improvement of muscular strength, RFD, and power.
For a motor unit to be trained, it must be recruited. As mentioned above,
the nature of the activity will directly affect what motor units are recruited
and how they will respond to training. For example, a distance runner
repeatedly recruits low-threshold, slow-fatiguing (type I) motor units due to
the low/moderate forces that are produced during each stride. Due to the
nature of the task, high-threshold (type II) motor units may not need to be
recruited until the type I motor units fatigue and additional force production
is needed to sustain the activity. In contrast, weightlifters performing the
snatch require high magnitudes and rates of force production during a task
that lasts less than 5 seconds. In this case, both low- and high-threshold
motor units are recruited due to the order of recruitment. However, it
appears that the preferential recruitment of high-threshold motor units
would be beneficial for the weightlifter in order to enhance muscular power
(Kraemer et al., 1996; Duchateau and Hainaut, 2003). Seminal work by van
Cutsem et al. (1998) demonstrated that while the orderly recruitment of
motor units existed during both slow, ramp and ballistic actions following
ballistic-type training, motor units were recruited at lower force thresholds.
From a practical standpoint, training methods that are ballistic in nature will
allow recruitment of larger, type II motor units at lower thresholds, thus
allowing for positive strength and power adaptations to occur, even without
near-maximal loads.
Firing frequency (rate coding)
Firing frequency may be defined as the frequency at which neural impulses
are transmitted from the α-motoneuron to the muscle fibres of recruited
motor units. Following the recruitment of specific motor units, force
production properties may be modified in two ways by the firing frequency.
Enoka (1995) indicated that force production magnitude may increase
upwards to 300–1500% when the firing frequency of recruited motor units
increases from its minimum to its maximum. In addition, RFD may be
impacted by the firing frequency of motor units due to high initial firing
frequencies being linked to an increase in doublet discharges (i.e., two
consecutive motor unit discharges in ≤5 ms) (van Cutsem et al., 1998). Both
the increase in magnitude and RFD, as the result of an increased firing
frequency, may ultimately contribute to positive strength and power
adaptations. Practically speaking, certain training methods may lead to
improvements in the firing frequency of recruited motor units. Previous
research findings demonstrate that ballistic-type training may enhance
motor unit firing frequency within 12 weeks (van Cutsem et al., 1998).
Additional researchers suggest that other ballistic training methods, such as
weightlifting movements (Leong et al., 1999) and sprinting (Saplinskas et
al., 1980), may enhance motor unit firing frequency, leading to enhanced
strength-power characteristics.
Motor unit synchronisation
Motor unit synchronisation refers to the simultaneous activation of two or
more motor units resulting in increased force production. While the
physiological underpinnings are not fully understood, some literature
indicates that motor unit synchronisation is more related to RFD compared
to the magnitude of force produced (Semmler, 2002). Milner-Brown and
Lee (1975) indicated that 6 weeks of strength training led to an increase in
motor unit synchronisation. Results of another study indicated that motor
unit synchronisation strength was largest in the dominant and non-dominant
hands of weightlifters compared to musicians and untrained individuals
(Semmler and Nordstrom, 1998). Although van Cutsem et al. (1998) found
that motor unit synchronisation did not appear to change following ballistictype training, another study indicated that motor unit synchronisation was
enhanced during tasks that require movement, especially those involving
rapid muscle actions (Semmler et al., 2000). Finally, Aagaard et al. (2000)
suggested that heavy strength training (~6RM loads) may result in an
increase in motor unit synchronisation, possibly contributing to force
production.
Neuromuscular inhibition
Neuromuscular inhibition, which refers to a reduction in the voluntary
neural drive of a given muscle group during voluntary muscle actions, may
negatively affect force production due to neural feedback received from
muscle and joint receptors (Gabriel et al., 2006). Undoubtedly, neural
mechanisms that negatively affect the development of force and power may
alter potential adaptations. However, Aagaard et al. (2000) indicated that
heavy strength training (~6RM loads) may down-regulate Ib afferent
feedback to the spinal motoneuron pool, ultimately reducing neuromuscular
inhibition and increasing force production. Results of additional studies
highlighted an enhanced neural drive from the spinal and supraspinal levels
following strength training that coincided with a decrease in neuromuscular
inhibition (Aagaard et al., 2002b) and enhanced RFD (Aagaard et al.,
2002a; Table 2.2). Taking the above into account, heavy resistance training
may lead to an enhanced neural drive, increased RFD, and decreased
neuromuscular inhibition, creating potential enhancements in the strengthpower characteristics of athletes.
Table 2.2
Neurological adaptations in response to different training stimuli
Training
stimulus
MU
Firing
recruitment frequency
MU
Neuromuscular
synchronisation inhibition
Hypertrophy
↑
↓
↓
↑
Strength
↑
↑
↑
↓
Power
↑
↑
↑
↓
Eccentric focus
↑
↑
↑
↓
MU, motor unit; ↑ = increase; ↓ = decrease; – = minimal change.
SECTION 2
Training considerations for improving muscular strength and
power
In addition to understanding the physiological underpinnings that affect
both strength and power, practitioners must select a periodisation model,
exercises and/or training methods, the movement intent (i.e., ballistic or
non-ballistic), and loads for each exercise, all while implementing each
factor in a sequenced progression. Moreover, the athlete’s training status
must be considered, as certain training methods may be more appropriate
for those who are more/less well trained. Readers are directed to Suchomel
et al. (2018a) and Cormie et al. (2011) for more thorough reviews on
developing muscular strength and neuromuscular power, respectively.
Periodisation model
An abundance of periodisation models exist within the strength and
conditioning field. Much of the extant literature supports the notion that
block periodisation may provide superior results compared to other models,
as discussed by DeWeese and colleagues (2015a). This model is based on
the idea that a concentrated load may be used to emphasise the development
of one specific characteristic during each training phase, while maintaining
the previously developed characteristic(s) (Figure 2.5). This appears to be
advantageous considering that researchers and practitioners have indicated
that it may be difficult, and potentially less productive, to develop multiple
physiological characteristics or motor abilities simultaneously (Stone et al.,
2007; Issurin, 2008, 2010). It should be noted that other models of
periodisation may still provide an effective blueprint for developing an
athlete’s strength-power characteristics (e.g., traditional, undulating,
conjugate, etc.). However, further research comparing periodisation models
with different athletic populations, with different competition schedules, is
still needed to determine their effectiveness. Periodisation and the
effectiveness of various periodisation models for athletic performance are
explored in greater detail in Chapter 7.
Example emphasis change during a periodised training programme (phase
potentiation). 1RM, one repetition maximum.
Resistance-training methods
The type of training method may provide a vastly different stimulus that
may affect gains in muscle CSA, strength, or power. As discussed in
Chapters 7 and 15, the training mode and exercises should be selected based
on their ability to achieve the goals of each training phase. For example,
exercises may be selected based on their power characteristics. Because
power is the product of force and velocity, certain exercises may emphasise
one or both characteristics. Simply put, force–velocity, force–velocity or
force–velocity are all combinations of exercise types used in training. Table
2.3 displays relative power outputs of a variety of exercises discussed
within the literature.
Table 2.3
Relative power outputs for male athletes during various exercises
Exercise
Relative power outputs: Force–velocity
male (W kg−1)
characteristics
Clean
33–80
Hang power clean
22–47
Jerk
44–80
Jerk drive
28–56
Power clean
25–80
Snatch
34–80
Clean pull from floor
33–80
Hang high pull
47–54
Hexagonal barbell
jump
45–80
Jump shrug
57–87
Mid-thigh clean pull
from dead stop
35–67
Mid-thigh snatch pull
from dead stop
35–48
Snatch pull from floor
30–80
Countermovement
jump squat
64–75
Static jump squat
58–69
Bench press
0.3–8.3
Deadlift
11–13
Squat
11–30
High-force and high-velocity
movements
Moderate–high-force and moderate–
high-velocity movements
Low-force and high-velocity
movements
High-force and low-velocity
movements
Notes: The relative power outputs displayed may vary based on the level of the athlete, load lifted,
technical efficiency of the athlete, and method used to quantify power output. The data presented
represent the ranges of averages across various loads within the literature.
(Adapted from Garhammer (1980, 1985, 1991, 1993), Haff et al. (1997, 2001, 2012, 2015),
McBride et al. (1999), Driss et al. (2001), Kawamori et al. (2005), Cormie et al. (2008), Stone et
al. (2008), Thompson et al. (2010), Comfort et al. (2012, 2015) and Suchomel et al. (2013, 2014,
2015, 2019a).)
Bodyweight exercise
Bodyweight exercise is one of the most basic forms of resistance training
that has been used for decades. Some of the most common bodyweight
exercises, such as bodyweight weight squats, push-ups, pull-ups, and situps, are still implemented in resistance-training programmes to this day as a
training exercise, progression, or regression. Bodyweight exercises have
several advantages, including being specific to the individual’s
anthropometrics and muscle/tendon insertion, the inclusion of closed-chain
exercises, the ability to train multiple muscle groups simultaneously, and its
accessibility and versatility compared to other training methods (Harrison,
2010).
Like any training method, bodyweight exercise has its limitations. The
most obvious limitation of bodyweight exercises is the inability to continue
to provide an overload stimulus to the athlete, preventing a significant
transfer to absolute strength measures (Harrison, 2010). For example,
practitioners may continue to prescribe a greater number of repetitions or
modify the movement (e.g., bilateral squat → split squat → single-leg
[unilateral] squat, etc.) in order to progress each bodyweight exercise.
However, a continual increase in repetitions would lead to an emphasis on
strength-endurance characteristics instead of the development of strengthpower characteristics necessary for enhanced sport performance. Based on
their advantages and limitations, it is suggested that bodyweight exercises
should be prescribed to enhance basic strength and movement
characteristics before progressing to other training methods that may result
in greater strength and power adaptations.
Machine vs. free-weight training
When prescribing either machine or free-weight exercises, practitioners
should note that each method has its limitations. For example, machinebased exercises allow for the isolation of specific muscle groups, which
may be important from a rehabilitation standpoint. However, utilising
machine-based exercises for sport performance may be questionable.
Researchers have indicated that athletic movements rarely include muscle
actions performed in an isolated manner (Behm and Anderson, 2006), with
the transfer from isolation (single-joint) exercises to athletic performance
being somewhat limited (Augustsson et al., 1998; Blackburn and Morrissey,
1998; Östenberg et al., 1998). Thus, it appears that exercises that
incorporate multiple muscle groups may provide a superior training
alternative (Bobbert and Van Soest, 1994; Anderson and Behm, 2005).
Furthermore, it is been noted that free-weight exercises may recruit muscle
stabilisers to a greater extent than machine-based exercises (Haff, 2000).
Collectively, it appears that the movement similarities with athletic
movements and the recruitment of muscle stabilisers of free-weight
exercises may produce greater strength-power adaptations as they relate to
sport performance.
Training with weightlifting movements
Weightlifting exercises produce some of the greatest power outputs
compared to other types of exercise (Table 2.3). Given the importance of
muscular strength and power in sport, it is not surprising that many
practitioners implement the weightlifting movements and their derivatives
within resistance-training programmes. Weightlifting movements are
unique in that they exploit both the force and velocity aspects of power
output by moving moderate–heavy loads with ballistic intent. In fact,
weightlifting pulling derivatives (i.e., those that remove the catch phase)
may expand the force and velocity spectrum of weightlifting exercises and
produce superior strength, sprint, jump, and change-of-direction training
adaptations compared to weightlifting catching derivatives alone (Suchomel
et al., 2017, 2020a, 2020b). One key advantage of the ballistic nature is the
fact that the athlete aims to accelerate throughout the propulsive phase,
whereas exercises such as the bench press and squat result in deceleration
during the later stages of the propulsive phase (Newton et al., 1996; Lake et
al., 2012b). Previous researchers have demonstrated that weightlifting
movements may provide a superior strength-power training stimulus
compared to jump training (Tricoli et al., 2005; Teo et al., 2016), traditional
resistance training (Hoffman et al., 2004; Channell and Barfield, 2008;
Arabatzi and Kellis, 2012; Chaouachi et al., 2014), and kettlebell training
(Otto III et al., 2012). Greater detail regarding the use of weightlifting
movements during resistance training will be provided in Chapter 16.
Plyometric training
While a thorough discussion of plyometric exercises will be provided in
Chapter 17, this chapter will provide a brief discussion on their
effectiveness as a strength-power training stimulus. Plyometric movements
may be defined as quick, power-based movements that utilise a prestretch/countermovement that includes the stretch-shortening cycle (SSC).
Specifically, plyometrics refer to a concentric muscle action that is
enhanced by a rapid preceding eccentric muscle action, generally with a
movement time of <250 ms. Their ballistic nature, combined with an
emphasis on power development, has led to their use within strength and
conditioning programmes for athletes. The authors of a meta-analysis
concluded that training with plyometric exercises may produce similar
improvements in jump height compared to training with weightlifting
exercises (Hackett et al., 2016), demonstrating that plyometrics may be an
effective training stimulus for athletes.
When it comes to designing a plyometric training programme,
practitioners should consider the fact that plyometric exercises are a form of
resistance training and should therefore be periodised. Previous research
findings demonstrate the effectiveness of programming plyometric
exercises in a periodised fashion during 6-week training programmes by
decreasing the volume of foot contacts and increasing the intensity of the
plyometric exercises during the final 4 weeks of the training (Ebben et al.,
2010, 2014). Practitioners should also consider the frequency of training
sessions, length of programme, and recovery time between repetitions, sets,
and training sessions. Typical training frequencies range from 1 to 3
sessions per week, while the length of most programmes ranges from 6 to
10 weeks (Allerheiligen and Rogers, 1995).
Most plyometric exercises are implemented using the athlete’s body
mass as the resistance to ensure a short movement duration and rapid prestretch of the muscle to stimulate the SSC. However, using only the
athlete’s body mass as a resistance may be limited in terms of strengthpower development. Practitioners may be able to prescribe small additional
loads to increase the loading stimulus on the athlete; however, a more
sensible method would be to increase plyometric exercise intensity, while
simultaneously adjusting the volume to meet the needs of each athlete. See
Chapter 17 for a detailed discussion of plyometric training.
Eccentric training
Eccentric muscle actions are those that lengthen the muscle as a result of a
greater force being applied to a muscle than the muscle itself can produce.
Although not well understood, eccentric muscle actions result in unique
molecular and neural characteristics that may contribute to a variety of
adaptations (Douglas et al., 2017b; Suchomel et al., 2019b). Douglas et al.
(2017a) indicated that eccentric training may produce similar or greater
adaptations in muscle mechanical function (e.g., muscular strength,
muscular power, RFD, and stiffness), morphological adaptations (e.g.,
tendon and muscle fibre CSA), neuromuscular adaptations (e.g., motor unit
recruitment and firing frequency) and performance (e.g., vertical jumping,
sprint speed, and change of direction) compared to concentric, isometric,
and traditional (eccentric/concentric) training. Due to the potential
adaptations listed above, it is not surprising that eccentric exercise has
received growing interest as a training stimulus.
Although interest in utilising eccentric training has grown, less is known
about how to effectively implement this type of training. Recent reviews
highlighted some of the most common methods of eccentric training (e.g.,
tempo, flywheel inertial training, accentuated eccentric loading [AEL], and
plyometric training) and provided some insight on how these methods may
be implemented within an athlete’s resistance-training programme
(Suchomel et al., 2019b, 2019c). It should be noted that researchers have
indicated that adaptations from eccentric exercise are based on their
intensity (Malliaras et al., 2013; English et al., 2014) and eccentric phase
speed (Farthing and Chilibeck, 2003; Isner-Horobeti et al., 2013; Stasinaki
et al., 2019). It is worth noting, however, that performing the lowering
phase of an exercise rapidly initially results in a reduction in force, to
permit gravitational acceleration, with a higher force required during the
braking phase, to permit deceleration over a shorter duration. Taking this
into account, higher eccentric loads may produce favourable adaptations
compared to lighter loads. Interestingly, practitioners have the opportunity
with eccentric-type training to prescribe loads in excess of what the athlete
can lift concentrically (i.e., > 1RM). This concept will be explored in
greater detail in Chapter 12.
Another aspect to consider with eccentric training is the type of
movement(s) the athlete can perform. For example, much of the previously
discussed literature within this section has focused on eccentric-only
movements. However, AEL is becoming increasingly popular amongst
practitioners and researchers. Training with AEL involves performing the
eccentric phase of a lift with a heavier load than the concentric phase as a
result of a portion of the load being removed by a weight release system
(Ojasto and Häkkinen, 2009; Wagle et al., 2018; Lates et al., 2020), spotters
(Brandenburg and Docherty, 2002), or the athlete dropping it (Sheppard et
al., 2008) at the end of the eccentric phase. Collectively, the results of the
previous studies provide evidence that AEL may produce greater
adaptations in explosive performance characteristics (i.e., jumping,
sprinting, and concentric power). Although a limited body of literature
exists, it appears that AEL may provide an effective training stimulus to
improve an athlete’s strength-power performance. A further discussion of
AEL and its benefits may be found in Chapter 12 and within a review by
Wagle et al. (2017).
Complex training and strength-power potentiation complexes
Complex training (CT) is a training method that involves completing a
resistance-training exercise prior to performing a ballistic exercise that is
biomechanically similar (Robbins, 2005). For example, back squats may be
paired with countermovement jumps, while the bench press may be paired
with bench press throws. CT may allow athletes to perform high-force or
power exercises at a higher intensity compared to traditional training
(Verkhoshansky, 1986; Ebben et al., 2000), ultimately creating a superior
training stimulus. In theory, CT may result in greater strength and speed
adaptations compared to traditional resistance-training methods
longitudinally by providing a broader range of training stimuli (Ebben and
Watts, 1998; Jones and Lees, 2003).
A topic of frequent research that uses CT principles is PAP. PAP is
defined as an acute enhancement in performance as a result of the muscle’s
contractile history (Robbins, 2005). Training complexes designed to
produce a potentiated state are termed strength-power-potentiating
complexes (SPPCs) (Robbins, 2005; Stone et al., 2008). SPPCs involve
performing a high-force or high-power movement to potentiate the
performance of a subsequent high-velocity or power movement. While
several studies have demonstrated that various potentiation stimuli may
acutely enhance strength-power performance (Gullich and Schmidtbleicher,
1996; Young et al., 1998; Bullock and Comfort, 2011), a number of factors
within the SPPC or the athlete’s characteristics may affect the magnitude of
potentiation produced (Suchomel et al., 2016a). Thus, it is not surprising
that similar SPPCs resulted in no change or a decrease in subsequent
performances in other studies (Jensen and Ebben, 2003; Till and Cooke,
2009; Tsolakis and Bogdanis, 2011). While the concept of using
implementing SPPCs within an athlete’s resistance-training programme is
appealing, limited research has examined the longitudinal effects of training
with SPPCs (Docherty and Hodgson, 2007). In addition, practitioners
should note that SPPCs may not be as appropriate for weaker individuals as
greater muscular strength may lead to faster and greater potentiation
(Miyamoto et al., 2013; Seitz et al., 2014; Suchomel et al., 2016d). Finally,
it should be noted that the long-term use of SPPCs may not be appropriate
given the goals of specific resistance-training phases. For example,
implementing SPPCs may be specific to the goals of a strength-speed
phase, but counterproductive during a strength-endurance phase.
Unilateral vs. bilateral training
Some practitioners may argue that unilateral exercises may be more sportspecific given the unilateral weight-bearing phase of various sport tasks
(e.g., sprinting, cutting tasks, etc.). Thus, a frequent topic of discussion
within the strength and conditioning field is the use of unilateral exercises
compared to bilateral exercises. Unilateral/partial unilateral movements
may be defined as those where the resistance is unevenly distributed
between an individual’s limbs, whereas bilateral movements are those
where the resistance is distributed evenly, for the most part, between an
individual’s limbs (McCurdy et al., 2005). The majority of resistancetraining programmes implement predominantly bilateral exercises for
strength and power development. This is not surprising given that strong
relationships exist between bilateral strength and sprinting, jump height and
peak power, and change-of-direction performance (Suchomel et al., 2016b).
However, in order to provide practitioners with a variety of options for
exercise prescription, further discussion on unilateral exercise is needed.
Several studies have compared the training effects of unilateral and
bilateral training. McCurdy et al. (2005) examined the strength and power
adaptation differences following 8 weeks of unilateral or bilateral strength
training and plyometric exercise in untrained subjects. Their results
indicated that both groups improved to a similar extent, suggesting that
either mode of training may be equally as effective. Makaruk et al. (2011)
indicated that both unilateral and bilateral plyometric training improved
both countermovement jump and alternate leg-bounding performance in
previously untrained females. However, the authors also noted that only the
bilateral training group retained their training adaptations following a 4week detraining period. Another study indicated that similar improvements
in unilateral and bilateral strength, sprint speed, and agility were displayed
by academy rugby players following 5 weeks of either training with the rear
foot elevated split-squat or traditional back-squat exercise (Speirs et al.,
2016). Although no difference was seen in sprint adaptations, Appleby and
colleagues (2020) showed that greater change-of-direction adaptations may
occur following bilateral training compared to unilateral training. In
addition, Appleby et al. (2019) indicated that both unilateral and bilateral
movements may improve strength characteristics in movement-specific
tasks, but may also transfer these improvements to other non-trained
movements. Collectively, the previous studies indicate that training with
unilateral exercises may be an effective alternative to bilateral exercises
when it comes to improving various performance parameters. However,
practitioners should focus on the physiological stimulus rather than
movement specificity when selecting exercises in order to maximise
training results (Appleby et al., 2020).
Previously, researchers indicated that gluteus medius, hamstring, and
quadriceps activation was greater during a modified split squat compared to
a traditional bilateral squat (McCurdy et al., 2010), which should not be
overly surprising given the decreased stability of unilateral exercises.
However, decreased stability may be viewed as a limitation because it is
difficult to prescribe heavy loads with unilateral exercises. Given that
greater stability within a movement may lead to a greater potential to
express force (Behm and Anderson, 2006), it appears that bilateral exercises
may serve as a better foundation for improving an athlete’s strength-power
characteristics. However, that is not to say that unilateral exercises should
not be programmed; rather, they should be implemented as assistance
exercises to bilateral movements (Ramirez-Campillo et al., 2018),
especially during the general preparatory phase of training.
Variable-resistance training
Traditional resistance-training methods typically involve performing
exercises with an eccentric and concentric component in which the external
load remains constant throughout the entire range of motion. While this
type of training has become an essential addition to training programmes, it
is not without its limitations. For example, an athlete performing a back
squat may be limited at the lowest point of the squat due to a decreased
capacity to produce force in that position. As a result, athletes may
experience a ‘sticking point’ when they begin to ascend, due to mechanical
disadvantages being present within the active musculature. In contrast,
muscle force production continues to increase and peaks during the top
portion of the squat. Based on this description of the back squat, a method
of training that trains each portion of the lift based on its mechanical
advantage/disadvantage would be beneficial.
Variable-resistance training refers to a training method that alters
external resistance during the exercise in order to maximise muscle force
throughout the range of motion (Fleck and Kraemer, 2014). Traditionally,
this method of training involves the use of chains or elastic bands during
exercises such as the back squat (Figure 2.6) or bench press (Figure 2.7).
The addition of chains or elastic bands may alter the loading profile of an
exercise (Israetel et al., 2010; Figures 2.6 and 2.7), which may allow the
athlete to match changes in joint leverage (Zatsiorsky, 1995) and overcome
mechanical disadvantages at various joint angles (Ebben and Jensen, 2002;
Wallace et al., 2006). Swinton et al. (2011) indicated that the addition of
chains equal to 20 and 40% of an individual’s 1RM deadlift may increase
the length of the acceleration phase of the overall movement, allowing for
greater peak force and impulse to be achieved at the end of the concentric
motion. Further support for this method of training comes from a metaanalysis that indicated that greater strength gains were produced during the
bench press exercise following variable-resistance training compared to
traditional methods (Soria-Gila et al., 2015). While additional training
studies are needed, it appears that variable resistance training may be used
as an effective training tool for developing muscular strength and power.
Back squat exercise using variable resistance with chains.
Bench press exercise using variable resistance with elastic bands.
Kettlebell training
Another form of resistance training that has gained popularity is the use of
kettlebell exercises. Kettlebells consist of a weighted ball and handle
(Cotter, 2014). Among other movements, individuals have used kettlebells
in a variety of ways, including swings, goblet squats, accelerated swings,
and modified weightlifting exercises such as a snatch for the purposes of
developing strength and power. Previous research has indicated that
kettlebell training may improve various measures of muscular strength (Jay
et al., 2011, 2013; Lake and Lauder, 2012; Otto III et al., 2012; Manocchia
et al., 2013) and explosive performance as measured by vertical jumping
(Lake and Lauder, 2012; Otto III et al., 2012) and clean and jerk 3RM
(Manocchia et al., 2013). However, it should be noted that two other studies
indicated that vertical jump (Jay et al., 2013) and sprint performance
(Holmstrup et al., 2016) were not enhanced following kettlebell training
when compared to a control group, indicating that not all research supports
the use of kettlebells as a strength-training method.
Research findings suggest that kettlebell training may provide an
effective strength-power-training stimulus. However, it should be noted that
more traditional methods of training, such as weightlifting, may provide
superior adaptations when it comes to improving maximal strength and
explosiveness (Otto III et al., 2012). This may in part be due to overload
placed on the body. For example, athletes training with weightlifting
movements may be able to clean and jerk 100 kg; however, it may be
difficult to perform a kettlebell swing with the same load using proper
technique. Further research examining kettlebell training is needed to
determine its role within strength and conditioning programmes.
Ballistic vs. non-ballistic
The intent of performing an exercise may alter a given training stimulus.
Ballistic exercises (i.e., those that accelerate throughout the entire
concentric movement) may lower the recruitment threshold for motor units
(Desmedt and Godaux, 1977; van Cutsem et al., 1998) and allow the entire
motor neuron pool to be activated within a few milliseconds (Duchateau
and Hainaut, 2003). Based on the discussion earlier in this chapter,
recruiting a greater number of motor units will ultimately lead to greater
magnitudes and rates of force production. This notion is supported by
previous research findings that indicated that ballistic exercises produced
greater force, velocity, power, and muscle activation compared to the same
exercises performed quickly (Newton et al., 1996; Lake et al., 2012b;
Suchomel et al., 2018b). The results of additional research indicate that
ballistic movements using 90% of an individual’s 1RM concentric-only
half-squat may also produce superior potentiation effects compared to nonballistic exercises (Suchomel et al., 2016c). Due to the potential training
benefits of ballistic-type exercises, it should come as no surprise that
practitioners often implement these exercises throughout the training year.
However, it should be noted that the goals of each training phase will often
dictate which exercises are prescribed.
Loading considerations
Training to failure
Training with heavy loads will ultimately lead to increases in muscular
strength. A method of training that supports this idea is training with loads
that result in failure on the final repetition. The theory behind this method is
that training with RM loads (e.g., 3RM, 5RM, etc.) will lead to greater
overall adaptations in strength compared to training with submaximal loads.
While it seems plausible that training to failure may stimulate the
recruitment of high-threshold motor units, Sundstrup et al. (2012) indicated
that there was no difference in motor unit recruitment following training to
failure compared to heavy-load training. However, the findings of existing
literature appear to be mixed as the results of previous meta-analyses
indicated that training to failure does not elicit greater strength gains
compared to not training to failure (Peterson et al., 2005) or produces
similar effects (Davies et al., 2016). It should be noted that training to
failure may increase the time needed to recover neuromuscular function and
metabolic and hormonal homeostasis (Morán-Navarro et al., 2017). The
fatigue that results from training to failure may decrease force and the
nervous system’s ability to voluntarily activate muscles (Häkkinen, 1993),
which could also negatively impact rapid force production, movement
velocity, and power output (Häkkinen and Kauhanen, 1989). Furthermore,
additional research findings suggest that training to failure may improve
muscle endurance characteristics rather than power development compared
to not training to failure (Izquierdo et al., 2006).
Due to the use of consistently heavy loads, athletes may not be able to
sustain training to failure for long periods of time, or during periods of
intensive competition/fixture congestion. While there are training periods
when the primary emphasis may be lifting very heavy loads (90–95% 1RM)
to improve maximal strength qualities (Suchomel et al., 2018a), it does not
appear that training to failure is a required element in an athlete’s
resistance-training programme (Davies et al., 2016). For example, Carroll et
al. (2019) indicated that not training to failure may produce greater
improvements in vertical jump, RFD, and maximal strength compared to
training to failure. The authors also noted that the build-up of residual
neuromuscular fatigue from training to failure may prevent continual
improvements in strength-power characteristics from occurring. Therefore,
it is important to include variation in the training stimulus to avoid a plateau
(Thompson et al., 2010). Due to the accumulation of fatigue and potential
decrements in strength-power characteristics, it is important to note that if
training to failure is incorporated into training programmes, it should be
used sparingly in order to limit the risks of injuries and overtraining (Davies
et al., 2016).
Combining heavy and light loads
Training for maximal strength and power requires the use of a variety of
loads. Specific to strength gains, heavier loads will likely provide a training
stimulus that will enhance the magnitude and rate of force production of an
athlete. In contrast, training to enhance maximal power production requires
the use of a range of loads that train the entire force–velocity curve (Haff
and Nimphius, 2012). The training loads implemented with various
exercises should complement the exercises that are being used. For
example, heavier loads may be used with core exercises (e.g., squats,
presses, and pulls) and certain weightlifting movements (e.g., power clean,
pull from the floor, mid-thigh pull) that emphasise high-force production,
while lighter loads may be prescribed for more ballistic movements that
emphasise high velocities (e.g., jump squat, jump shrug, bench press
throws). However, as mentioned above, combination loading may also be
achieved through the implementation of both weight training (high force)
and plyometrics (high velocity). Suchomel et al. (2017) discussed this
concept using weightlifting derivatives (also discussed in more detail in
Chapter 16).
It should be noted that a combination loading stimulus may also be
achieved across each microcycle (e.g., week of training) and session of
training. Over the course of an individual microcycle, the same exercises
may be implemented throughout the week; however, the exercises are
prescribed using a ‘heavy day/light day’ loading concept. One review
discussed this method of programming for track and field athletes
(DeWeese et al., 2015b). In addition, Harris et al. (2000) displayed that a
combination loading group performed back squats at 80% 1RM on their
heavy day and back squats at 60% 1RM on their light day. Similarly,
achieving a combined loading stimulus within a single training session is
realised through the combination of working sets as well as warm-up and
warm-down sets of each exercise.
Optimal loads
Some literature supports the idea of training at or near the load that
maximises power production, termed the ‘optimal load’ (Kawamori & Haff,
2004). In theory, optimal loads provide an ideal combination of force and
velocity magnitudes that produce high-power outputs. However, it should
be noted that a number of factors may affect optimal loads. For example,
research findings indicated that the optimal load or range of loads for the
greatest power output is exercise-specific for both upper- (Soriano et al.,
2017) and lower-body exercises (Soriano et al., 2015). Additional research
findings suggest that the load that maximises power may be specific to the
method that is used to assess power output (e.g., force platform, linear
position transducer, etc.) (Cormie et al., 2007; Hori et al., 2007; McBride et
al., 2011; Lake et al., 2012a), further indicating that it may be necessary to
train with a range of loads, especially as an athlete gets stronger (Stone et
al., 2003). Collectively, it appears that training near or at optimal loads may
be beneficial from a power development standpoint. However, the extant
literature supports the notion that practitioners should prescribe a range of
loads instead of a single load in order to train both low- and high-force
power characteristics during different exercises (Haff and Nimphius, 2012).
Training status
An athlete’s training status may dictate: (1) what exercises and loads the
individual can tolerate; and (2) what their training emphasis should be. As
with any type of training, practitioners should be mindful of an athlete’s
abilities as exercise competency will dictate whether it is appropriate to
implement certain exercises or progress using various training methods.
Because muscular strength serves as a foundation for a number of other
abilities (Suchomel et al., 2016b), the training emphasis for weaker and/or
less well-trained athletes should focus on increasing maximal strength. Too
often practitioners place an emphasis on high-velocity or power training
without developing the necessary strength characteristics that will allow the
athletes to exploit power-type training more extensively. That is not to say
that power-type exercises such as weightlifting movements and plyometrics
should not be prescribed to a weaker athlete, but they may not be featured
as exclusively until an athlete increases their baseline strength levels using
core movements such as squats, presses, and pulls, and improves their
technique during power exercises.
While the emphasis of training for weaker and/or less well-trained
individuals may be on gaining maximal strength, the emphasis of training
for stronger/well-trained athletes may be modified. Previous literature
indicated that although strength influences an athlete’s performance, the
degree of this influence may diminish when athletes maintain high levels of
strength (Kraemer and Newton, 2000). Therefore, the window of adaptation
for greater strength gains is reduced while an athlete increases their
maximal strength. As a result, additional literature has indicated that after
achieving specific standards of strength (e.g., parallel back squat ≥ 2 × body
weight as the barbell load), an athlete’s training emphasis may shift towards
power-type or RFD training while maintaining or increasing their strength
levels (Stone et al., 2007; DeWeese et al., 2015b). Specifically, achieving a
high baseline level of strength may allow an athlete to maximise the
benefits of incorporating training methods such as plyometrics, ballistic
exercises, and CT.
Summary
Muscular strength is defined as the ability to exert force on an external
object and is considered to be the primary underpinning factor for greater
RFD and power. It is important that adequate strength development is the
primary, although not exclusive, focus of training initially, before
progressing to power-type training once an athlete’s strength increases. By
achieving a high level of muscular strength, athletes may increase their
RFD, power, and athletic performance, while decreasing the risk of injury
(Suchomel et al., 2016b). Both morphological and neuromuscular factors
may affect the development of muscular strength and power. Morphological
factors include muscle CSA and architecture while neuromuscular factors
include motor unit recruitment, rate coding, motor unit synchronisation, and
neuromuscular inhibition.
From a practical standpoint, the periodisation model, method of
resistance training, prescribed loads, and training status may directly affect
muscular strength and power adaptations and training emphases. The
training programmes of weaker individuals should focus on improving
muscular strength before too much emphasis is placed on power. In
contrast, stronger athletes may shift to a power emphasis while maintaining
or improving their strength level.
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3
Stretch-shortening cycle and
muscle–tendon stiffness
John J. McMahon
DOI: 10.4324/9781003044734-5
What is the stretch-shortening cycle?
Early research findings revealed that when isolated skeletal muscle fibres
were tetanically stimulated (i.e. maximally activated by a nerve stimulator),
stretched and then immediately allowed to shorten, they performed a far
greater amount of positive mechanical work than when compared to being
shortened alone (Cavagna et al., 1965, 1968). This sequential combination
of eccentric (lengthening) and concentric (shortening) muscle actions was
later termed the stretch-shortening cycle (SSC) (Cavanagh and Komi,
1979). The apparent ‘performance-enhancing’ effect of the SSC was also
demonstrated during a range of SSC actions involving the entire lower
limb(s), such as those involved during running, jumping and hopping
(Asmussen and Bonde-Petersen, 1974; Luhtanen and Komi, 1978;
Fukashiro and Komi, 1987). Whilst it is important to note the SSC is
common to upper-limb movements too, such as when throwing (Newton et
al., 1997), the majority of researchers have explored the SSC of the lower
limb(s) and so this will comprise the focus of this chapter.
Due to its aforementioned prevalence in key athletic actions such as
running, jumping and hopping, the SSC forms the most common type of
lower-limb muscle function (Van Ingen Schenau et al., 1997a). In recent
years, there has been much debate over the proposed mechanisms that cause
the potentiating effect (e.g. increased positive work) of the SSC; however,
stimulation of muscle stretch reflexes (e.g. muscle spindles) and storage and
re-utilisation of elastic energy within the involved muscle–tendon units
(MTUs) are the two primary mechanisms that have been agreed upon by
researchers (Van Ingen Schenau et al., 1997a, 1997b; Cormie et al., 2011;
Turner and Jeffreys, 2011). During the SSC, stretch reflexes act to increase
muscle stiffness (Taube et al., 2012) while tendon stiffness influences the
storage and re-utilisation of elastic energy (Farris et al., 2011), thus it can be
deduced that MTS has a profound influence on lower-limb SSC function.
What is stiffness?
Simply stated, stiffness describes the relationship between force and
lengthening, or stress and strain, of an object or body (Butler et al., 2003;
Brughelli and Cronin, 2008a; McMahon et al., 2012). When applied to the
MTU, the object or body of reference could be the muscle, the tendon or
both. The term ‘stiffness’ is based on Hooke’s law, which has been
described in detail elsewhere (Butler et al., 2003; Brughelli and Cronin,
2008a). Hooke’s law describes the stiffness of an ideal spring–mass system
(Butler et al., 2003). When an object that obeys Hooke’s law deforms (i.e.
stretches, such as tendon), its change in length will be directly proportional
to the force acting upon it (Alexander, 1997) (Figure 3.1). During this
deformation (e.g. during the eccentric phase of an SSC action), the object
will store elastic energy, which will be re-utilised as the object shortens
(e.g. during the concentric phase of an SSC action) and returns to its
original resting length (Butler et al., 2003). It is worth pointing out at this
stage that activated muscle does not always adhere to Hooke’s law and the
reasons for this will be discussed in later sections of this chapter.
Nevertheless, during the performance of lower-limb SSC actions, stiffness
can be described at a broad range of levels, from an individual MTU, to
modelling the entire body as a simple spring–mass system (Butler et al.,
2003; Brughelli and Cronin, 2008a).
An example of an object that obeys Hooke’s law and the equation to
calculate stiffness (k), where ∆F = change in force and ∆x = change in
length.
Muscle–tendon stiffness (MTS)
When considering stiffness in the context of the various MTUs that
surround the primary lower-limb joints (e.g. ankles, knees and hips), it is
known that there are both passive components (tendon, connective tissue,
etc., commonly referred to as the series and parallel elastic components)
and active components (muscle, commonly referred to as the contractile
component). Due to this, the MTU is considered to be a variably stiff
system because whilst tendon possesses a fairly linear relationship (due to it
demonstrating mainly elastic behaviour) between force and deformation
(Lichtwark and Wilson, 2005; Farris et al., 2011), muscle can vary its
stiffness through both feedforward (e.g. pre-programmed) and feedback
(e.g. reflex) activation mechanisms (Taube et al., 2012). It must also be
noted that the tendon is known to possess viscous as well as elastic
properties (Pearson and McMahon, 2012) and so the amount of tendon
stretch (and thus storage of elastic energy) experienced during SSC actions
will be somewhat affected by tendon-loading rate (McMahon et al., 2014).
Muscle activation is, therefore, the primary modulator of MTS during SSC
actions, as this will influence both muscle stiffness (i.e. the resultant muscle
length changes) and tendon stiffness (i.e. by affecting load rate) alike.
Therefore, it is important to note that when discussing whole lower-limb
SSC actions it may be seen that the involved muscle components of the
MTUs do not always lengthen and shorten during the ‘eccentric’ and
‘concentric’ phases, respectively, of the movement, thus ‘braking’ and
‘propulsion’ phases may be more appropriate terms.
As mentioned earlier, both pre-programmed and reflex muscle activation
strategies largely dictate the muscle stiffness attained during SSC tasks
(Taube et al., 2012). The pre-programmed aspect of muscle activation
relates to both muscle pre-activation, which acts to provide sufficient
stiffness to the MTU at initial ground contact (Taube et al., 2012), and
variable activation during ground contact, which helps to maintain stiffness
(i.e. prevent muscle lengthening) during the braking phase and then
facilitate the controlled release of high forces (produced in the braking
phase) in the subsequent propulsion phase (Komi, 2003). The reflex aspect
of muscle activation relates primarily to the stimulation of a stretch reflex
called short-latency response (SLR), although when muscle is pre-activated
prior to stretching (as is the case during SSC tasks) there are mediumlatency responses (MLR) and long-latency responses (LLR) involved too
(Taube et al., 2012). These reflex responses simply relate to their timecourse of stimulation with time epochs of 30–60, 60–90 and 90–120 ms
typically relating to the SLR, MLR and LLR, respectively. It has been
suggested, however, that stretch reflex contributions to muscle stiffness are
more apparent when the muscle is not fully activated, e.g. during
submaximal SSC tasks: Cronin et al., 2011), in order to help prevent sudden
muscle yielding during the braking phase (Taube et al., 2012).
Calculating individual MTS contributions to the total stiffness attained
by a given MTU during SSC tasks is a relatively complex process which
requires the simultaneous collection of ultrasound, electromyography, force
platform and motion analysis data, followed by a lengthy data analysis
process which makes this discrete level of analysis difficult to perform in a
competitive sport setting. Thus, in the applied strength and conditioning
research and practice setting, it is more common to see ‘global’ measures of
lower-limb MTS assessed, such as joint stiffness (Kjoint) and leg stiffness
(Kleg), as these measures are easier to attain, require less processing time
and can still provide valuable insight into how MTS influences SSC
function during a variety of athletic tasks (e.g. running, jumping, hopping).
Joint stiffness
Lower-limb Kjoint is typically calculated using the torsional-spring model
(Figure 3.2), as the ratio of the peak sagittal plane joint moment (i.e. the
joint rotatory force) to peak sagittal plane joint angular displacement
(Figure 3.3), between the instants of ground contact and maximum joint
flexion (Farley et al., 1998). An alternative method of quantifying Kjoint has
also been described in the literature, as the ratio of negative mechanical
work to change in joint angle between the instants of ground contact and
maximum joint flexion (Arampatzis et al., 1999); however, this method was
later critiqued (Gunther and Blickhan, 2002) and, to the author’s
knowledge, has not been reported in any other studies. Despite the method
used, however, Kjoint calculations require access to both a force platform
and either two- or three-dimensional motion capture, so this equipment may
be more accessible to strength and conditioning researchers and
practitioners than the addition of ultrasound and electromyography
equipment needed to calculate MTS. The torsional-spring model assumes
that the lower limbs can be represented by multiple spring-like joints (i.e.
the ankles, knees and hips) during SSC actions, which flex and extend
during the ground contact period, thus storing and releasing energy (Figure
3.2).
An example of the torsional spring model and how it corresponds to the
human body.
An example of the joint moment–joint angular displacement relationship
during loaded flexion and extension.
It has been suggested that Kjoint only provides a measure of ‘quasistiffness’, as one stiffness value is used to describe all contributing
components to Kjoint, such as muscles, tendons, ligaments, cartilage and
bone (Latash and Zatsiorsky, 1993). Nevertheless, Kjoint during SSC tasks is
mainly influenced by the magnitude of agonist muscle activation, in
addition to the magnitude of antagonist muscle coactivation, immediately
prior to and during ground contact (Farley et al., 1998; Arampatzis et al.,
2001a, 2001b). Therefore, Kjoint is mainly controlled by muscle stiffness
through the muscle activation mechanisms mentioned in the previous
section. Another point to consider is that Kjoint attained during SSC tasks is
also influenced by limb geometry at touchdown (Devita and Skelly, 1992;
Farley et al., 1998; Moritz and Farley, 2004). This can be reasoned by the
understanding of the joint moment–angle relationship, in that as the lower
limb becomes more extended at touchdown, the moment about the joint
decreases for any given external ground reaction force (Figure 3.4),
resulting in decreased joint flexion for any given level of extensor muscle
activation (Moritz and Farley, 2004). Therefore, athletes can be cued to
contact the ground with their limbs orientated in such a manner to either
increase or decrease Kjoint depending on the desired outcome.
An example of how joint touchdown angles influence leg and joint stiffness
values.
Leg stiffness
It has been shown in several studies that Kjoint is the primary determinant of
Kleg during SSC actions (Farley et al., 1998; Arampatzis et al., 1999;
Kuitunen et al., 2002) and so although the predominant joint that regulates
Kleg depends on the type of SSC task being performed, this most ‘global’
measure of lower-limb stiffness provides valuable information pertaining to
SSC function and is the easiest of the lower-limb stiffness hierarchy to
measure in both laboratory and field settings.
The Kleg measurement is based on the human body acting as a simple
spring–mass system during SSC tasks (Geyer et al., 2006; Brughelli and
Cronin, 2008b). The spring–mass model (Figure 3.5) is comprised of a
point mass (equal to body mass), which is supported by a single massless
Hookean spring (representing the leg or legs depending upon whether a
unilateral or bilateral task is being performed) (Blickhan, 1989; McMahon
and Cheng, 1990). When the spring is not compressed (i.e. during the flight
phase of SSC tasks), it does not store any energy and thus no force is
developed; however, energy is stored when the spring is compressed (i.e.
during the braking phase of SSC tasks) and force is produced and the
majority of this energy is re-utilised when the spring subsequently recoils
(i.e. during the propulsion phase of SSC tasks) (Brughelli and Cronin,
2008a).
An example of the spring–mass model and how it corresponds to the human
body.
From the spring–mass model, Kleg can be calculated as the ratio of the
peak ground reaction force (GRF) to peak leg compression during the
period of ground contact (McMahon and Cheng, 1990). This direct measure
of Kleg requires access to a force platform system, which is becoming
increasingly affordable and utilised in applied practice (Lake et al., 2018).
Other methods can also be used to calculate Kleg, based on body mass and
either the natural period of oscillation (McMahon et al., 1987; Cavagna et
al., 1988) or temporal characteristics such as ground contact and flight
times (Dalleau et al., 2004; Morin et al., 2005). Although the latter methods
(i.e. based on body mass and temporal factors) have been less frequently
reported in the scientific literature (Brughelli and Cronin, 2008b; Serpell et
al., 2012), they are commonly used in applied practice as these
measurements of Kleg are easily attainable from simple jump mats,
optoelectronic systems (e.g. Optojump) and even smartphone applications
(Balsalobre-Fernández et al., 2016). The limitation of using field-based
calculations of Kleg is that they do not directly include force and
deformation in their calculations and so they provide somewhat of a proxy
of ‘true’ Kleg. Indeed, the suggested criterion method of calculating Kleg
involves considering movement in multiple planes via three-dimensional
motion analyses (Liew et al., 2017), but this is beyond most practitioners’
scope and equipment access. At the very least, practitioners should give
consideration to the method that they use to calculate Kleg (Maloney and
Fletcher, 2021).
Stiffness and performance
The implications of MTS being primarily regulated by pre-programmed and
reflex muscle activation, and somewhat influenced by tendon stiffness and
joint geometry, is that it is acutely sensitive to changes in SSC task type and
intensity which, in turn, influence SSC function (Ishikawa and Komi, 2004;
Ishikawa et al., 2005; McMahon et al., 2014). For example, when drop
jumps (DJs) were performed from increasing drop heights (10 cm lower
than ‘optimal’ drop height, with optimal drop height determined by best
jump height achieved, and 10 cm higher than ‘optimal’ drop height), vastus
lateralis (VL) muscle activation increased, decreased and remained
unchanged during the pre-contact, braking and propulsive phases,
respectively, but tendon recoil decreased (Ishikawa et al., 2005). Tendon
recoil also reduced by virtue of increased drop height for the medial
gastrocnemius (MG) and its activation patterns were similar to those
reported for the VL in the pre-contact and braking phases; however, the MG
showed increased activation during the propulsive phase (Ishikawa et al.,
2005). Interestingly, the SLR amplitude decreased for the MG but increased
for the VL during DJs performed from the highest drop (Ishikawa et al.,
2005). This is perhaps explained by the MG showing a reduction in
lengthening during the braking phase, whereas the VL demonstrated a
general increase in lengthening during this phase (Ishikawa et al., 2005),
since the muscle spindle stretch reflex detects the rate and magnitude of
muscle lengthening (Taube et al., 2012). These results illustrate that
variations in MTS and thus SSC function for a given task and intensity are
muscle specific (as noted by the differential response of the VL and MG
MTUs) and that high stiffness (as shown for the highest drop condition)
does not always transfer to improved performance (e.g. improved jump
height).
The differential stiffness strategies of the individual VL and MG
muscle–tendon components during various DJ tasks mentioned above
(Ishikawa et al., 2005) are echoed in the results of a range of studies where
the researchers explored the associations between muscle activation
strategies and both Kleg and Kjoint for a range of DJ tasks. For example,
there were significant correlations between Kleg and the magnitude of preactivation of the MG, lateral gastrocnemius (LG), VL and hamstrings
during the performance of DJs, by decathletes, from a height of 20 cm
(Arampatzis et al., 2001b). Interestingly, when DJs were performed from
heights of 40 and 60 cm, relationships between Kleg and the magnitude of
pre-activation were demonstrated for VL and the hamstrings only for this
group of athletes (Arampatzis et al., 2001b). For female athletes, significant
correlations between Kleg and the magnitude of pre-activation of the MG,
LG and VL were found for bilateral DJs performed from a 20-cm height,
whereas the magnitude of pre-activation of MG and VL, only, were
correlated to Kleg attained during DJs from 40 cm (Arampatzis et al.,
2001a). Nine healthy males also demonstrated a relationship between preactivation of the VL muscle and Kknee during DJs performed from 50 cm
(Horita et al., 2002).
Recent research by Helm and colleagues, which focused on
unanticipated versus anticipated DJs (e.g. drop height was known, unknown
or falsely stated [drop height was different to what the subjects were told]),
explained that anticipation is key for precise timing of neuromuscular
responses during ground contact and jump outcomes, such as jump height
(Helm et al., 2019, 2020). The outcomes of these studies may reflect the
training status of the subjects (i.e. they were not high-level athletes), but
also they may rationalise the inclusion of various jumping exercises to
enhance an athlete’s overall MTS abilities and SSC function, perhaps even
those that include unanticipated drop heights. However, further research is
needed to explore the efficacy of this suggestion.
The earlier described results pertaining to the varying muscle activation
responses to DJs performed from different drop heights echo the different
Kjoint contributions to total Kleg that have been highlighted for a range of
other athletic performances. For example, ankle stiffnes (Kankle) has been
shown to be the primary determinant of Kleg during hopping in place at high
(≥2.0 Hz) hopping frequencies whereby the ability to hop at high
frequencies requires high levels of Kleg due to the associated short contact
times (Farley et al., 1998; Hobara et al., 2011). Contrastingly, Kknee was the
primary modulator of Kleg at low (≤1.5 Hz) hopping frequencies which
requires lower levels of Kleg and where greater hop heights are noted by
virtue of greater time spent on the ground (Hobara et al., 2009, 2011).
Similarly, Kknee was also the primary determinant of Kleg during both low(6.5 m s−1) velocity running (Arampatzis et al., 1999) and maximal sprint
running (Kuitunen et al., 2002). These differential Kjoint contributions to
total Kleg across different SSC tasks reflect differential muscle–tendon
contributions to these tasks, with the contribution of tendon (in terms of
comprising greater total lengthening and shortening within the MTU) being
higher and muscle length being almost constant (i.e. isometric) when Kleg
increases (McMahon et al., 2013b).
Based on the results of the research presented above, it is apparent that
there is an appropriate amount of Kleg for success in a particular SSC task.
This notion is supported by a range of scientific studies related to jumping.
For example, when DJs were performed from heights of 20–60 cm, jump
height was maximised when participants adopted a range of Kleg strategies
(Arampatzis et al., 2001a, 2001b; Laffaye and Choukou, 2010). However,
the general trend in these studies was that too much Kleg had a negative
impact upon vertical jump height (Arampatzis et al., 2001a, 2001b; Laffaye
and Choukou, 2010) and this was especially seen in a study whereby DJs
were performed from very high (80 and 100 cm) drop heights (Walshe and
Wilson, 1997). The potentially inhibiting effect of excessive Kleg was also
demonstrated during a high jumping manoeuvre, as greatest jump heights
were achieved when participants adopted a more compliant (i.e. less stiff)
leg strategy (Laffaye et al., 2005). The aforementioned results suggest that
the degree of Kleg required to successfully complete a jumping-based task
depends upon both the aims (e.g. maximal height attainment vs. fast
execution [i.e. short contact time]) and type (e.g. hopping vs. DJ) of the
specific task being performed. Several studies have also reported that Kleg
was associated with increased submaximal running velocity (Farley and
Gonzalez, 1996; Stefanyshyn and Nigg, 1998; Arampatzis et al., 1999;
Hobara et al., 2010) and increased running economy (McMahon and Cheng,
1990; Heise and Martin, 1998; Dutto and Smith, 2002; Rabita et al., 2011)
but not with maximal sprint acceleration (Chelly and Denis, 2001; Lockie et
al., 2011; Pruyn et al., 2014).
The reason for Kleg being beneficial to DJ from lower heights, as
compared to DJ from greater heights and the high jump, can be explained
by increased Kleg being linked to shorter ground contact times and increased
vertical GRFs (Arampatzis et al., 2001a, 2001b). When increasing jump
height is the desired outcome, then vertical net impulse (area underneath the
net force–time curve) must be increased (Kirby et al., 2011). Although net
impulse can be maintained or increased by increasing vertical GRFs when
ground contact times decrease (as seen when employing a stiff jumping
strategy), it seems that the latter prevails when high Kleg is demonstrated in
DJs performed from greater heights and during the high jump. Similarly,
researchers have shown that the achievement of faster top running speeds
was more closely related to the production of a greater resultant GRF than
to an increase in stride frequency (Weyand et al., 2000). Therefore, if
running was to be performed with high Kleg, ground contact times would
decrease (Farley et al., 1991; Arampatzis et al., 2001a, 2001b), which
would reduce the time available for force production (Weyand et al., 2010).
A reduction in resultant GRF during running would likely reduce stride
length (McMahon and Cheng, 1990; Kerdok et al., 2002). This is, as for
jumping, due to a reduction in net impulse. For example, unless a reduction
in ground contact time is accompanied by at least the maintenance of, or an
increase in, GRF, there will be a reduction in net impulse. Therefore, top
running speeds may plateau with an increase in Kleg, in spite of a potential
increase in stride frequency (McMahon et al., 1987; Farley and Gonzalez,
1996; Hobara et al., 2010). Researchers did indeed find that the fastest man
on earth (i.e. Usain Bolt) ran with significantly lower Kleg, lower stride
frequency and longer ground contact times during competition when
compared with his two closest rivals (Taylor and Beneke, 2012).
In terms of running economy, it is known that the storage and release of
elastic energy will help to reduce the work produced by the muscle itself
(Roberts and Marsh, 2003; Lichtwark and Barclay, 2010; Perl et al., 2012)
and although previous studies revealed that a high Kleg strategy was
associated with improved running economy (McMahon and Cheng, 1990;
Heise and Martin, 1998; Dutto and Smith, 2002; Rabita et al., 2011), a
stiffer MTU may not always elicit a more economical outcome. For
example, previous researchers have examined the relationship between MG
muscle fascicle length and Achilles tendon stiffness and maximum
efficiency during a range of running and walking tasks (Lichtwark and
Wilson, 2007, 2008; Lichtwark et al., 2007) and despite maximum
efficiency for both running and walking occurring at similar values of
tendon stiffness, it was suggested that moving towards a stiffer tendon
would reduce efficiency in the walking task but may be more ideal for
running, when coupled with longer muscle fibres to optimise efficiency.
However, a modelling study indicated that muscle fibre lengths could vary
by approximately one and a half times (45–70 mm) and tendon stiffness by
approximately threefold (150–500 N mm−1) to give optimal efficiency in a
given walking or running task (Lichtwark and Wilson, 2008), which further
highlights both the individual and task-specific nature of ‘optimal’ MTS,
which has been echoed in more recent work (Moore et al., 2019).
In conclusion, the amount of MTS required during an SSC task depends
on desired task outcome (Figure 3.6). If reducing ground contact time and
increasing GRF is sought then stiffer is better but if increasing joint angular
velocity to increase short sprint acceleration or jump height is sought then
too much stiffness will be detrimental. Acutely modulating an athlete’s
MTS strategy in the direction of stiffening their legs via verbal coaching
cues etc. will increase GRFs and load rates and so this should only be done
if they are appropriately conditioned and (in line with the previous point) if
the task warrants a stiffer strategy (Figure 3.6). A safer and more sensible
approach to increasing MTS is through long-term training rather than via
acute modulation (i.e. immediately coaching a change in movement
strategy), which will be discussed in the next section.
A schematic illustrating how the legs change from being more compliant
(opposite of stiff) to more stiff for a range of stretch-shortening cycle tasks.
DJ, drop jump.
Stiffness and training
Only a few studies to date have examined the effects of training
interventions on Kleg and Kjoint, as determined during lower-limb SSC
actions (Table 3.1). Most of the training interventions included in these
studies were very distinct, which makes it somewhat difficult to make any
definitive conclusions about the most effective training methods for
increasing Kleg and Kjoint, but there are some general trends noted across
studies which warrant discussion.
Table 3.1
Summary of studies that have determined the effects of training interventions on global
lower-limb stiffness measures
Study
Subjects
Training programme
overview
Training
duration
Result
Toumi et
al.
(2004)
8 male
handball
players
6 × 10 reps of leg press at 70%
1RM
6 weeks (4
No change in
sessions/week)
Kleg (CMJ)
Cormie et
al.
(2010)
8 strengthtrained
males
7 × 6 reps of jump squat at 0%
1RM (2 sessions) + 3 × 5 reps
of jump squat at 30% 1RM (1
session)
10 weeks (3
Increase in Kleg
sessions/week)
(CMJ)
Cormie et
al.
(2010)
8 strengthtrained
males
3 × 3–6 reps of back squat at
75–90% 1RM
10 weeks (3
Increase in Kleg
sessions/week)
(CMJ)
Hunter and 14 males
Marshall
(mixed
(2002)
sports)
1–4 × 3–8 reps of CMJs, 1–2 ×
6–10 reps of DJs (30–90 cm)
& 2–3 × 6–10 reps of
deadlift/squat at 60–100%
1RM
10 weeks (2
Increase in Kleg
sessions/week)
(CMJ)
Decrease in
Kleg (DJ 30,
60 and 90
cm)
Millet et
al.
(2002)
7 male
triathletes
3–5 × 3–5 reps of hamstring
curl, leg press, seated press,
parallel squat, leg extension,
and heel raise at >90% 1RM
14 weeks (2
No change in
sessions/week)
Kleg
(hopping)
Increase in Kleg
(running)
Arabatzi
and
Kellis
(2012)
9 physically
active
males
4–6 × 4–6 reps of power clean,
snatch, clean and jerk, high
pull, half-squat at >85% 1RM
8 weeks (3
Increase in Kleg
sessions/week)
(DJ 20 and
60 cm)
Arabatzi
and
Kellis
(2012)
9 physically
active
males
4–6 × 4–6 reps of leg press, leg
curl, leg extension, bench
press, half-squat of at >85%
1RM
8 weeks (3
Increase in Kleg
sessions/week)
(DJ 20
cm)Decrease
in Kleg (DJ
60 cm)
Toumi et
al.
(2004)
8 male
handball
players
6 × 10 reps of leg press at 70%
1RM and 3 × 5 reps of crossover jump
6 weeks (4
Increase in Kleg
sessions/week)
(CMJ)
1RM, one repetition maximum; CMJ, countermovement jump; DJ, drop jump; Kleg, leg stiffness;
Kankle, ankle stiffness.
Study
Subjects
Training programme
overview
Kubo et al.
(2007)
24
5 × 10 reps of unilateral hopping 12 weeks (4
Increase in
and DJs (20 cm) at 40% 1RM
sessions/week)
Kankle (DJ
20 cm)
Kubo et al.
(2007)
24
physically
active
males
5 × 10 reps of unilateral calf
physically
raise at 80% 1RM
active
males
Training
duration
Result
12 weeks (4
No change in
sessions/week)
Kankle (DJ
20 cm)
1RM, one repetition maximum; CMJ, countermovement jump; DJ, drop jump; Kleg, leg stiffness;
Kankle, ankle stiffness.
Generally, traditional resistance exercises performed individually with
≤80% one repetition maximum (1RM) tended not to increase Kleg and Kjoint
(Toumi et al., 2004; Kubo et al., 2007), unless performed concurrently with
plyometric exercises (Toumi et al., 2004). Individual traditional compound
resistance exercises can increase Kleg, however, if performed with a relative
load of up to 90% 1RM (Cormie et al., 2010). Multiple traditional
resistance exercises performed with ≥85% 1RM have been shown to
increase task-specific Kleg (Millet et al., 2002; Arabatzi and Kellis, 2012).
For example, the results presented by Millet et al. (2002) showed increased
Kleg measured during running but not during hopping at 2.0 Hz. These taskspecific differences in Kleg seen post-intervention are most likely due to the
training programme being knee-dominant (Table 3.1) in light of Kknee being
the primary modulator of Kleg during running (Arampatzis et al., 1999;
Kuitunen et al., 2002) and Kankle being the primary determinant of Kleg
when hopping at 2.0 Hz (Farley et al., 1998; Hobara et al., 2011).
Contrastingly, the training programme included in the study by Arabatzi
and Kellis (2012) was also knee-focused (weightlifting or traditional
compound resistance training), although Kleg increased during DJs
performed from 20 but not 60 cm, despite the latter drop height being more
synonymous with Kknee regulation (Arampatzis et al., 2001b); this is
possibly due to the relatively short training duration of 8 weeks. Similarly,
moderate–heavy (60–100% 1RM) traditional compound resistance exercise
performed concomitantly with plyometric exercises increased Kleg during
countermovement jump performance, but reduced Kleg during DJs
performed from ≥30 cm drop heights (Hunter and Marshall, 2002).
However, the participants tested by Hunter and Marshall (2002) had never
performed any structured plyometric training prior to the commencement of
the study nor were they given any verbal instructions either before or during
the jump performances, which may have influenced these findings.
In contrast to the contradictory Kleg and Kjoint adaptations brought about
via traditional compound resistance-training interventions mentioned above,
all training programmes that included plyometric, ballistic or weightlifting
exercises increased Kleg and Kjoint (Kubo et al., 2007; Cormie et al., 2010;
Arabatzi and Kellis, 2012). The differential adaptations to Kleg and Kjoint
following different exercise modalities and intensities have been attributed
to the different mechanisms that modulate MTS attainment. For example,
heavy resistance training (≥80% 1RM) leads to greater strength (i.e. muscle
force) capacity and although muscle strength is not a direct measure of
muscle stiffness it can be thought of as a proxy for stiffness (Pearson and
McMahon, 2012). Additionally, tendon stiffness is related to the forceproducing capacity of the muscle (Muraoka et al., 2005; Arampatzis et al.,
2007) and, as has been shown in several studies, tendon stiffness increases
in response to traditional resistance training, in addition to isometric and
eccentric-focused training (refer to the systematic review and meta-analysis
on this topic by Bohm et al., 2015). Alternatively, enhanced muscle
recruitment strategies (commonly associated with plyometric training and
weightlifting: Chimera et al., 2004; Arabatzi and Kellis, 2012) may explain
increased post-training Kleg and Kjoint (Taube et al., 2012), as muscle
strength and tendon stiffness generally do not increase following plyometric
training (Kubo et al., 2007; Bohm et al., 2015) unless performed with a very
high volume (Fouré et al., 2010, 2011).
The mixed results of training studies presented in Table 3.1, particularly
when interpreted alongside the underpinning mechanisms for MTS
adaptation, highlight the efficacy of including both traditional resistance
(i.e. strength) and power-focused exercises in a training programme
designed to increase MTS. Traditional compound resistance exercises,
particularly when utilised by relatively weak athletes, should be performed
for at least 8–12 weeks as this is the minimum time likely needed to induce
increases in tendon stiffness, despite muscle strength gains occurring from
as soon as 4 weeks (Kubo et al., 2010, 2012). If an athlete is relatively
strong then it may be prudent to include low-load SSC tasks alongside
traditional resistance exercises (particularly as they progress through the
training weeks) to facilitate the previously mentioned enhanced muscle
activation strategies that can be gained through this (Chimera et al., 2004).
Because increases in muscle strength generally outweigh increases in
tendon stiffness, due to the differential time-course of adaptation of these
structures to resistance training (Kubo et al., 2010, 2012), moderate–highload SSC tasks performed too early may lead to excessive strain of the
lower-limb tendons (McMahon et al., 2013a), thus these should be avoided
until at least after the 12-week resistance-training period, unless the athlete
is deemed to be ‘strong’ (see Chapter 2) and is used to performing such
SSC tasks. A recent study suggested that the magnitude of Kleg adaptations
to training (plyometric training, in this case) is sports-specific, with
taekwondo athletes demonstrating a 31% post-training increase in Kleg, but
rhythmic gymnasts showing no significant change (Dallas et al., 2020).
Thus, practitioners should perhaps consider the athlete’s sport and training
experience when programming (exercise selection, intensity, volume and
duration) for improvements in Kleg and SSC function.
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4
Understanding and developing
aerobic fitness
Richard C. Blagrove
DOI: 10.4324/9781003044734-6
Introduction
An athlete’s physical performance is fundamentally limited by their ability
to display explosive power and repeat these expressions of power over a
given distance or duration. To sustain a required power output and avoid
fatigue, adequate muscle energy levels must be maintained to satisfy the
requirement for force generation. Aside from short (<30-s) single bursts of
maximal effort, a large proportion of the energy generated for skeletal
muscle contraction is derived using aerobic metabolic processes. The
necessity to possess high levels of aerobic fitness is perhaps obvious in
endurance sports, such as distance running, road cycling, and rowing, where
continuous efforts can last from several minutes to many hours. In
intermittent sports, the ability to display high levels of maximal power and
engage in frequent changes in speed is at least as important as the aerobic
performance of athletes. In the chaotic and unpredictable environment of an
intermittent sport, it is the rapid recovery of anaerobic substrates and
transient kinetics of oxygen consumption that more accurately describe the
relevance of aerobic fitness. Furthermore, while many intermittent sports
may appear similar in terms of the duration of play and the distribution of
effort, there are important differences, such as the size of the playing area,
unique positional demands, and the rules that govern play. These factors
influence the degree to which aerobic fitness is important relative to other
physical qualities and therefore the time that a strength and conditioning
(S&C) coach devotes to development of aerobic fitness. The aim of this
chapter is to explore the components of aerobic fitness and the main factors
that limit each component, to enable S&C coaches to design appropriate
training practices to enhance these capabilities in their athletes. Moreover,
for the S&C coach working with endurance athletes, an appreciation of the
physiological determinants limiting performance and the typical training
practices athletes engage with is also vital.
SECTION 1
Bioenergetics of exercise
To produce energy within the muscle cell, adenosine triphosphate (ATP) is
broken down by ATPase enzymes to adenosine diphosphate (ADP) and
inorganic phosphate (Pi). At the onset of a forceful muscular contraction,
the ATP utilisation rate in the involved skeletal muscle can increase 1000fold, compared to at rest. Despite this sudden and rapid increase in the
demand for energy during exercise, ATP never gets close to being fully
depleted in muscle cells due to the tight coupling between the rate of ATP
hydrolysis and ATP synthesis. The three pathways for ATP synthesis in
skeletal muscle are: (1) phosphorylation of ADP to ATP using
phosphocreatine (PCr); (2) anaerobic glycolysis; and (3) oxidative
phosphorylation in the mitochondria.
PCr is broken down into creatine and a phosphate that can be transferred
to the ADP molecule to resynthesise ATP using the creatine kinase enzyme
as the catalyst. In skeletal muscle, the activity of creatine kinase is quite
high and energy can be produced rapidly; however, the capacity of the
system is very low (<10-s maximal work). At the onset of exercise, glucose
(derived from muscle glycogen) is converted to glucose-6-phosphate and
subsequently to pyruvic acid, which in the absence of oxygen reduces to
lactic acid, a process that also resynthesises two molecules of ATP. This
anaerobic glycolytic process generates ATP at a slower rate than the PCr
pathway, but has a far greater capacity, so is the predominant pathway for
up to around a minute of near-maximal exercise. Lactic acid dissociates to
lactate and hydrogen ions, with the latter implicated in the inhibition of key
regulatory enzymes associated with glycolysis. Lactate that diffuses into the
blood provides a useful indication of the activation of the anaerobic
glycolytic system (i.e. exercise intensity) and the remainder is largely
oxidised in the muscle and other tissues. However, there is still a widely
held belief that lactic acid causes fatigue, which is inaccurate (Brooks,
2001). In the presence of oxygen, pyruvate is converted to acetyl
coenzyme-A, which forms the major entry point for metabolic fuels (fat and
carbohydrate) into the tricarboxylic acid (or ‘Krebs’) cycle in the
mitochondria. The Krebs cycle degrades acetyl coenzyme-A to carbon
dioxide and hydrogen, plus resynthesises one molecule of ATP. The
hydrogen atoms subsequently enter the electron transport chain that uses
oxidative phosphorylation to yield 38 ATP molecules from glucose
metabolism, or 130 ATP from a fatty acid. Clearly the only energy pathway
with the capacity to support prolonged exercise is the aerobic system.
The three energy systems described above are often considered as a
hierarchy, which is only appropriate if the relative total capacities for ATP
generation are considered; however, the metabolic response to exercise
relies on input through all three pathways that occurs simultaneously.
Rather, the extent to which each pathway is being utilised is primarily
dependent upon the demand for ATP turnover, i.e. the intensity of exercise.
The contribution of oxidative phosphorylation to the energy required for a
single maximal sprint is negligible; however, when sprints (≤10 s) are
repeated with short recovery periods (≤60 s), the aerobic contribution
increases with time (Gaitanos et al., 1993). Possessing a higher level of
aerobic fitness, therefore, tends to be associated with a lower fatigue index,
better repeated sprint ability (Girard, Mendez-Villanueva and Bishop,
2011), and a higher relative contribution of oxidative metabolism to each
sprint (Balsom et al., 1994). Crucially, resynthesis of PCr is an oxidative
process and therefore PCr recovery kinetics between repeated maximal
efforts is highly sensitive to oxygen availability (Haseler, Hogan and
Richardson, 1999). Additionally, Pi accumulation is considered to be a
major cause of fatigue during repeat sprint work, with aerobic endurance
training thought to enhance the rate of Pi removal during recovery periods
(Yoshida and Watari, 1993; Hogan, Richardson and Haseler, 1999).
Components of aerobic fitness
An athlete’s aerobic fitness is dependent upon the following physiological
constructs: maximal oxygen uptake (V̇O2max), exercise economy, lactate
threshold, fractional utilisation, critical power/speed, and oxygen uptake
kinetics. All of these components of aerobic fitness are required to varying
degrees depending upon the oxidative nature of the event an athlete is
preparing for. For example, performance in long-distance running and road
cycling is heavily reliant on exercise economy and the speed that athletes
can sustain at lactate threshold. For intermittent sports, V̇O2max represents
the ‘gold-standard’ measure of aerobic fitness and coaches would be best
served prioritising development of this component. A detailed
understanding of each aerobic capability is therefore required for S&C
coaches who work with both endurance and intermittent sport athletes;
however, it is noteworthy that the aerobic contribution to continuous events
lasting 1–3 min is also substantial (Gastin, 2001).
Maximal oxygen uptake
V̇O2max reflects the combined ability of the pulmonary, cardiovascular, and
muscular systems to uptake, transport, and utilise oxygen in the
mitochondria of working muscles, respectively (Poole and Jones, 2017). It
is well established that V̇O2max is a key determinant of both middle-distance
(e.g. Cosgrove et al., 1999; Ingham et al., 2008; Blagrove, Howatson, et al.,
2019) and long-distance endurance performance (e.g. Coyle et al., 1991;
O’Toole and Douglas, 1995; Bassett and Howley, 2000), therefore the
objective for all endurance athletes should be to maximise their aerobic
power. Although V̇O2max is undoubtedly important for any endurance
athlete, well-trained athletes have a time to exhaustion at 100% of V̇O2max
of 5–10 min (Billat et al., 1994). Therefore, the proportional contribution of
V̇O2max to events that fall within (or close to) this window of time, such as
Olympic rowing and 3-km running, is higher than other aerobic fitness
components.
In a laboratory setting with individuals who are familiar with aerobic
exercise, V̇O2max is assessed using a continuous incremental test that begins
at a moderate intensity and progresses to a severe intensity, ideally over 6–
12 min, until volitional exhaustion is reached. Expired air is collected
during the test and analysed for concentrations of oxygen and carbon
dioxide to determine V̇O2max, defined as a mathematical plateau in oxygen
uptake occurring shortly before exhaustion is reached (Poole and Jones,
2017). This should coincide with a heart rate that is within 10% of agepredicted maximum (220 − age in years). The linear relationship that exists
between oxygen uptake and intensity at submaximal work rates and the
ensuing plateau in oxygen uptake that occurs at exhaustion are shown in
Figure 4.1. In a field-based setting, the multi-stage fitness test (Léger et al.,
1988) and yoyo level 1 intermittent recovery test (Bangsbo, Iaia and
Krustrup, 2008) provide valid and reliable alternatives that enable
prediction of V̇O2max in healthy individuals.
Relationship between intensity and oxygen uptake response during an
incremental test. Oxygen uptake during the early stages of the test represents
exercise economy and the plateau in oxygen uptake represents maximal
oxygen uptake (V̇O2max). In this hypothetical example, two athletes with the
same V̇O2max (dashed line) may differ in terms of their exercise economy and
power at V̇O2max (dotted lines).
V̇
The Fick equation defines that V̇O2max is the product of maximal cardiac
output (stroke volume × heart rate) and the difference in oxygen
concentration between arterial and venous blood. This suggests that
adaptations underpinning an improvement in V̇O2max could be a
consequence of either central (oxygen delivery by cardiovascular system) or
peripheral (oxygen extraction at muscular level) mechanisms (Levine,
2008). Central mechanisms relating to increases in blood volume, red blood
cell mass, and stroke volume largely explain inter-individual variability in
V̇O2max values and correlate well with improvements after training
(Montero, Diaz-Cañestro and Lundby, 2016). Although theoretical models
(Wagner, 2015) suggest improvements in V̇O2max may be partly explained
by peripheral factors such as augmented capillarisation and increases in size
and density of mitochondrial content, there is little experimental evidence
indicating these mechanisms limit oxygen extraction. Circulatory factors
(total oxygen-carrying capacity of blood) therefore appear to be the
dominant factor underlying improvements in V̇O2max (Lundby, Montero and
Joyner, 2017).
As both replenishment of PCr and the removal of intracellular Pi are
oxygen-dependent processes, it is unsurprising that many studies have
observed a relationship between V̇O2max and performance decrements
during repeated sprinting (e.g., McMahon and Wenger, 1998; Bishop and
Edge, 2006; Rampinini et al., 2009). However, other studies have noted low
associations between V̇O2max and the drop-off in power/speed during
repeated sprint tasks (e.g., Bishop, Lawrence and Spencer, 2003; Silva,
Guglielmo and Bishop, 2010; Dardouri et al., 2014). The reasons for the
discrepancies are likely to relate to the work-to-rest ratios employed in the
studies, with higher ratios (or shorter sprint distances) generally showing
weak associations compared to lower work-to-rest ratios. Furthermore, as
V̇O2max largely reflects the ability of the cardiovascular system to deliver
oxygen, recovery from sprints may be more closely governed by respiration
at the muscle level (Girard, Mendez-Villanueva and Bishop, 2011).
Figure 4.2 provides V̇O2max scores for elite endurance athletes, which
represent the upper limits for human aerobic power (Haugen et al., 2017),
and reference values for other sports plus the 50th percentiles for healthy
adults. Elite male endurance athletes tend to possess V̇O2max values of >75
mL kg−1 min−1 and their female counterparts >65 mL kg−1 min−1, which is
virtually double that of age-matched sedentary controls. Exercise modality
impacts measurements of V̇O2max due to variations in the total muscle mass
involved, hence elite cross-country skiers tend to have higher V̇O2max
values than world-class cyclists. Although V̇O2max is highly trainable, it is
believed to have a strong genetic component (Bray et al., 2009). In elite
endurance athletes, V̇O2max values are likely to be close to the genetic
ceiling, and therefore tend to be similar and poor at explaining the interindividual variability in performances (Conley and Krahenbuhl, 1980).
Therefore, understanding and improving other components of aerobic
fitness are also important.
Maximal oxygen uptake values for male and female elite endurance athletes,
elite athletes from selected intermittent sports, and healthy individuals (20–
40 years old) from the population (50th-percentile values from several
studies shown; Kaminsky, Arena, and Myers, 2016). Population-level
descriptors for aerobic training status are also shown (Winter et al., 2006).
Shaded boxes for elite intermittent sport athletes represent typical maximum
and minimum values reported. Numbers within brackets reflect the mean
values reported in a review paper or across several original papers. MMA,
mixed martial arts. (Data taken from: Powers and Walker, 1982; Jones, 2006;
Montgomery, 2006; Kovacs, 2007; Saltin et al., 2007; Berthelot et al., 2008;
Burr et al., 2008; Ziv and Lidor, 2009; Burtscher, Nachbauer and Wilber,
2011; Gilenstam, Thorsen and Henriksson-Larsén, 2011; Lenetsky and
Harris, 2012; Manchado et al., 2013; Ransdell, Murray and Gao, 2013;
Datson et al., 2014; Phomsoupha and Laffaye, 2015; Chaabène et al., 2015;
Tønnessen et al., 2015; Bell et al., 2017; Blagrove, Howatson and Hayes,
2017; Haugen et al., 2017; Solli, Tønnessen and Sandbakk, 2017; Rønnestad
et al., 2019; Slimani et al., 2019; Spanias et al., 2019.)
Exercise economy and mechanical efficiency
Exercise economy refers to the oxygen or energy cost of performing
exercise at a submaximal intensity. To obtain a valid measurement of
economy in an athlete, a ‘steady state’ of oxygen uptake is required,
therefore only moderate intensities of exercise are appropriate for testing.
More economical athletes will use less energy to complete a given amount
of physical exercise, and thus can rely on a greater relative contribution
from aerobic metabolism for longer, thereby delaying fatigue. Exercise
economy should not be confused with ‘exercise efficiency’, although in a
colloquial sense the terms are often used interchangeably. Whereas
economy is usually quantified physiologically using oxygen consumption
and substrate utilisation values, efficiency is a mechanical term that refers
to the effective external work that is performed as a percentage of the total
energy expended to produce that work.
Unlike other physiological components of aerobic fitness that are
predominantly limited by cardiovascular and metabolic processes, exercise
economy is also influenced by biomechanical, anthropometric,
neuromuscular, and technological factors (Figure 4.3). Crucially, several of
these factors are modifiable with appropriate S&C coaching and training
interventions. Specifically, biomechanical factors that relate to how force is
modulated during a sports skill can potentially be altered with S&C
practices. For example, gait re-training approaches may improve running
economy (Moore, 2016), and weightlifting derivatives offer a means of
developing appropriate movement sequencing for enhancing rowing
efficiency (Soper and Hume, 2004). Neuromuscular factors relating to the
rate and magnitude of muscle activation, and contribution of passive
structures to elastic energy storage and return (i.e., tendon stiffness), are
also known to influence the behaviour of force–length–velocity properties
of muscles, thereby affecting energy turnover (Fletcher and MacIntosh,
2017). Indeed, eccentric strength, maximal strength and rate of force
development have been shown to relate to better running economy (Barnes,
McGuigan and Kilding, 2014; Li et al., 2021) and cycling efficiency (Sunde
et al., 2010; Louis et al., 2012).
Although a high V̇O2max is considered a prerequisite for elite endurance
performance, in a group of highly trained athletes with similar V̇O2max
scores, exercise economy or efficiency is a far better predictor of
performance (Conley and Krahenbuhl, 1980; Lucía et al., 1998; Ainegren et
al., 2013). Inter-individual variation in exercise economy can be as high as
30% in groups of endurance athletes with comparable V̇O2max values, and
improvements in economy appear to be closely related to performance
improvements (Beneke and Hütler, 2005; Saunders et al., 2010; Hoogkamer
et al., 2016). Furthermore, case studies of the former world-record holder
for the women’s marathon (Jones, 2006) and a former elite cyclist (Coyle,
2005) show that V̇O2max remained relatively stable over long periods of
time (7–11 years), yet economy/efficiency continued to improve and could
explain performance progression.
Factors that influence an athlete’s exercise economy with examples.
The lactate threshold and fractional utilisation
At low–moderate relative exercise intensities, the contribution of anaerobic
processes to energy provision is negligible, therefore blood lactate remains
similar to resting values. Figure 4.4 shows that as exercise intensity
continues to rise and the demand for energy increases, blood lactate rises
exponentially, reflecting greater reliance on the anaerobic glycolytic
pathway. An athlete’s power (or speed) at fixed blood lactate
concentrations, or blood lactate for a given power output, is an important
predictor of aerobic endurance (Steinacker, 1993; Yoshida et al., 1993;
Bentley et al., 2001) and repeated sprint performance (Silva, Guglielmo and
Bishop, 2010). The lactate threshold is represented by the first rise (>0.2
mmol L−1) in blood lactate (1–2 mmol L−1) from baseline (Jones, Carter
and Doust, 1999; Figure 4.4, panel i), which in well-trained endurance
athletes represents an intensity that can be sustained for hours.
The proportion of V̇O2max that an athlete can access and maintain for
long periods is referred to as ‘fractional utilisation’, and is also an important
factor in endurance performance (Maughan and Leiper, 1983). For example,
elite marathon runners can sustain ~85% of their V̇O2max for the duration of
the event, whereas recreational-level runners are closer to 60% (Sjodin and
Svedenhag, 1985; Jones, 2006). An athlete’s lactate threshold corresponds
closely with the fractional utilisation of V̇O2max that can be sustained for a
given duration (Bassett and Howley, 2000), therefore an increase in power
or speed at lactate threshold also allows a greater proportion of maximal
aerobic power to be accessed. A shift to the right of the lactate curve
(Figure 4.4, panel i) represents an improvement in performance, which is
primarily underpinned by metabolic adaptations relating to an ability to
buffer and clear metabolites from the blood (Jones and Carter, 2000).
Power at maximal oxygen uptake
Although V̇O2max and exercise economy are highly useful physiological
parameters, they are of limited practical use to athletes because they fail to
provide a meaningful expression of power that can be used to prescribe
training and predict performance. Power (or speed) at V̇O2max (also known
as ‘maximal aerobic speed’: MAS) provides a composite measure of
V̇O2max and exercise economy based upon the economy–intensity
relationship extrapolated to the V̇O2max value. As shown in Figure 4.1, an
athlete with superior (lower) economy at a range of submaximal intensities
who possesses a similar V̇O2max to another athlete is likely to have a
superior speed at V̇O2max. As V̇O2max represents a ceiling of an individual’s
aerobic metabolic power, a poor value will also generate a weak power at
V̇O2max score. The amalgamation of two important physiological qualities
into this single determinant appears to more accurately differentiate
performance in well-trained runners (Stratton et al., 2009; McLaughlin et
al., 2010) and elite rowers (Ingham et al., 2002) compared to other
components of aerobic fitness.
Power at V̇O2max is usually defined as the minimal power output that
elicits V̇O2max (Billat and Koralsztein, 1996). It can be determined directly
based upon the results of an incremental test to exhaustion, as shown for the
two athletes in Figure 4.1. If V̇O2max is determined using an alternative
method (e.g., increasing treadmill gradient), the oxygen uptake–intensity
relationship from a submaximal incremental test can be extrapolated, and
power/speed at V̇O2max calculated by rearranging the linear regression
equation. MAS can also be estimated in a field-based setting using a 5-min
running test (Berthon et al., 1997), or by applying the following equation to
the result of the multi-stage fitness test (for adults): MAS = 1.81 × final
shuttle stage – 7.86 (Berthoin et al., 1992).
Physiological profile and training zones for an elite male endurance runner.
Panel (i) displays results of a submaximal incremental treadmill running test,
which can be used to identify lactate threshold (dotted line) and the
corresponding heart rate zone for moderate-intensity continuous training for
this athlete (<162 beats min−1). Speed at maximal oxygen uptake (V̇O2max),
determined from a maximal test, is also shown (23.1 km h−1) along with
maximal (‘max’) heart rate. Speeds above V̇O2max are considered in the
‘extreme’ exercise domain. The typical running speeds where exercise
economy would be quantified are also displayed. Panel (ii) displays the
speed–duration relationship based upon the athlete’s best race performances
(800 m to 5 km) at the time of testing. The hyperbolic relationship is plotted,
with critical speed represented by the horizontal asymptote (dashed line; 20.8
km h−1). This critical speed is identified in panel (i) to demarcate the
boundary between the heavy-intensity and severe training zones (181 beats
min−1). Work performable at any speed above critical speed is represented by
W′. Panel (iii) shows the hyperbolic relationship between running speed and
time linearised by plotting running speed against 1/time, where the y-axis
intercept represents critical speed and the gradient of the slope represents W′.
Critical power and W′
Between the lactate threshold and power/speed that elicits V̇O2max lies a
physiological threshold that generates the maximal sustainable oxidative
metabolic rate, which is an important prerequisite for predicting
performance and guiding training decisions (Jones and Carter, 2000). The
literature is awash with a plethora of terms and definitions to identify the
maximal metabolic steady state, such as ‘maximal lactate steady state’,
various ventilatory thresholds, ‘lactate turn-point’, ‘anaerobic threshold’,
‘D-max’ threshold, and ‘onset of blood lactate accumulation’ (Jones et al.,
2019). Crucially, these terms represent different physiological events and
processes and therefore do not provide a valid reflection of the maximal
metabolic steady state that is attainable by an athlete (Jamnick et al., 2018;
Jones et al., 2019).
The critical power (or speed) model represents exercise tolerance at the
boundary between the heavy- and severe-intensity domains (Figure 4.4).
Two main parameters can be assessed using the critical power model, which
is defined as the curvilinear relationship between power output and time to
exhaustion in the severe-intensity domain. Firstly, critical power itself is
widely recognised as the most important fatigue threshold in exercise
physiology, and represents the critical metabolic rate separating two distinct
physiological domains that promote different adaptations (Poole et al.,
2016). When critical power is maintained in well-trained endurance
athletes, it leads to attainment of V̇O2max and ultimately exhaustion, usually
in ~30–45 min (Burnley and Jones, 2007). The second parameter that can
be quantified from the model is the curvature constant of the power–time
hyperbola above critical power, known as W ′ (pronounced ‘W prime’),
which is represented by the total distance that can be covered prior to
exhaustion at a constant power output (Jones et al., 2010). Above critical
power, anaerobic processes quickly begin to predominate, and provided
exercise can be sustained long enough (>2 min), V̇O2max will still be
attained (Vanhatalo et al., 2016). As shown in Figure 4.4 panel ii, the
magnitude of the difference between critical power/speed and actual
power/speed will dictate the size of W′ and therefore the rate at which the
finite work capacity will be utilised. Critical power is a strong determinant
of endurance cycling performance (e.g., Black et al., 2014; Morgan et al.,
2019) and middle-distance running performance is strongly related to
critical speed models in trained runners (Bosquet et al., 2006). Recently, the
critical power concept has been broadened to intermittent exercise, which
may have important implications for the real-time monitoring of fatigue and
residual performance capacity in game sports (Jones and Vanhatalo, 2017).
Knowledge of an athlete’s critical power and W′ enables a coach or
exercise physiologist to calculate sustainable speeds or accurately predict
tolerance limits in the severe-intensity domain, thereby informing tactics,
positioning, and pacing strategies to optimise performance. Critical power
and W′ are traditionally generated by recording the average power and time
to exhaustion for four or five separate high-intensity constant work-rate
exercise bouts in the severe exercise domain that each last between 2 and 15
min (Figure 4.4, panel ii). Alternatively, if recent race performances are
available for three or more events that take between 2 and 15 min to
complete, these can also be used. This enables the power–time hyperbolic
relationship to be plotted and the asymptote (levelling off) of the curve to
be calculated, which represents critical power. A less complicated and more
user-friendly strategy to identify the critical power value is shown in Figure
4.4, panel iii. The curvilinear power–time relationship can be expressed
linearly by plotting power/speed against 1/time. The relationship is
described using the regression equation y = mx + c, where the slope is m
and represents W′, and c is the intercept with the y-axis and identifies
critical power.
The method described above requires exhaustive exercise bouts to be
completed over multiple days with sufficient recovery, which can be time
consuming. An alternative 3-min all-out single-bout test has fortunately
been validated using cycle ergometry (Burnley, Doust and Vanhatalo, 2006;
Vanhatalo, Doust and Burnley, 2008) and running (Broxterman et al., 2013).
A further popular index of aerobic fitness that S&C coaches working with
cyclists may encounter is the ‘functional threshold power’ (FTP), which is
calculated as 95% of the mean power sustained during a 20-min time trial,
and estimates the power sustainable for ~1 hour (Gavin et al., 2012).
Although the FTP is often used interchangeably with critical power in the
coaching community, the validity of this is questionable (Morgan et al.,
2019).
Oxygen uptake kinetics
The aforementioned aerobic fitness components represent key determinants
of endurance performance; however, they do not describe the dynamic and
instantaneous nature of energy transfer that occurs during intermittent
sports, nor in endurance events where the pace and terrain vary (Burnley
and Jones, 2007). The oxygen uptake kinetic response refers to the rate at
which oxygen consumption rises during exercise to meet the required
energy demand via oxidative phosphorylation (Figure 4.5). At the onset of
exercise (or a repeat sprint), there is a short delay in the oxygen uptake
response followed by a sharp exponential rise (‘fast component’) until the
demand for energy is met (defined by a plateau in oxygen uptake). Above
moderate intensities of exercise approaching critical power, a ‘slow
component’ in oxygen uptake will also be observable; this is characterised
by an upward drift in oxygen consumption over a prolonged period.
Exercise at the upper end of the extreme zone, which is highly anaerobic
and leads to exhaustion before V̇O2max is attained, is characterised by a
single-exponential profile that describes the fast component only.
Oxygen uptake kinetics during moderate- (dotted line), heavy- (dashed line),
and severe-intensity (hatched-line) exercise. The time constant that defines
the exponential rise in oxygen uptake at the onset of exercise (‘fast
exponent’) dictates the oxygen deficit during moderate-intensity exercise.
Heavy-intensity exercise is characterised by oxygen uptake continuing to rise
beyond ~2 min, albeit at a reduced rate (‘slow component’). Quantification
of exercise economy is only valid when there is an absence of a slow
component (‘steady state’). Oxygen uptake continues to rise rapidly during
severe-intensity exercise until maximal oxygen uptake is reached. During
high-intensity exercise at the upper end of the severe-intensity zone (e.g. <1min sprints), only a fast component in oxygen uptake kinetics would be
observable.
A more rapid oxygen uptake kinetic response enhances muscle
metabolic stability, accompanied by a lower oxygen deficit, thereby
offsetting fatigue. Oxygen uptake kinetics is an important determinant of
endurance performance (Burnley and Jones, 2007; Jones and Burnley,
2009), and longer-distance endurance athletes seem to possess faster
oxygen uptake responses compared to middle-distance athletes matched for
competitive status (Kilding, Winter and Fysh, 2006). As alluded to
previously, the ability to recover sprint ability during intermittent sports
performance is largely dependent upon the recovery of PCr and metabolites
associated with fatigue, which are governed by oxidative processes. Faster
oxygen uptake kinetics to exercise of severe intensity is associated with
smaller decrements in repeated sprint performance (Dupont et al., 2005,
2010; Rampinini et al., 2009), although it has been suggested that this
correlation is spurious, and it is aerobic fitness (V̇O2max) rather than
metabolic control that governs the relationship (Buchheit, Hader and
Mendez-Villanueva, 2012). Certainly, endurance training, which increases
oxygen transportation and delivery, capillarisation, mitochondrial density,
oxidative enzyme activity, and muscle perfusion, has also been shown to
improve V̇O2max and oxygen uptake kinetics (Phillips et al., 1995; Koppo,
Bouckaert and Jones, 2004).
A large body of work has illustrated the importance of the warm-up for
acutely enhancing oxygen uptake kinetics (Jones et al., 2011). In particular,
a warm-up that includes a short period of high-intensity activity (60–85% of
peak power output) lasting 3–6 min is sufficient to positively influence
subsequent endurance performance via an improvement in oxygen uptake
kinetics at the onset of exercise (e.g., Gurd et al., 2006; Bailey et al., 2009;
Mattioni Maturana et al., 2018). Several studies have also investigated the
effects of high-intensity intermittent and single-sprint approaches to
enhancing the oxygen uptake response at the start of exercise (Burnley,
Doust and Jones, 2002; Bishop, Bonetti and Spencer, 2003; McIntyre and
Kilding, 2015). For example, when compared to a continuous warm-up of
lower intensity, a priming protocol involving 5 × 10-s near-maximal sprints
(50 s recovery) has been shown to enhance kayak 2-min time trial
performance by a small but significant margin (Bishop, Bonetti and
Spencer, 2003).
SECTION 2
Strategies to develop aerobic fitness
Based upon an understanding of the physiological factors that limit
endurance performance, several key thresholds emerge that can clearly
demarcate aerobic training zones for athletes (Figure 4.4, panel i):
Moderate zone: intensities below the lactate threshold
Heavy zone: intensities above the lactate threshold and below critical
power/speed
Severe zone: intensities above critical power/speed and below
power/speed at V̇O2max
Extreme zone: intensities above power/speed at V̇O2max.
A schematic displaying the main strategies to develop the components of
aerobic fitness for various sports, including recommendations for exercise
prescription, is shown in Figure 4.6. Discussion of repeat sprint training and
peri-maximal sprint interval training is beyond the scope of this chapter as
the physiological demands are largely associated with anaerobic
metabolism and neuromuscular factors (see Chapter 5). Repeat sprint
training is characterised by bouts of maximal effort (≤10 s) interspersed by
incomplete recoveries (≤60 s) to mimic sports-specific scenarios (Girard,
Mendez-Villanueva and Bishop, 2011). Sprint training requires full interrepetition recovery to ensure that close to absolute maximal power/speed
can be achieved in each repetition. For competitive long-distance athletes,
the sprint at the end of an event often determines the winner. It is a
misconception that high volumes of endurance training cause athletes to
lose their explosive power/speed; rather, it is the lack of stimulus directed
towards maintaining (or indeed improving) this capability that causes the
deterioration (Mujika and Padilla, 2000). It is therefore important that
endurance athletes include a small amount of maximal power/speed training
in their programme year-round (Sandford et al., 2019), and this can form
part of S&C sessions (Blagrove, Howe et al., 2020).
Training strategies and recommended exercise prescription to develop
aerobic fitness components for various categories of sports. %HRmax,
percentage of maximum heart rate; V̇O2max, maximal oxygen uptake.
Continuous moderate-intensity training
Continuous exercise performed at a moderate intensity (below lactate
threshold; <75% maximum heart rate; <70% power/speed at V̇O2max) is
usually prolonged (30 min to several hours) in nature and represents an
important mode of training for endurance athletes (Midgley, McNaughton
and Jones, 2007). Exercise in this domain enhances stroke and plasma
volume, and increases capillary and mitochondrial density that improves the
efficiency of metabolic processes and V̇O2max (Holloszy and Coyle, 1984;
Hellsten and Nyberg, 2015). This training zone is used extensively by
endurance athletes for ‘easy’ active recovery training, which punctuates
more intensive interval training workouts (Seiler, 2010), but has less
functional relevance for intermittent sport performers.
It has been recognised that endurance training history is an important
factor determining superior exercise economy (Morgan et al., 1995) and
several case reports have demonstrated continued improvement in exercise
economy or efficiency over long periods of time with increased volume of
aerobic training, despite little alteration in V̇O2max (Conley et al., 1984;
Coyle, 2005; Jones, 2006). A recent meta-analysis has also shown that
continuous training is more effective than interval training for improving
exercise economy in recreational endurance runners (González-Mohíno et
al., 2020). Furthermore, recreational runners possess higher stride-to-stride
movement variability, more inconsistent muscle recruitment patterns, and
longer durations of muscle activity compared to moderately trained runners
(Chapman et al., 2008). These factors suggest an inferior level of motor
control in lesser-trained endurance athletes, which is in line with findings
from across the motor learning literature showing that long-term practice of
a skill decreases movement variability, and results in reduced amplitude and
duration of muscle activity, thus improving exercise economy
(Thoroughman and Shadmehr, 1999; Osu et al., 2002).
Tempo training
An intensity of exercise that falls above the lactate threshold but below
critical power (Figure 4.4) is often colloquially referred to as ‘steady’: too
fast to be used for active recovery sessions, and too slow to stimulate
meaningful cardiovascular adaptations. Exercise in the upper end of this
zone, where blood lactate is increasing >1 mmol L−1 for every 1 km h−1
increase in speed (~2–4 mmol L−1), is often referred to by endurance
athletes as ‘tempo’ training. Tempo sessions are usually performed
continuously (20–60 min), but when the intensity approaches critical power,
exercise can be performed as long intervals of 8–20 min with a short
recovery, e.g., 4 × 8 min (2-min recovery). These sessions are popular with
long-distance endurance athletes (e.g., marathon runners and road cyclists)
as regular exposure to these intensities is slightly higher than competition
power/speed and can increase lactate threshold and fractional utilisation
(Midgley, McNaughton and Jones, 2007).
Interval training
Both continuous training and interval training (above critical power) elicit
improvements in V̇O2max following a 3–24-week training intervention
(Milanovic, Sporis and Weston, 2015). However, there is a large body of
evidence that demonstrates interval training provides a more potent
stimulus to maximise aerobic adaptations (Bacon et al., 2013; Gist et al.,
2014), including in highly trained endurance athletes (Kubukeli, Noakes
and Dennis, 2002; Laursen and Jenkins, 2002). A multitude of different
interval training methods have been shown to enhance the components of
aerobic fitness. For endurance athletes, the optimal intensity to develop
aerobic fitness (specifically, V̇O2max and critical power) appears to be
around power/speed at V̇O2max, which corresponds to an intensity of 90–
100% maximum heart rate (Billat and Koralsztein, 1996; Stöggl and
Sperlich, 2014). Repeated sprint training (i.e., near-maximal sprints ≤ 10 s,
≤ 60 s recovery), and even maximal speed training, has been shown to
improve V̇O2max in moderately trained games players (Ross and Leveritt,
2001; Bishop, Girard and Mendez-Villanueva, 2011), demonstrating that in
less aerobically trained athletes, most types of interval training are likely to
enhance aerobic fitness capabilities. Rather, in well-trained endurance
athletes, there is a greater requirement for careful deliberation around how
interval training is prescribed and progressed.
Taken together, research findings suggest that the use of a 1:1 or 2:1
work-to-rest ratio optimises interval training for aerobic development,
including enhancement of intermittent sports performance. For example, 8
× 2-min repetitions (1 min recovery) performed at 80–90% of V̇O2max have
previously been recommended as a suitable session for improving aerobic
fitness in athletes who require repeated sprint ability in their sport (Bishop,
Girard and Mendez-Villanueva, 2011). A session of 4 × 4 min (3 min active
recovery) at 90–95% maximum heart rate has also been advocated for
soccer players (Helgerud et al., 2001). ‘Tabata’ sessions have been
popularised over the last 20 years due to their time efficiency (4 min of
high-intensity exercise), and involve 20-s bouts of exercise with 10 s
recovery, repeated eight times, and performed at 115–130% of the
power/speed associated with V̇O2max (Tabata et al., 1996; Viana et al., 2018,
2019). Other session examples from peer-reviewed publications that have
reported the training of gold medallists from major international
championships include 4 × 6 min (1 min recovery) in a 1500-m runner
(Tjelta, 2013), 5 × 4–5 min (2–3 min recovery) in a cross-country skier
(Solli, Tønnessen and Sandbakk, 2017), and 10 × 1 min (~45 s active
recovery) in a long-distance runner (Pugliese et al., 2014).
Although these types of session are likely to be more beneficial than
moderate-intensity continuous training for improving V̇O2max in athletes
who are moderately aerobically trained, it is unclear which specific strategy
offers the best outcome. It is likely that adaptations to longer work interval
bouts (3–6 min per repetition) are more centrally (cardiovascular) derived,
whereas shorter high-intensity sessions (e.g. Tabata sessions) provide
greater peripheral-level adaptations. Additionally, the work-to-rest ratios
suggested (Figure 4.6) by no means represent ‘the rule’, as middle-distance
athletes (e.g., 400-m swimmers, rowers, 1500-m runners) will often
undertake extended sprint efforts (20–40 s duration) with long recoveries
(work-to-rest ratio of 1:10) within competitive phases of training to enhance
event-specific speed.
Manipulation of technical sport practices
It has been suggested that the technical training completed by intermittent
sport athletes on a regular basis is sufficient to enhance aerobic fitness
(Hill-Haas et al., 2011). This has appeal because the simultaneous
development of technical skills, tactical aptitude, and physiological factors
is time-efficient, and could maximise motivation in sub-elite and younger
athletes. Indeed, in male youth soccer players, small-sided games are an
effective method for developing aerobic capabilities compared to
conventional endurance training (Moran et al., 2019). Certainly, in
recreational-level games players, and adolescent athletes at the
specialisation stage of their development, small-sided games should be
prioritised to provide concurrent improvements of aerobic fitness and
technical skills (Harrison et al., 2015; Moran et al., 2019). However, in
games players of higher qualification status and young athletes pursuing
proficiency in their chosen sport, a combination of small-sided games and
interval training is likely to offer greater benefits, particularly during offseason preparatory periods (Harrison et al., 2015). Equally, in short-burst
intermittent sports where aerobic fitness is far less important than other
physical attributes (e.g., rugby, baseball, cricket), technical practices are
likely to provide enough stimulus to stress the metabolic systems
appropriately. S&C coaches utilising small-sided games with the aim of
improving aerobic fitness should consider how task constraints alter the
physiological response of training. Specifically, a smaller number of
involved players, a larger playing area, an absence of goalkeepers, and a
rule that reduces the number of touches permitted all increase the
physiological intensity in soccer games (Clemente, Martins and Mendes,
2014).
Training intensity distribution in endurance athletes
As discussed, interval training (in the severe- and extreme-intensity zones)
has been shown to provide greater enhancements in endurance sport
performance compared to moderate-intensity continuous training.
Instinctively, S&C coaches will often take these findings at face value and
may be tempted to level criticism at endurance athletes and their coaches
for following a high-volume paradigm of training. There are several issues
and caveats associated with the literature that has compared moderateversus high-intensity focused approaches in endurance athletes, and which
S&C coaches should be aware of:
Studies are often short in duration. High-intensity interval training has
a high physiological burden, therefore frequent and excessive use of
this style of exercise in the long term may lead to overtraining
(Kellmann, 2010). Consequently, the findings of studies can only be
applied to the duration over which the training intervention was carried
out. Indeed, adding additional high-intensity interval training sessions
in the 4–8 weeks prior to a major competition as part of a long-term
periodised plan seems highly appropriate, and is typically the approach
employed by well-trained and elite endurance athletes (Stöggl and
Sperlich, 2015).
Studies may be observing a ‘peaking effect’ that can be attributed to
the reduction in training volume rather than the increase in intensity. In
studies that have used well-trained endurance athletes, who are likely
to be habitual high-volume exercisers, manipulating training towards
an intensity bias approach may also act as a novel stimulus to reduce
feelings of staleness (Gustafsson, Kenttä and Hassmén, 2011).
Lastly, the primary dependent variables examined in studies are usually
V̇O2max and time trial performance; therefore, based upon the principle
of training specificity, it is likely that the training regimen that most
closely matches the intensities associated with V̇O2max elicitation and
time trial performance will improve the most. Often, other important
aerobic fitness components are not measured as part of studies,
therefore it is unknown whether a high-intensity dominant approach to
training would promote these capabilities to the similar extent.
Based upon this brief critique and previous discussion, it is likely that a
combination of moderate-intensity continuous and high-intensity interval
training sessions yield the greatest benefit to endurance performance in the
long term (Seiler, 2010). Several models have emerged from the training
literature in elite endurance athletes; the three main approaches are shown
in Figure 4.7:
Endurance training intensity distribution for three common approaches
adopted by endurance sport athletes.
An approach where a high proportion (75–90%) of training time is
dedicated to moderate-intensity exercise, with decreasingly smaller
amounts to heavy zone training (10–20%) and severe-intensity training
(5–10%) has been termed a ‘pyramidal design’.
A ‘threshold approach’ involves athletes spending a large portion of
their total training time (35–55%) in the ‘heavy’ domain with the
remainder (45–55%) largely spent in the moderate-intensity zone
(Seiler and Kjerland, 2006).
Lastly, a method termed the ‘polarised training’ approach consists of a
high volume of moderate-intensity training (~80%), a low amount of
training in the heavy domain (~5%) and 15–20% of training time in the
severe and extreme domains (Stöggl and Sperlich, 2015).
In the majority of observational studies, elite athletes from rowing
(Fiskerstrand and Seiler, 2004), cross-country skiing (Solli, Tønnessen and
Sandbakk, 2017; Rasdal, Moen and Sandbakk, 2018), cycling (Schumacher
and Mueller, 2002), distance running (Jones, 2006), and paratriathlon
(Mujika, Orbañanos and Salazar, 2015) tend to adopt a pyramidal approach
to training, with a high volume of moderate-intensity exercise, particularly
during general preparatory phases, and small amounts of high-intensity
interval training. Interestingly, the majority of experimental studies (6
weeks to 5 months) in endurance performers of all levels demonstrate
superior responses to a polarised training approach, especially compared to
a threshold intensity distribution (see reviews: Stöggl and Sperlich, 2015;
Rosenblat, Perrotta and Vicenzino, 2019). Spending high volumes of
training time (>10%) in the heavy-intensity domain has been associated
with diminished training gains (Munoz et al., 2014), therefore current
recommendations are to avoid this ‘middle ground’ for easy recovery
training volume and interval training sessions. Longitudinal retrospective
reports of elite athletes and international training squads also provide
evidence that a shift towards a polarised training approach characterises
higher levels of performance (Fiskerstrand and Seiler, 2004; Ingham, Fudge
and Pringle, 2012; Orie et al., 2014).
The role of strength-training exercise with endurance athletes
Strength training and aerobic endurance training are diverse exercise
modalities offering vastly different functional outcomes. Endurance training
(low load–high repetition) elicits largely cardiovascular and metabolic
changes such as mitochondrial biogenesis and changes to substrate
metabolism, whereas strength training (high load–low repetition) is
associated with an increase in contractile protein content and maximal
contractile force output (Coffey and Hawley, 2007). It may therefore seem
counterintuitive that strength training may positively affect components of
aerobic fitness and enhance endurance performance.
As previously highlighted, exercise economy is partly dependent upon
the intrinsic contractile energetic cost of the muscle fibres recruited during
exercise, as well as the peak fibre force, shortening velocity, magnitude of
fibre length change, and rate of contractions. These neuromuscular factors
can potentially be positively influenced by strength-training activities.
Moreover, muscular performance characteristics can be acutely enhanced as
a result of their recent contractile history (Tillin and Bishop, 2009), which
offers a potential for short-term improvement in endurance performance.
Strength training may also play a role in offsetting the risk of overuse injury
(Lauersen, Andersen and Andersen, 2018), which is common in endurance
athletes, and has been cited as the most frequent reason for the inclusion of
S&C in training programmes (Blagrove et al., 2020).
Post-activation performance enhancement
High-intensity conditioning contractions using strength-training exercises
have become a popular means of acutely enhancing muscle contractile
properties that benefits subsequent explosive athletic performance (Seitz
and Haff, 2016). Following a low-intensity aerobic warm-up, performing a
maximal or near-maximal strength exercise 5–10 min prior to a bout of
aerobic endurance exercise may also be effective for enhancing
performance (Blagrove, Howatson and Hayes, 2019). Indeed, a single set
(5–6 repetitions) of depth jumps appears to acutely enhance running
economy in high-performing adolescent middle-distance runners compared
to a traditional low-intensity warm-up (Blagrove, Holding, et al., 2019).
Similarly, band-resisted squat jumps (4 × 5 repetitions) have also been
shown to improve performance in a session of 5 × 1-km runs (Low et al.,
2019). Moreover, a series of pre-session ‘strides’ (6 × 10 s at 1500-m pace)
wearing a weighted vest (20% of body mass) has also provoked an acute
benefit to running economy and time to exhaustion in well-trained distance
runners (Barnes et al., 2015). The early stages of both a 1-km rowing
ergometer time trial and a 20-km static cycle were also significantly
improved following maximal isometric contractions (5 × 5 s) and a highload leg press protocol (4 × 5 repetition maximum), respectively (Feros et
al., 2012; Silva et al., 2014). In each of the aforementioned studies, welltrained or elite endurance athletes were used, and most participants
possessed a background in strength training (Feros et al., 2012; Silva et al.,
2014; Barnes et al., 2015; Low et al., 2019). The extent to which a postactivation performance enhancement is elicited in endurance athletes also
appears closely related to the training status of the limb exposed to the
conditioning stimulus (Hamada, Sale and Macdougall, 2000). Therefore,
S&C coaches should consider the type of endurance athlete who may
benefit from a post-activation performance enhancement warm-up protocol.
Chronic strength training
A large body of literature has investigated whether strength training (i.e.,
heavy resistance training, explosive power training, plyometrics or mixedmodality training) can improve performance and/or the physiological
factors that underpin endurance events, compared to a group who only
carries out aerobic endurance training (see reviews: Berryman et al., 2018;
Blagrove et al., 2018; Thiele et al., 2020). In general, findings support the
implementation of regular strength training as an addition to sport-specific
endurance training to enhance exercise economy and performance.
Typically, studies show a small–moderate benefit (2–8%) to exercise
economy and performance from incorporating 2–3 sessions per week of
strength training for a period of 6–14 weeks, compared to a control group
(Denadai et al., 2017; Berryman et al., 2018).
Most investigations that utilise resistance training as part of their
strength-training intervention observe large improvements in strengthrelated metrics with little change in measures of body composition
following the training period. This is important because resistance training
is associated with a hypertrophy response that increases total body mass and
decreases capillary density, oxidative enzymes, and mitochondrial density
(Tesch, Komi and Hakkinen, 1987; Dudley, 1988), which is likely to
adversely impact upon aerobic performance. Strength training-induced
effects to exercise economy and performance do not appear to be moderated
by strength-training type, athlete age or training status. Indeed, beneficial
changes to running economy have been observed in both post-pubertal
adolescent distance runners (Mikkola et al., 2007; Blagrove et al., 2018)
and masters runners (Piacentini et al., 2013).
Summary
Possessing an understanding of aerobic fitness is important for S&C
practitioners because: (1) it may be within their remit to assess and develop
components of aerobic fitness when working with intermittent sports
performers; and (2) when supporting endurance sport athletes, developing
effective S&C practices is predicated on a familiarity with the factors that
limit performance and how athletes prepare for their event. The power
elicited at lactate threshold and critical power are valid physiological
constructs that demarcate the boundaries between moderate–heavy and
heavy–severe exercise intensity zones, respectively. These parameters,
along with V̇O2max and exercise economy, provide an invaluable framework
to understand and develop aerobic fitness in athletes. In intermittent sports,
aerobic metabolism plays a major role in the restoration of homeostasis
during the recovery periods between high-intensity efforts. Endurance
training increases mitochondrial density, which enhances PCr and oxygen
uptake kinetics and therefore improves intermittent sprint performance.
Interval training, at a work-to-rest ratio of 1:1 or 2:1, appears to be the most
potent stimulus to enhance several important aerobic fitness capabilities.
However, S&C coaches should expect well-trained endurance athletes to be
undertaking high volumes of aerobic training, with a large proportion of the
total volume (~80%) performed at a moderate intensity. Supplementing the
training of an endurance athlete with twice-weekly strength-training
sessions is likely to enhance exercise economy and improve performance
over a period of several months. Highly trained endurance athletes may also
benefit from the inclusion of high-intensity sprints or a high-load strength
exercise in the latter stages of a warm-up.
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5
Repeat sprint ability:
physiological basis and
implications for training
Anthony N. Turner and David Bishop
DOI: 10.4324/9781003044734-7
Introduction
Many sports involve frequent bursts of high-intensity movements,
interspersed with brief recovery intervals (consisting of complete rest or
low- to moderate-intensity activity), over an extended period of time (1–4
hours) (Glaister, 2005; Spencer et al., 2005). Therefore, the ability to
recover and to reproduce performance during subsequent high-intensity
efforts is an important fitness requirement of athletes engaged in these
disciplines and has been termed repeated-sprint ability (RSA). While many
different types of training have been proposed to improve RSA, highintensity interval training (HIIT) and sprint interval training (SIT) have
been suggested as a means of developing many of the factors contributing
to RSA. Given the apparent importance of HIIT and SIT for developing
RSA, it is important that strength and conditioning coaches have a thorough
understanding of how to manipulate the programming of these to best
achieve improvements in RSA. Therefore, the aims of this chapter are to:
(1) provide a brief overview of the underlying physiology of repeated
sprints; (2) discuss the interaction between sprint intervals (duration and
frequency) and metabolic energy supply; (3) identify various approaches to
HIIT and SIT programming and their physiological basis for adaptation;
and, finally, (4) discuss RSA testing that can then be used to judge the
efficacy of training.
The metabolic demands of repeated sprints
RSA requires both a high maximal sprint power and the ability to maintain
high power during each subsequent sprint. A high maximal sprint power is
related to the ability to deplete large amounts of high-energy phosphates at
a fast rate. The human muscle stores ~25 mmol/kg dry muscle (dm) of
adenosine triphosphate (ATP). With a peak ATP turnover rate of ~15
mmol/kg dm/s, that is enough to fuel 1–2 s of maximal work (Gaitanos,
Williams, Boobis, & Brooks, 1993). Therefore, from a metabolic
perspective, power is dictated by the amount and rate at which ATP is
resynthesised and then hydrolysed. ATP is never actually fully depleted (as
it is also used for basic cellular functioning), depleting by 45% in a 30-s
sprint (Boobis, Williams, & Wooton, 1982) and between 15% and 30% in a
10-s sprint (Jones et al., 1985). As ATP stores are broken down, various
metabolic pathways (energy systems) collaborate to resynthesise ATP in an
attempt to maintain peak rates of ATP turnover. As the brief recovery times
between repeated sprints will lead to only a partial restoration of energy
stores, the amount of ATP resynthesised is likely to be an important
determinant of the ability to maintain high power during each subsequent
sprint. With respect to the energy systems used to resynthesise ATP, there is
a trade-off between power and capacity. The contribution of each energy
system is determined by exercise intensity, bout frequency and the duration
of the rest period. The energy systems are phosphocreatine (PCr), anaerobic
glycolysis and the aerobic/oxidative system; these are briefly discussed in
the next sections.
Phosphocreatine
There are ~80 mmol/kg dm of PCr stored in the muscle (Gaitanos,
Williams, Boobis, & Brooks, 1993) – around three times the amount of
ATP. With a turnover rate of ~9 mmol ATP/kg dm/s (Hultman & Sjöholm,
1983), PCr stores are largely depleted within 10 s of sprinting (Glaister,
2005). The PCr system has the fastest ATP turnover rate of all energy
systems, as there is only one enzymatic reaction (compared to the nine that
occur with glycolysis, for example). As with ATP, and because of the
contribution made by the other pathways, PCr is not normally completely
depleted. For example, during all-out efforts, PCr is only depleted by 60–
80% over 30 s (Boobis, Williams, & Wooton, 1982), 40–70% over 10 s
(Jones et al., 1985), 30–55% over 6 s (Boobis, Williams, & Wooton, 1982)
and 25% over 2.5 s (of electrical muscle stimulation) (Hultman & Sjöholm,
1983); these results suggest that the ATP for a short sprint is also heavily
subsidised by anaerobic glycolysis.
Because the recovery of power output maps the time course of PCr
resynthesis (Sahlin & Ren, 1989; Bogdanis, Nevill, Boobis, Lakomy, &
Nevill, 1995; Mendez-Villanueva, Edge, Suriano, Hamer, & Bishop, 2012)
and is attenuated by creatine supplementation (Mujika et al., 2000), PCr
availability is likely to be a major factor governing the ability to repeat a
maximal sprint effort (Glaister, 2005). PCr is resynthesised by the aerobic
system within the mitochondria, via the creatine shuttle, and requires one
molecule of ATP to resynthesise ATP. Given this cost, restoration happens
when energy requirements are low, such as during recovery periods. As
such, the contribution of PCr to subsequent sprints is governed by the
length of the rest period; PCr resynthesis occurs at around 1.3 mmol/kg
dm/s (Gaitanos, Williams, Boobis, & Brooks, 1993). Approximately 85% of
PCr stores are restored in 2 min, 90% in 4 min and 100% in 8 min (Harris et
al., 1976; Hultman, Bergstrom, & Anderson, 1967). Furthermore, recovery
only happens when the blood supply to the working muscle is not occluded,
which in turn is suggestive of why an active recovery between bouts is
important (and may expedite PCr resynthesis). For example, an active
recovery (vs. passive) consisting of cycling at submaximal intensities
significantly increased peak power using 8 × 6-s cycle sprints with 30 s of
rest (Signorile, Tremblay, & Ingalls, 1993). In addition to aiding PCr
resynthesis, the active recovery may reduce muscle acidosis by speeding up
the removal of hydrogen ions (H+) and lactate (LT) from the working
muscles; this would also increase the use of LT as a fuel source (Signorile,
Tremblay, & Ingalls, 1993).
Adaptations that aid the resynthesis of ATP by the PCr system likely
result from increases in the enzymes creatine kinase and myokinase (the
latter catalyses the phosphorylation of two adenosine diphosphate (ADP)
molecules to ATP and adenosine monophosphate (AMP)), and adaptations
to the aerobic system such as increased blood flow and mitochondrial
biogenesis. For example, Bishop et al. (2008) reported improvements in
PCr resynthesis following a HIIT protocol of 6–12 × 2-min repetitions at
approximate maximal oxygen uptake (~V̇O2max), with 1-min rest periods.
Adaptations here were attributed to improvements in aerobic fitness. This
was in contrast to 8 × 30-s repetitions at ~130% V̇O2max, with 90-s rest
periods, where no change was found. There is, however, limited research
investigating the effects of different types of training on PCr resynthesis.
Anaerobic glycolysis
During brief maximal sprints, the rapid drop in PCr stores is offset by
increased activation of glycolysis and glycogenolysis; the former relates to
the breakdown of glucose from the blood stream and the latter to the
breakdown of glycogen in the cytoplasm. The maximal turnover rate of
ATP production via these pathways is around ~8 mmol/kg dm/s (Hultman
& Sjöholm, 1983; Jones et al., 1985; Gaitanos, Williams, Boobis, &
Brooks, 1993; Parolin et al., 1999). This system involves multiple
enzymatic reactions, so is not as fast as the PCr system, but collectively
they maintain an ATP turnover rate of ~12 mmol/kg dm/s (Boobis,
Williams, & Wooton, 1982; Gaitanos, Williams, Boobis, & Brooks, 1993).
Glycolysis actually uses one ATP, as glucose must first be converted into
glucose 6-phosphate via the hexokinase reaction once it enters the cytosol;
this point should emphasise the importance of starting competitions in a
fully glycogen-loaded state. The rapid onset of anaerobic glycolysis with
maximal work can be noted by studies that report high values of LT (>4
mmol/L) within 10 s (Boobis, Williams, & Wooton, 1982; Jones et al.,
1985). Surprisingly, values as high as 40 mmol/kg dm have been recorded
after just 6 s of sprint cycling (Dawson et al., 1997).
Following different types of training, adaptations to this system include
increases in the enzymes phosphorylase, phosphofructokinase (PFK) and
pyruvate dehydrogenase (PDH). PFK is considered the regulatory enzyme
here, responding to increased cellular levels of AMP and inorganic
phosphate (Pi), as would be expected at the start of a sprint. Increases in
PDH activity ensure that pyruvate production is more closely matched to
oxidation, thus increasing acetyl coenzyme A provision for the tricarboxylic
acid (TCA) cycle. This is an important adaptation to RSA, as it means less
production of lactate acid or, rather, the accompanying increases in H+.
Training-induced changes in phosphorylase and PFK are likely greater
using intervals that stimulate maximal accumulated oxygen deficit (Bishop,
Girard, & Mendez-Villanueva, 2011); for example, training that involves
repeated 30-s bouts (Bogdanis, Nevill, Boobis, Lakomy, & Nevill, 1995).
Furthermore, greater rest durations between repetitions appear needed (>4
min) to ensure a maximally high intensity of work, and thus maximal
stimulation of glycolytic enzymatic activity.
With intramuscular stores of around 400 mmol/kg dm (Gaitanos,
Williams, Boobis, & Brooks, 1993), glycogen availability is not likely to
majorly compromise ATP provision during the repeated sprints typically
used during research studies (Glaister, Stone, Stewart, Hughes, & Moir,
2005). Instead, it may be the progressive changes in metabolic environment
(as noted by the aforementioned high LT values) that ultimately cause a
reduction in ATP provision via this system. For example, Gaitanos et al.
(1993), using 10 × 6-s sprints with 30-s rest periods, found that the first
sprint produced ATP using 50% PCr and 44% glycolysis, while the tenth
sprint used 80% PCr and 16% glycolysis; this was accompanied by a 27%
loss in power output, an 11 mmol/L increase in muscle LT and a significant
drop in ATP production rate. In such scenarios, noting the relatively
forgiving work-to-rest (W:R) ratio of Gaitanos et al. (1993), the shortfall in
energy is thus provided by the aerobic system (McGawley & Bishop, 2015).
Hydrogen ion flux and buffer capacity
The anaerobic conversion of pyruvate yields LT and H+. LT, however, is not
the cause of fatigue and can be used as an energy substrate. For this, LT is
transported in the blood to the liver, referred to as the Cori cycle, and
converted into glucose. Instead, the H+ accumulation decreases intracellular
pH, which in turn has been reported to inhibit oxidative phosphorylation
and the activity of glycolytic enzymes (such as PFK), as well as the binding
of calcium to troponin and thus muscle excitation–contraction coupling
(Nakamaru & Schwartz, 1972). Therefore, the removal of H+ from skeletal
muscle is likely to be of importance for the ability to sustain repeated
sprints (Pilegaard, Domino, Noland, & Bangsbo, 1999). For example, while
the trained and untrained may have similar release rates of LT and H+
during intense exercise, the intracellular-to-interstitial gradients of these are
lower in the trained population (Sahlin & Henriksson, 1984). Combined,
these results suggest a trainable muscle buffer capacity that may be
important to repeated-sprint performance.
The transient nature of the physiological pH (i.e. 7.4), which is affected
by changes in H+, is governed by a series of buffering mechanisms. These
attenuate the effects of H+ on metabolism by removing H+ when the pH
declines (creating an acidic environment) and by releasing H+ when the pH
increases. There are both intracellular (i.e. protein and phosphate groups)
and extracellular (i.e. proteins, haemoglobin and the bicarbonate pool)
buffers. As the H+ diffuses out of the muscle into the blood, it is buffered by
bicarbonate (via the bicarbonate buffering system), thus attenuating changes
in plasma pH by shifting the chemical equilibrium according to Le
Chatelier’s principle. For example, any excess H+ will associate with
bicarbonate (forming carbonic acid), thus resulting in a smaller net increase
in acidity. The reaction is illustrated in equation 5.1, below. This buffering
system is further facilitated by an increase in respiration rate to remove
excess CO2 and thus acidity. Interestingly, one of the reasons you vomit
during high-intensity training is that this provides the quickest means to
remove large amounts of acid – the stomach is full of hydrochloric acid. In
a similar way to bicarbonate, phosphate ions (see equation 5.2, below) and
carnosine act as intracellular buffers. Carnosine is a dipeptide formed of
two amino acids, beta-alanine and histidine, with the former often regarded
as an ergogenic aid to HIIT-type activities (Artioli, Gualano, Smith, Stout,
& Lancha, 2010). Similarly, supplementation with sodium bicarbonate can
be beneficial (Bishop, Davis, Edge, & Goodman, 2004), as is a combination
of both (Tobias et al., 2013).
Bishop et al. (2004) have shown that muscle buffer capacity (calculated
in vivo from the ratio of blood LT to changes in pH and as per equation 5.3)
and RSA (5 × 6-s cycle sprints, departing every 30 s) are significantly
correlated (r = 0.72, n = 23); this relationship with RSA was actually higher
than that for V̇O2max and LT (r = 0.60 and 0.55, respectively). Further, Edge
et al. (2006) have shown that increases in buffer capacity are intensitydependent. In two groups matched for volume and showing similar
improvements in V̇O2max and LT post-training, only the high-intensity
group (working at 120–140% LT) significantly improved buffer capacity.
Improvements in buffer capacity are also attributable to improvements in
the sarcolemmal LT/H+ transport capacity as well as an enhanced content of
monocarboxylate transport proteins (MCT1 and MCT4) (Pilegaard,
Domino, Noland, & Bangsbo, 1999).
where CO2 = carbon dioxide, H2O = water, H2CO3 = carbonic acid, H+ =
hydrogen ion and HCO3− = bicarbonate ion
where HPO42− = hydrogen phosphate, H+ = hydrogen ion and PO43− =
phosphate ion.
for calculating buffer capacity (β), where Δ = change and La− = lactate
(Sahlin & Henriksson, 1984).
Aerobic metabolism
Unlike the anaerobic resynthesis of ATP that occurs in the cytoplasm of the
cell, oxidative resynthesis occurs in the mitochondria. Here, pyruvate (via
PDH) is converted to acetyl coenzyme A (rather than lactic acid), where it
then enters the TCA cycle and then the electron transport chain, before
yielding 28 moles of ATP (vs. 1 from the PCr system, 2 from glycolysis and
3 from glycogenolysis). This system contributes to ATP provision sooner
than commonly believed. For example, during the first 6 s of a 30-s
maximal sprint (Parolin et al., 1999), or the first 5 s of a 3-min intense bout
(> 120% V̇O2max) (Bangsbo, Krustrup, González-Alonso, & Saltin, 2001),
an ATP turnover rate of ~1 mmol ATP/kg dm/s was hypothesised; this
contributed ~10% of total energy produced. Also, as sprints are repeated,
the V̇O2 of successive sprints will increase (Gaitanos, Williams, Boobis, &
Brooks, 1993; Spencer, Bishop, Dawson, & Goodman, 2005) if recovery
periods are not sufficient to resynthesise PCr, oxidise LT and remove
accumulated intracellular Pi (through ADP phosphorylation via myokinase).
For example, McGawley and Bishop (2015) investigated the V̇O2 during the
first and last sprints during two 5 × 6-s repeated-sprint bouts, separated by
passive rest, such that work done between each bout was the same. These
investigators sought to assess the influence made by oxidative metabolism
on RSA, hypothesising that reductions in fatigue and improved sprint times
would be related to markers of aerobic fitness. Across both bouts, the V̇O2
during the first sprint was significantly less than the last sprint (p < 0.001),
the estimated aerobic contribution to the final sprint (measured in kJ) was
V̇
significantly related to V̇O2max (r = 0.81, p = 0.015 and r = 0.93; p = 0.001,
respectively) and finally, the V̇O2 attained in the final sprint was not
significantly different from V̇O2max (p = 0.284 and p = 0.448, respectively).
The authors concluded that given the continuous increases in V̇O2 across
sprints, V̇O2max might be a limiting factor to performance in later sprints.
However, while V̇O2 may increase with successive sprints, the supply of
ATP made by the aerobic system is significantly less than required for
repeated sprints (Gaitanos, Williams, Boobis, & Brooks, 1993) and uses a
lower ATP turnover rate. As such, while this could guard against a build-up
of fatiguing by-products (and sprint frequency/duration can be increased), it
would not be able to sustain power output (i.e. sprint performance).
RSA is greater when tested in conditions of hyperoxia (Charles et al.,
1996; Hogan, Kohin, Stary, & Hepple, 1999) or enhanced oxygen
availability (via erythropoietin injection) (Balsom, Ekblom, & Sjodin,
1994); the opposite is true when RSA is tested in hypoxic conditions
(Balsom, Gaitanos, Ekblom, & Sjodin, 1994). The consensus is that a
greater quantity of PCr at the start of each sprint would reduce the demand
on anaerobic glycolysis (and concomitant fatiguing by-products, e.g. H+
and Pi) and enhance ATP turnover (Glaister, Stone, Stewart, Hughes, &
Moir, 2005). Glaister (2005) concludes that the key role of the aerobic
system during repeated sprints is the return to homeostasis during rest. The
natural assumption is that increasing V̇O2max will increase recovery rates
and thus improve RSA. While there is little contention to this, it is worth
noting that there is probably an optimal value above which further increases
in RSA may not be noted (Bishop, Girard, & Mendez-Villanueva, 2011).
Section summary and non-chemical sources of fatigue
Sprint power is dictated by the amount and rate at which ATP is
resynthesised and then hydrolysed, and three mechanisms principally
contribute to ensuring that ATP is resynthesised as fast as it is hydrolysed.
These are: (1) the donation of a phosphate group from PCr; (2) substratelevel phosphorylation involving the breakdown of glycogen or glucose to
pyruvate; and (3) oxidative phosphorylation. The rate of hydrolysis is based
on the number of reactions required, while the ability to sustain ATP
turnover at fast rates is based on PCr availability and avoiding metabolic
by-product accumulation (e.g. Pi, H+). As sprint frequency increases, and
rest periods do not allow for sufficient recovery, ATP synthesis becomes
progressively supported by oxidative phosphorylation. While oxidative
phosphorylation allows for sustained work periods and repeated efforts, it
does so with reduced metabolic power and thus RSA declines.
It should be noted that declines in RSA are also related to additional
muscular and neurochemical factors not outlined above. These include
muscle excitability, whereby during intense contractions, the Na+–K+ pump
cannot effectively reaccumulate the K+ into muscle cells, with the
subsequent K+ efflux causing muscle membrane depolarisation, and thus
reduction of muscle excitability (Clausen, Nielsen, Harrison, Flatman, &
Overgaard, 1998). There may also be reductions to neural drive (i.e. a
decrease in recruitment, firing rate, or both) and a reduced cerebral function
owing to disturbances in neurotransmitter concentrations (e.g. serotonin,
dopamine, acetylcholine) (Ross, Leveritt, & Riek, 2001). Also, altered
muscle recruitment strategies, such as timing delays between agonist and
antagonist muscle activation – highlight a possible decrease in muscle
coactivation with fatigue (Hautier et al., 2000) – and a preferential
recruitment of slow-twitch motor units (Matsuura, Ogata, Yunoki, Arimitsu,
& Yano, 2006). There may also be changes in stiffness regulation, with the
negative effects of a more compliant system outlined in Chapter 3. Finally,
fatigue is likely to result from several homeostatic perturbations including
hyperthermia, dehydration and muscle damage.
Determinants of RSA performance
Most RSA studies cite V̇O2max as the major determinant of RSA
performance – no surprise given its role in PCr resysnthesis and the
contribution it makes as intervals extend. However, there are conflicting
findings regarding this relationship that appear largely attributable to the
RSA test used. For example, a moderate correlation (r = −0.35) between
V̇O2max and RSA was found when using 8 × 40-m sprints with 30 s of
active recovery between sprints (Aziz, Chia, & Teh, 2000), but not 6 × 20m sprints with 20 s of recovery between sprints (Aziz, Mukherjee, Chia, &
Teh, 2007). Bishop et al. (2004) utilised an RSA involving 5 × 6-s cycle
sprints, departing every 30 s, and found a relationship between RSA and
V̇O2max of r = 0.60. The discrepancies between these and others are
probably attributable to the length and frequency of the sprints used, as this
is likely to alter the contribution of the aerobic system (Balsom, Seger,
Sjodin, & Ekblom, 1992). In essence, V̇O2max has not been reported to
relate to RSA when only a few sprints of less than 40 m (or 6 s) have been
used (Da Silva, Guglielmo, & Bishop, 2010). Also, in protocols using a
W:R ≥ 1:5, sufficient recovery may be provided for the aerobic system to
resynthesise ATP and PCr despite inadequate fitness levels.
Unsurprisingly, RSA has also been found to strongly correlate with
peripheral factors (Spencer, Bishop, Dawson, & Goodman, 2005). For
example, Da Silva et al. (2010) showed that an RSA test consisting of 7 ×
35-m sprints (involving a change of direction) and a between-sprint
recovery period of 25 s produced high values of LT (15.4 ± 2.2 mmol/L).
Logically, then, Da Silva et al. (2010) found that the velocity at the onset of
blood LT accumulation (vOBLA) better correlated with RSA performance
(r = −0.49); vOBLA reflects peripheral training adaptations, such as
increased capillary density, the ability to resynthesise PCr and the capacity
to transport LT and H+ (Billat, Sirvent, Py, Koralsztein, & Mercier, 2003;
Thomas, Sirvent, Perrey, Raynaud, & Mercier, 2004). Therefore, to improve
RSA, it appears prudent not to only target the development of vOBLA, but
also the muscles’ buffer capacity. Several intervals of 30–60 s, with 1:1
W:R, may therefore be beneficial. Also, to enable the accumulation of H+,
passive recovery between intervals may be best.
Finally, Da Silva et al. (2010) (protocol aforementioned) and Pyne et al.
(2008) (using 6 × 30-m sprints with 20 s of rest) found that the strongest
predictor of RSA was actually anaerobic power, i.e. the fastest individual
sprint time; this explained 78% of the variance and had a relationship (r) of
0.66 respectively. These results suggest that in addition to training targeting
the improvement of V̇O2max, vOBLA and muscle buffer capacity, some
training should also focus on improving strength, power and sprint speed
(including acceleration). As well as traditional gym and track-based
sessions (outlined in Chapters 15 through 19), this may also need to include
single-repetition, all-out 30-s intervals, to maximally activate glycolytic
flux and thus adaptations in PFK and phosphorylase. The former
adaptations may be on account of increases in rate of force development,
stretch-shortening cycle mechanics, movement efficiency and also increases
in type II muscle fibre content. These fibres, which contain higher amounts
of PCr than type I (Sant’Ana Pereira, Sargeant, Rademaker, de Haan, & van
Mechelen, 1996), may be able to replenish ATP faster. However, this
advantage may diminish after several sprints as type I fibres have better
mitochondrial density and thus are better able to resynthesise PCr.
Furthermore, and as an additional caveat, enhanced initial sprint
performance via improved glycolytic flux may actually lead to increased
fatigue in subsequent sprints given the likely build-up of additional
fatiguing by-products. So this training intervention may need to be
supported by others aimed at increasing V̇O2max and buffer capacity, to truly
see it as a positive adaptation.
Training to improve RSA
As discussed above, RSA can be improved by increasing V̇O2max, vOBLA
and muscle buffer capacity, as well as strength, power and sprint speed.
Here we will focus on V̇O2max, vOBLA and muscle buffer capacity via
HIIT and SIT, as training for strength, power and sprint speed are discussed
in Chapters 15 through 19. Interestingly, with regard to aerobic capacity, a
series of meta-analyses show that HIIT and SIT are as effective, if not more
so, at increasing aerobic capacity when compared to moderate-intensity
continuous training (MICT) (Sloth, Sloth, Overgaard, & Dalgas, 2013; Gist,
Fedewa, Dishman, & Cureton, 2014; Weston, Taylor, Batterham, &
Hopkins, 2014; Milanović, Sporiš, & Weston, 2015; Taylor, Macpherson,
Spears, & Weston, 2015). These modes also better stimulate improvements
in muscle buffer capacity and thus vOBLA, as will be explored shortly.
According to Weston et al. (2014) and MacInnis and Gibala (2017), HIIT,
also referred to as aerobic interval training, is defined as ‘near-maximal’
efforts, generally performed at an intensity that elicits ≥80% (but often 85–
95%) of maximal heart rate, with bouts typically lasting up to ~5 min. SIT,
also referred to as anaerobic interval training or speed endurance training, is
characterised by efforts performed at intensities equal to or greater than the
pace that would elicit V̇O2max, including ‘all-out’ or ‘supramaximal’ efforts,
with bouts typically lasting ≤45 s. MICT describes exercise that is
performed in a continuous manner and at lower intensities than HIIT
(Figure 5.1). Below we will provide examples of some SIT and HIIT
protocols and associated findings, before exploring the physiological basis
of their underpinning mechanisms.
How modes of training differ between moderate-intensity continuous training
(MICT), high-intensity interval training (HIIT) and sprint interval training
(SIT). HR max, maximum heart rate; V̇O2max, maximal oxygen uptake.
As illustrated in Table 5.1, Gibala et al. (2006) compared SIT consisting
of 4–6 repetitions of 30-s work at ‘all-out’ supramaximal intensity (~700
W), with 4-min recovery, with MICT consisting of 90–120 min at ~175 W.
Both groups completed six training sessions over 14 days, accumulating a
total exercise duration of 135 min and 630 min respectively. Post-training,
both groups revealed significant improvements in 750-kJ time trial
performance, muscle buffer capacity and concentrations of various aerobic
enzymes (such as COX, which is an enzyme acting within the electron
transport chain), along with a concomitant decrease in muscle glycogen
utilisation – no significant differences were noted between groups. This
study was later repeated by Burgomaster et al. (2008), who compared SIT
consisting of 4–6 repetitions of 30-s work at ‘all-out’ supramaximal
intensity (~500 W), with 4-min recovery, with MICT consisting of 40–60
min at ~150 W. Both groups undertook training for 6 weeks, with the SIT
group training 3 times per week and the MICT 5 times per week. This
resulted in a total exercise duration of 90 min and 270 min respectively.
Post-training, both groups revealed significant improvements in aerobic
enzyme concentration, including citrate synthase (CS), which is an enzyme
that acts in the first step of the citric acid cycle, and β-HAD, which is an
enzyme involved in fatty acid metabolism. Furthermore, increases in PDH
concentrations and fat oxidation were noted, with concomitant decrease in
carbohydrate oxidation and muscle PCr utilisation. Of note, CS is
considered a proxy of mitochondrial content given its relationship with total
mitochondrial content assessed via electron microscopy. Finally, there was
again no significant difference between groups (Table 5.1).
Table 5.1
Group
Comparison of sprint interval training (SIT) vs. high-intensity interval training (HIIT)
vs. moderate-intensity continuous training (MICT) protocols on peripheral muscle
adaptations and central adaptations. Results reveal that adaptations across protocols are
similar, despite the large differences in total exercise time
MICT
SIT
HIIT
Adaptations
‘All-out sprint’ (~700
W)
Not tested
Both groups
significantly
improved:
Gibala et al. (2006)
Intensity
65% V̇O2max
(~175 W)
PCr, phosphocreatine; PGC-1α, proliferator-activated receptor y coactivator-1α.
Group
MICT
SIT
Protocol
90–120 min
continuous
exercise
30 s × 4–6 repeats, 4 min
recovery
Total
630 min over
duration
6 sessions
(across 2
weeks)
HIIT
Adaptations
Time trial
performance
Muscle
15 min (intervals) + 120
min (recovery) over 6
sessions (across 2
weeks)
buffer
capacity
Aerobic
enzyme
concentration
Fat oxidation
Glycogen
sparing
Burgomaster et al. (2008)
Intensity
65% V̇O2max
(~150 W)
‘All-out sprint’ (~500
W)
Not tested
Both groups
significantly
improved:
Aerobic
Protocol
40–60 min
continuous
exercise
30 s × 4–6 repeats, 4 min
recovery
enzyme
concentration
Fat oxidation
Glycogen
Total
270 min over
duration
30 sessions
(across 6
weeks)
sparing
10 min (intervals) + 80
min (recovery) over
18 sessions (across 6
weeks)
PCr
concentration
PGC-1α
protein
content
Matsuo et al. (2014)
Intensity
65% V̇O2max
120% V̇O2max
90% V̇O2max
PCr, phosphocreatine; PGC-1α, proliferator-activated receptor y coactivator-1α.
All groups
significantly
improved:
Group
MICT
SIT
HIIT
Adaptations
Protocol
40 min
continuous
exercise
30 s with 15 s rest,
repeated 7 times
3 min work, with 2
min rest at 50%
V̇O2max, repeated
3 times
40 sessions (across 5
weeks)
40 sessions (across 5
weeks)
V̇O2max
SIT and HIIT
groups
significantly
improved:
Total
40 sessions
duration
(across 5
weeks)
Left
ventricular
mass
Stroke
volume
Resting heart
rate
PCr, phosphocreatine; PGC-1α, proliferator-activated receptor y coactivator-1α.
Professor Ulrik Wisloff and colleagues developed a four-by-four HIIT
method that has proven popular and effective with soccer players and
Nordic skiers. While the physiological adaptations noted between SIT and
HIIT training are comparable, it appears that SIT predominantly drives
improvements in V̇O2max via increased oxidative capacity in the peripheral
muscles, while HIIT predominantly drives improvements in V̇O2max via
increases in stroke volume and blood flow (i.e. central factors) (Helgerud et
al., 2007; Matsuo et al., 2014). A comparison of the four-by-four HIIT
method with other work-matched methodologies is summarised in Table 5.2
(Helgerud et al., 2007). Also, and as described by Baker (2011), aerobic
fitness can be improved using a HIIT protocol consisting of 15-s intervals at
100–120% maximal aerobic speed (MAS), with a 1:1 W:R and continuing
for 5–10 min. Table 5.3 shows how to calculate interval distances from a 3km run, and how to organise these sessions within team sports. When
estimating MAS, any distance (or time) can be used but the athlete should
be working for >5 min (Baker, 2011). When training for a sport like boxing,
for example, it may be prudent to use these types of methods early on in the
periodised plan (to ensure an appropriate aerobic base), before progressing
the athletes towards shorter yet higher-intensity intervals that are more
specific to the sport. In sports such as football, and particularly for
midfielders where a high V̇O2max may be just as important as RSA, it may
be prudent to include these throughout the periodised plan.
Table 5.2
Effective training systems to enhance aerobic fitness
Training Protocol
group
Training
intensity
Pretraining
V˙O2max
(mL/kg/min)
Posttraining
V˙O2max
(mL/kg/min)
Long slow
distance
(LSD)
running
Low–
moderate
55.8 ± 6.6
56.8 ± 6.3
Lactate
Continuous run at lactate
threshold
threshold (85% HRmax) for
(LT)
24 min
running
Moderate–
high
59.6 ± 7.6
60.8 ± 7.1
15/15
interval
running
47 repetitions of 15-s intervals
at 90–95% HRmax with 15 s
of active resting periods at
warm-up velocity,
corresponding to 70%
HRmax between
High
60.5 ± 5.4
64.4 ± 4.4*
4 × 4-min
interval
running
4 × 4-min interval training at
90–95% HRmax with 3 min
of active resting periods at
70% HRmax between each
interval
High
55.5 ± 7.4
60.4 ± 7.3*
Continuous run at 70% HRmax
for 45 min
* Significantly (p < 0.001) different from pre- to post-training.
HRmax, maximum heart rate.
Table 5.3
Training
protocol
Interval distances for high-intensity interval training using maximal aerobic speed
(MAS), and calculated using a 1.5-mile run time of 10 min (Baker, 2011)
15-s intervals at 100–120% MAS
Work-to-rest ratio of 1:1
Repeat over 5 min using multiple sets as appropriate
Calculating
100% MAS
v = d/t
where v = velocity (m/s), d = distance (m) and t = time (s)
3 km = 3000 m; 12 min 30 s = 750 s
v = 3000/750 = 4 m/s
Calculating
interval
distance
If an athlete runs 4 m every second, then he/she will run 60 m in 15 s (4 × 15)
Calculating
120% MAS
1.2 × 100% MAS value, i.e., 4 m/s × 1.2 = 4.8 m/s
Notes on
shuttles and
variations
using agility
drills
A 30-m shuttle for example, i.e., out and back and covering 60 m, probably
represents 120% MAS as you must factor in the change of direction
Don’t
We do not recommend calculating lane distance for everyone in the group.
individualise
Instead, simply group runners based on 30-s intervals
too much
What does it
look like?
For example, group 1: 16 min (960 s) for 3 km run (MAS = 3.125 m/s), therefore
they run out and back 23 m (≈ 120% MAS given the turn), up to group 6: 10
min (600 s) for 3 km (MAS = 5 m/s) = 37.5 m out and back
What if you do
not have the
space?
Assuming only a 20-m shuttle is available: prior to the run (but within the 15 s),
athletes perform an exercise, the intensity of which is dependent on how short
the lane is. The exercise may be a series of tuck jumps or as simple as starting
from a prone position
The physiological basis for the peripheral muscle adaptations noted
through HIIT and SIT has been explained by MacInnis and Gibala (2017)
and Gibala (2020). These authors describe how exercise intensity mediates
mitochondrial biogenesis, with a greater metabolic signal for adaptation
occurring at higher intensities on account of the increased cellular stress. At
higher intensities, ATP turnover is greater, and this is supplemented by an
increase in the utilisation of glucose and glycogen, culminating in the
accumulation of intracellular LT, creatine, AMP and ADP. These metabolic
changes, and in particular low glycogen and the AMP:ATP ratio, increase
the activity of AMP activated protein kinase (AMPK; along with CaMKII,
which responds to elevated levels of cytosolic Ca2+ during muscle
contraction), which act as a ‘cellular energy gauge’. AMPK controls the
overall balance between energy production and energy utilisation in all
eukaryotic cells, with its activation tilting the balance towards energy
production. The greater the activation of these kinases, the greater the
expression of mRNA for proliferator-activated receptor y coactivator-1α
(PGC-1α).
To further demonstrate the intensity-dependent nature of these metabolic
signals (which are independent of volume) and subsequent adaptions, Di
Donato et al. (2014) also found that mitochondrial protein synthesis was
greater in response to continuous exercise performed at a higher intensity
relative to work-matched exercise performed at a lower intensity.
Understanding this cascade of cellular signals and reactions goes some way
to explaining the otherwise counterintuitive finding that high-intensity
exercise can be just as beneficial, if not more so, as the more traditional
mode of training aerobic capacity via moderate- to low-intensity,
continuous training. Furthermore, appreciating that low cellular energy
stimulates the activity of AMPK, which in turn drives mitochondrial
biogenesis via PGC-1α, provides some rationale behind the beneficial
results noted within several fasted or, rather, train-low paradigms (Bartlett,
Hawley, & Morton, 2015; Marquet et al., 2016). In these, athletes will
typically consume a low-carbohydrate meal prior to bedtime and then train
in the morning before breakfast. Training in such a glycogen-depleted state
will quickly activate AMPK. However, it should be noted that while this
may drive increases in mitochondrial protein synthesis, the enzyme PDH
will be down-regulated given the decreased metabolism of glycogen and
subsequently reduced accumulation of LT. As such, adaptations in this
enzyme – and by extension, vOBLA and muscle buffer capacity – would be
compromised. Therefore, in line with other modes of training, a variety of
HIIT and SIT protocols should be used; these can be further manipulated
via nutrition, and supported by strength and power training.
With regard to the central adaptations noted by SIT and HIIT, these have
been nicely detailed within the study of Matsuo et al. (2014). Through
cardiac magnetic resonance imaging (MRI) they revealed that an 8-week (5
times per week) SIT (30 s at 120% V̇O2max, with 15-s rest, repeated 7 times)
and HIIT (3 min at 85–90% V̇O2max, with 2-min rest at 50% V̇O2max,
repeated 3 times) intervention increased left ventricular mass, systolic
performance (ejection fraction) and thus stroke volume and resting heart
rate. (The results are illustrated in Table 5.1.) Furthermore, improvements in
the contractile performance of the cardiomyocyte through improved Ca2+
cycling were hypothesised. At the cellular level, Ca2+ has an important role
in the contraction–relaxation rates of the cardiomyocyte and it may be that
submaximal rather than maximal exercise intensity better stimulates
increasing Ca2+ sensitivity in the cardiomyocyte. These results may explain
that while there is generally no statistically significant difference between
SIT and HIIT protocols with regard to central adaptations (and noting the
large variation in protocols across the literature), HIIT tends to experience
slightly improved results when assessed via effect size analysis. In closing,
training approaches associated with HIIT, SIT and each energy system
discussed above are identified in Table 5.4.
Table 5.4
High-intensity interval training (HIIT) based on each energy system
Training
focus
Training plan
Rationale
Phosphocreatine
system
Gym-based strength and power
Track-based max. speed and acceleration
(SIT)
Repeated bouts (6–12) of 6–30 s, with
~60-s rest (SIT)
≥ 2-min intervals, separated by relatively
shorter rest periods, e.g. 1 min, and ≥ 4
reps (HIIT)
Increase initial sprint speed
May increase PCr stores by
virtue of increased type II
fibre concentration
Reduced effort through
increases in strength, power
(including RFD and SSC
mechanics) and technical
proficiency
Increases in aerobic capacity
and thus creatine shuttle
efficiency
Anaerobic
glycolysis
Maximal-intensity 30-s intervals, separated Maximally activate and thus
by 4–10 min to ensure subsequent
adapt key enzymes, e.g. PFK
intervals are again maximally utilising
and phosphorylase
anaerobic glycolytic enzymes (SIT)
Muscle buffer
capacity
Repeated bouts (~6) of 30–60-s intervals,
with work-to-rest ratio of 1:1. Utilise a
passive recovery (HIIT)
Increase and accumulation of
H+ and thus buffer capacity
Aerobic system
Longer-duration (≥ 2-min) intervals (at ~
V̇O2max), separated by relatively shorter
rest periods, and ≥ 4 reps (HIIT)
Improve PCr resynthesis via the
creatine shuttle,
mitochondrial biogenesis and
enhanced blood flow
SIT, sprint interval training; PCr, phosphocreatine; RFD, rate of force development; SSC, stretchshortening cycle; PFK, phosphofructokinase; H+, hydrogen ion.
Reporting results from RSA tests
It is important to judge the efficacy of any training intervention, and this
can be done by monitoring an athlete’s RSA over time. Once a drill has
been designed that replicates the sport and, importantly, requires athletes to
work at an intensity that represents (and even surpasses) a worst-case
scenario bout of play, there are considerations with regard to data analysis.
The method of data analysis for RSA testing should principally centre on
the following: (1) fastest sprint; (2) total or mean RSA time; or (3) the rate
of fatigue (or performance drop-off). The last factor can be reported by one
of two methods: (1) sprint decrement (Sdec) or (2) fatigue index (FI). The
formula for each, according to Spencer et al. (2005) is listed below in
equations 5.4 and 5.5, respectively. Unlike the FI, the Sdec takes into
account all sprints and is less influenced by a good or bad start or finish.
To improve reliability, Spencer et al. (2005) advise that, 5 min prior to
testing, athletes complete a single criterion sprint. During the subsequent
first sprint of the RSA test, athletes must achieve at least 95% of this score.
Should they fail, the test is terminated and restarted following another 5min break. While total (or mean) sprint time demonstrates good reliability
(CV < 3%), indices of fatigue give unacceptable levels of reliablility (CVs
11–50%); therefore we advise that the former should predominantly be used
(Spencer, Fitzsimons, & Dawson, 2006; Oliver, 2009).
Conclusion
It is the manipulation of exercise duration, frequency and rest period that
brings about specific adaptations to metabolic pathways. The results of
Balsom et al. (1994) provide a useful summary of this point. They found
that 40 × 15-m sprints (~2.5 s) with 30-s rest could be completed without
any reduction in performance. However, using the same rest period, 40 ×
30-m (~4.5 s) and 15 × 40-m (~6 s) sprint times increased significantly, and
after only the third 40-m sprint, times were already significantly longer.
Blood LT was also only elevated in the longer sprints. Although all sprint
combinations were matched for distance (i.e. each covered 600 m), each
emphasised a different energy system, with the final one presumably
incorporating the largest aerobic stimulus. Such (small) differences in HIIT
design can make all the difference to competition performance. Therefore,
when programming, strength and conditioning coaches need an
understanding of exercise biochemistry to ensure they are targeting the
appropriate energy system.
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6
Concurrent training
Rodrigo Aspe, Richard Clarke, Gareth Harris
and Jonathan Hughes
DOI: 10.4324/9781003044734-8
Introduction
Successful sports performance is multifaceted and includes optimal
preparation of skill, tactics, and physical qualities. Activities such as
marathon running and weightlifting have clear physical qualities at opposite
ends of a continuum. For example, a marathon runner requires excellent
aerobic capacity, with elite athletes typically demonstrating maximum
oxygen consumption (V̇O2max) values of 70–85 ml kg−1 min−1 (Joyner &
Coyle, 2008), while, in contrast, weightlifting necessitates high levels of
muscular force, and as a result, a greater cross-sectional area (CSA) of type
II muscle fibers (Aagaard et al., 2011; Fry et al., 2006). Therefore, the
amount of time dedicated to enhancing strength and power qualities by the
endurance athlete is markedly lower than that dedicated by the weightlifter,
just as the time dedicated to aerobic qualities is lower for the weightlifter
compared to the marathon runner.
Many sports require a range of physical qualities, including both
strength/power and aerobic capacity for optimal performance. For instance,
in a single rugby union match, it may be necessary for a player to accelerate
past their opponent in a line break (acceleration and power), ruck and maul
in offensive and defensive plays (muscular mass and strength), and cover
large distances tackling opponents throughout (aerobic capacity). Therefore,
training for rugby and many other team sports requires multiple physical
qualities, which often need to be developed concurrently (Chiwaridzo,
Ferguson, & Smits-Engelsman, 2016). Typically these qualities are
classified into two simple training paradigms, endurance and strength
training. Endurance training is commonly denoted by low–moderateintensity (∼70% V̇O2max) and high-volume training, which places greatest
demand on oxidative metabolism and promotes adaptations specific to
enhanced oxygen uptake and delivery, such as increased mitochondrial and
capillary density (Baar, 2014). In contrast, strength training is characterized
as high-intensity (≥80% one repetition maximum (1RM)) and low-volume,
and places greater demand on anaerobic metabolism and promotes
adaptations enhancing muscle CSA and neuromuscular efficiency to
enhance force production (Farup et al., 2012). Herein lies the concern, as
concurrent strength and endurance training promotes diverse physiological
adaptations (Nader, 2006). It is important that strength and conditioning
coaches and sport scientists have appropriate physiology knowledge to
optimize programming, and thus training adaptations. The aim of this
chapter is to discuss the adaptive response to concurrent exercise and
identify how periodization can minimize the interference effect of diverse
adaptations.
The interference effect
An interference effect has been reported when strength and endurance
exercises are performed concurrently (Hickson, 1980). The cause appears to
be linked to the differing physiological responses and adaptations to
strength and endurance training, possibly due to the high volume and long
duration that are often associated with endurance-based training (Wilson et
al., 2012). It is presumed that endurance exercise interferes with resistance
exercise sessions (via residual fatigue and/or substrate depletion) and
therefore blunts any muscular developments, e.g., muscle fiber-type
alterations and architectural adaptations (Leveritt & Abernethy, 1999;
Murlasits, Kneffel, & Thalib, 2018).
Neural development
It has been well documented that increases in maximal strength during the
initial weeks of strength training can be largely attributed to the increased
motor unit activation of the trained agonist muscles (Häkkinen et al., 1998;
Häkkinen, Kraemer, Newton, & Alen, 2001a; Häkkinen et al., 2001b). It
has also been demonstrated that strength training, performed concurrently
with endurance training, may have no detriment to neuromuscular
characteristics in elite endurance populations with no resistance-training
experience (Mikkola, Rusko, Nummela, Paavolainen, & Häkkinen, 2007;
Paavolainen, Häkkinen, Hamalainen, Nummela, & Rusko, 1999; Støren,
Helgerud, Stoa, & Hoff, 2008; Taipale et al., 2010) and recreationally
resistance-trained men (Jones, Howatson, Russell, & French, 2013).
Häkkinen et al. (2003) demonstrated that alongside large increases in
maximal force, there was an increase in the maximum integrated
electromyography (EMG) signal in the leg extensor muscles during a
concurrent training program lasting 21 weeks. Increases in EMG
amplitudes via strength training would result from an increased number of
active motor units and/or an increase in their rate coding (Sale, 1992).
However, there are conflicts in the literature, where an interference effect
has been demonstrated. It is purported to manifest as: (1) alterations in the
neural recruitment patterns of skeletal muscle (Chromiak & Mulvaney,
1990; Gergley, 2009); (2) limitations in force generation (Rhea et al., 2008;
Rønnestad, Hansen & Raastad, 2012); and (3) increased neuromuscular
fatigue from increased training demands of high-volume endurance training
(Davis, Wood, Andrews, Elkind, & Davis, 2008; Pattison, Drinkwater,
Bishop, Stepto & Fyfe, 2020). Interestingly, any impairments were less
evident in the early stages of training (first 4 weeks), which may indicate
that there is a progressive interference to neuromuscular function with
prolonged concurrent training periods (Pattison et al., 2020). These findings
have been supported via a meta-analysis that indicated that, whilst muscular
power increased, the magnitude of change was lower in concurrent-trained
groups (effect size (ES) = 0.55) than in strength-only trained groups (ES =
0.91) (Wilson et al., 2012). It is speculated that forces at high contraction
velocities, i.e., movements that need ‘explosive’ strength with high levels of
rate of force development (RFD), are affected more by endurance training
than force at low contraction velocities (Dudley & Djamil, 1985; Wilson et
al., 2012). Therefore, in sports that require explosive strength development
and/or maintenance, coupled with endurance capabilities, decrements in
muscular power may be likely and a result of impaired contraction velocity
or RFD (Häkkinen et al., 2003).
Muscular development
Following periods of concurrent training, skeletal muscle CSA has been
found to be depressed (Bell, Petersen, Wessel, Bagnall, & Quinney, 1991)
and, within the total CSA, it has been evidenced that individual muscle
fibers have hypertrophied to a lesser degree (Bell, Syrotuik, Martin,
Burnham, & Quinney, 2000; Kraemer et al., 1995). Mikkola et al. (2012)
postulate that, during bouts of concurrent training, optimal adaptation of
trained muscles to both strength- and endurance-training stimulus may not
be morphologically or metabolically possible. It has been theorized that an
increased catabolic state of skeletal muscle could lead to a reduced change
in the CSA (Bell et al., 2000; Kraemer et al., 1995). In support of this, it has
been discussed that there is a likely impact of testosterone and cortisol
interference due to mixed endocrine responses to training, where strength
training stimulates an increase in testosterone and prolonged endurance
training increases basal levels of circulating cortisol (Taipale & Häkkinen,
2013; Taipale et al., 2010). In addition, endurance training may decrease
muscle fiber size in order to accommodate increases in capillary and
mitochondrial density (Sale, MacDougall, Jacobs & Garner, 1990). This
may be due to the oxidative stress imposed on the muscle and the
requirement to optimize the kinetics of oxygen transfer because of the
additional endurance training (Häkkinen et al., 2003). Furthermore, a lack
of development in muscle CSA during concurrent training could be
attributed to overtraining induced by chronic muscle glycogen depletion
(down-regulating the signaling cascade required for protein accretion, as
well as reducing training performance) and an increase in catabolic
hormones (Mikkola et al., 2012). Further analysis demonstrates that
potential interferences to muscle hypertrophy during concurrent training are
more prominent when strength training is performed concurrently with
running compared to cycling (Wilson et al., 2012). This is likely explained
by greater levels of muscle damage in running (eccentric muscle action) and
thereby reducing the development of muscle tissue via competing demands
for tissue regeneration via the inflammatory process (Clarkson & Hubal,
2002; Wilson et al., 2012).
Molecular signaling
Excessive bouts of endurance exercise are known to reduce rates of protein
synthesis for several hours following the cessation of training (Rennie &
Tipton, 2000). Molecular signaling research has evidenced that during (and
following) endurance training the metabolic signaling pathways that are
linked to substrate depletion and calcium release and uptake into the
sarcoplasmic reticulum are activated (Coffey & Hawley, 2007). The
secondary messenger adenosine monophosphate-activated kinase (AMPK)
is activated, as its role is to increase mitochondrial function to enhance
aerobic capacity via the breakdown of glycogen and fatty acids to fuel
activity (Rose & Hargreaves, 2003). However, this activation inhibits the
mammalian target of rapamycin (mTOR), whose role is to mediate skeletal
muscle hypertrophy through up-regulation of protein synthesis via
activation of ribosome proteins (Bodine, 2006). Knowledge of this
signaling system informs us that conditions of low glycogen and high
concentrations of calcium and adenosine monophosphate (AMP) (as would
occur during aerobic training) would activate the AMPK pathway, thus
protein accretion (via the mTOR pathway) is significantly reduced (Figure
6.1). Therefore, strength training in a fatigued state may not be best
practice.
Putative adaptive pathways in response to the concurrent programming of
endurance and resistance exercises in a training program.
Cardiorespiratory development
There is empirical evidence that in elite endurance athletes, strength
training can lead to enhanced long-term (>30-minutes) and short-term (<15minutes) endurance capacity (Aagaard & Andersen, 2010). Investigations
into adaptations of cardiorespiratory function have indicated that there are
no differences in the magnitude of adaptation when endurance training is
completed in isolation or concurrently with strength training (Bell et al.,
2000; McCarthy, Pozniak, & Agre, 2002). The greatest impact on
cardiorespiratory adaptations arises when peripheral adaptations (e.g.,
capillary and mitochondrial density) are blunted. As the volume and
intensity of resistance training increase, competition for contractile protein
synthesis (promoting an increase in fiber size and muscle CSA) and an
increase in glycolytic enzymes exist (Docherty & Sporer, 2000). The more
recent focus on cardiorespiratory adaptations has investigated the acute
effects of concurrent training on oxidative metabolism (Alves et al., 2012;
Kang et al., 2009). Alves et al. (2012) did not observe differences in mean
values of V̇O2 or heart rate (HR) during endurance exercise performed prior
to or following a strength-training session. However, Kang et al. (2009)
demonstrated greater mean values for participants’ V̇O2 when endurance
exercise was performed following strength training compared with
endurance exercise only. There are a number of methodological differences
that can explain these results, i.e., intensity of endurance exercise, strength
exercises chosen, and populations used. The positive effects of strength
training for endurance athletes may occur independently of changes in
cardiorespiratory development (Paavolainen et al., 1999) and could be due
to improvements in RFD that aid improvements in exercise economy. An
improved force profile may augment RFD and the time required to produce
the desired force for each movement, reducing ground contact time (GCT)
(Hoff, Gran, & Helgerud, 2002; Paavolainen et al., 1999; Sedano, Marín,
Cuadrado, & Redondo, 2013). Moreover, an enhanced force profile can
augment the utilization of elastic energy in the muscle–tendon system,
decrease GCT, and reduce the demand on ATP production, thus improving
exercise economy (Wilson and Lichtwark, 2011).
Underlying all these proposed mechanisms, it may be that there is an
individual response that is coupled to an athlete’s training experience (Fyfe
& Loenneke, 2017). When comparing moderately trained athletes with
well-trained athletes, it has been evidenced that higher activation of
molecular mechanisms leading to both myofibrillar and mitochondrial
protein synthesis occurs in less-trained populations regardless of the
concurrent nature of the training (Nader, von Walden, Liu, Lindvall,
Gutmann, Pistilli & Gordon, 2014; Perry, Lally, Holloway, Heigenhauser,
Bonen & Spriet, 2010). This is attributed to the philosophy that, in lessdeveloped athletes, any stimuli may induce significant alterations to a cell’s
homeostasis and, therefore, lead to greater training-induced adaptations, and
that endurance-based athletes could be considered less developed in
strength parameters and therefore the interference effect is a reduced factor
in their training development.
Training strategies to minimize interference
Training periodization
Periodizing a training program (which should include the planning of all
tactical and technical training) for a sport that includes a range of physical
qualities and planning of multiple training units within a training day,
microcycle, and mesocycle, needs to be cautiously managed to minimize
the interference effect, as one training unit may inhibit adaptations to a
previous or subsequent training unit. In addition, the inclusion of training
units such as technical and tactical skills within the sport may provide
enough stimuli to maintain or enhance physical qualities and such training
stressors should be considered in the periodized plan to optimize fitness and
minimize fatigue (Issurin, 2010; Suarez-Arrones et al., 2014).
Wong et al. (2010) investigated a concurrent training program using
professional football players during an 8-week pre-season. Programming
prioritized 1RM half back squat and yo-yo intermittent recovery test
(YYIRT) performance, alongside sport-specific tactical and technical
training units. The experimental group completed twice-weekly strengthtraining units and 8 minutes of high-intensity running sessions (low
volume) on the same day, in addition to their normal 6–8-weekly soccertraining units. The control group completed their normal 6–8-weekly
soccer-training units. Results demonstrated significant improvements for
the experimental group in 1RM half back squat (+25 kg) and YYIRT (+298
m) but only the YYIRT (+137 m) for the control group.
Similarly, Enright et al. (2015) demonstrated half back squat 1RM
improvements during a 5-week in-season concurrent training program that
included strength training, soccer-specific endurance training, technical, and
tactical sessions. In this study design, all groups completed a concurrent
training protocol and sequencing was manipulated. Training groups either
completed strength–endurance or endurance–strength, separated by ~1 hour.
Regardless of sequence, both groups significantly improved half back squat
1RM by 10.3% and 19.1%, respectively. However, the more pronounced
changes and larger increase observed in the endurance–strength training
situation may suggest that the concurrent training sequence, in association
with adequate recovery duration between training bouts and nutrient
availability, may be able to modulate significant changes in physical
performance measures.
These applied research examples demonstrate minimal interference
effect and suggest that, within professional sport, both strength and aerobic
measures can be augmented with concurrent training programs over
prolonged periods.
With regard to maximizing strength-training adaptations for strengthand power-based athletes (contact sport), Appleby et al. (2012) assessed
strength over a 2-year period in professional rugby union players. Findings
indicate increases in strength are highly related to increases in lean body
mass and the magnitude of improvement is related to initial strength level.
However, the degree of strength improvement diminishes with increased
strength, training experience (4–7 years), and if athletes do not have the
capacity to increase lean body mass (Baker, 2013). Consequently, it is
important to recognize methodological differences in concurrent training
research. Comparing athletes with a low resistance-training age to welltrained strength athletes is unwise as the stimulus for adaptation is different.
Longitudinal research where strength-based athletes have participated in
concurrent training (Appleby et al., 2012; Baker, 2013; Stodden & Galitski,
2010) has typically dedicated specific training periods such as pre-season
(Appleby et al., 2012) or off-season (Stodden & Galitski, 2010) to
hypertrophy development and included a minimum of three resistancetraining sessions per week for this mesocycle. This form of block/emphasisbased periodization enables a large training stimulus to be applied to welltrained athletes. During in-season, training frequency is reduced to a
minimum of one session per week to maintain physiological adaptations
made in the pre- and off-season.
In the Appleby et al. (2012) and Stoden and Galitski (2010) studies,
1RM strength improved within year 1 and year 2, alongside the inclusion of
speed, agility, aerobic capacity, technical, and tactical training units. This
in-season reduction in strength-training frequency demonstrates wellthought-out programming with regard to concurrent training volume and
periodization. As such, there is no decrease in strength, which is a positive
outcome in this scenario (Baker, 2013). A review on the development,
retention, and decay of strength in trained athletes further confirms these
programming variables, suggesting that, to maintain strength, 1–2 training
units per week are required (McMaster, Gill, Cronin & McGuigan, 2013);
this low-frequency stimulus could be sufficient due to athletes undertaking
substantial doses of high/rapid force-generating activities during technical
and tactical training sessions. Interestingly, it also speculated that a
detraining period of 3 weeks has minimal effect on muscular strength
(McMaster et al., 2013). This provides valuable programming information
with regard to the duration of strength-training residuals and the potential
for programming adjustments, such as an opportunity to reduce resistancetraining volume and implement a tapering strategy, or increase training
volume to target another physical quality.
For successful periodization within sports where concurrent training is
required, it would be prudent to determine off-season and in-season periods
to establish specific training goals. Furthermore, determining pre-season
and in-season mesocycle goals would help focus programming and lessen
the interference effect of physiological adaptations of diverse physical
qualities. For example, Garcia-Pallares et al. (2009) demonstrated in elite
kayakers that strength and endurance qualities can be trained concurrently
with positive performance outcomes. The distinctive aspect of this research
was coupling hypertrophy training with aerobic training at 90% of V̇O2max
in the first mesocyle and strength training and maximal aerobic power
training (high-intensity aerobic training, between 90% and 100% of
V̇O2max) in the second mesocycle. The rationale for this was the
physiological adaptations expected, as hypertrophy (increase in contractile
proteins synthesis) and aerobic power training (increase in oxidative
capacity modulated by changes to oxidative enzymatic reactions) promote
opposing adaptations at a peripheral level (Garcia-Pallares et al., 2009).
Emphasizing fitness qualities in this manner has the potential to limit the
interference effect based on specific physiological adaptations. The use of
transition or detraining periods from strength-training units within
programming may also be beneficial as: (1) this period may enable
restoration and supercompensation; and (2) another training unit may be
prioritized without detrimental effects to strength (McMaster et al., 2013;
Sedano et al., 2013). Special attention should be considered in regard to the
type of sport; for example, contact sports may necessitate hypertrophy and
an increased frequency of resistance-training units whilst minimizing the
amount of aerobic training units completed.
Training session sequencing
One opportunity to manipulate training variables and reduce interference
may be through the sequencing of training units within a microcycle. In
programs that include both strength- and endurance-based training stimuli
in the same session, the training response may be different depending on
whether endurance or strength training is performed first. In a metaanalysis, Eddens et al. (2018) included ten studies directly comparing intrasession exercise sequence and the interference effect. Results identified that
performing resistance training first enhanced the improvement in lowerbody dynamic strength within prolonged concurrent training programs
(weighted mean difference, 6.91% change; 95% confidence interval (CI)
1.96–11.87 change; p = 0.006). Similar findings were also reported by
Murlasits et al. (2018), whose meta-analysis directly compared strength and
endurance-training sequence on performance measures and identified a
significantly different effect size of 3.96 kg (95% CI 0.81–.10 kg),
indicating the superiority of the strength-prior-to-endurance order.
Interestingly, Ratamess et al. (2016) demonstrated endurance training
performed 10 minutes before strength training resulted in 9.1–18.6% fewer
repetitions performed compared to strength training only. Therefore, it is
plausible that the order effect is explained by residual fatigue, with the
stress of the preceding endurance training acting to inhibit the quality of the
strength-training session.
Training recovery
Insufficient recovery between training sessions may limit the desired
adaptations from previous training. Residual fatigue from aerobic training
may reduce the quality of strength-training sessions by alterations in neural
recruitment patterns (Chromiak & Mulvaney, 1990; Gergley, 2009),
inhibiting force generation capacity (Rhea et al., 2008; Rønnestad et al.,
2012) or neuromuscular fatigue (Davis et al., 2008; Leveritt & Abernethy,
1999). For example, Robineau et al. (2016) concluded that strength and
power adaptations were inhibited unless at least 6 hours’ recovery was
allowed between training sessions (strength followed by high-intensity
endurance exercise); however, a 24-hour recovery period was superior to
further reduce interference. Furthermore, Sale et al. (1990) reported that
strength and endurance training performed on the same day (alternating
order) had no effect on muscle hypertrophy, but did cause a significant
reduction in strength development in untrained men compared to separateday training (approximately 24 hours’ rest). It is likely that increasing
recovery between sessions reduces the magnitude of the interference effect
as there is less disruption in post-training signaling pathways (Lundberg et
al., 2012) and an increased period for protein synthesis, restoration, and
opportunity to replenish fuel stores (Chtourou et al., 2014).
Further, the interference effect may also be increased when the same
muscle groups are utilized for strength- and endurance-based training
(Craig et al., 1991; Sporer & Wenger 2003). Sporer and Wenger (2003)
report that lower-body strength was significantly decreased for at least 8
hours after completion of a cycling submaximal aerobic training session (36
minutes’ cycling at 70% maximal power at V̇O2) and a cycling highintensity interval training session (3 minutes’ work and 3 minutes’ rest at
95–100% of maximal power at V̇O2), with no difference between groups at
any recovery time point. However, a meta-analysis, examining the
interference of aerobic and resistance training, suggests interference effects
are primarily body part-specific as performance decrements were found in
lower-, but not upper-, body exercise (Wilson et al., 2012). Therefore,
athletes who engage in multiple strength training units per week may
benefit from utilizing a split training routine where upper-body strength
training is completed on days that contain aerobic training sessions (given
these predominantly tax the legs).
Training intensity
It may also be important to consider endurance training intensity, as Chtara
et al. (2008) and Davis et al. (2008) reported that interference is more likely
to occur at aerobic training intensities close to maximal oxygen uptake.
Ratamess et al. (2016) investigated the acute response of strength
performance initiated 10 minutes after four different endurance (running)
protocols. These included: (1) continuous moderate intensity for 45
minutes; (2) continuous moderately high intensity for 20 minutes; (3) highintensity intervals for 15 minutes (with 15 minutes of low intensity in
between); and (4) continuous moderately high-intensity uphill for 20
minutes. Results demonstrated all endurance protocols observed a
significant strength-training performance deficit (repetitions) compared to
strength training only. Interestingly, protocol 3 (most intensive) led to the
greatest performance decrement followed by protocol 1 (most extensive).
With regard to longer-term research, Varela-Sanz et al. (2017) investigated
two matched-volume concurrent training protocols of different training
intensities for a duration of 8 weeks. Subjects were randomly allocated to
either: (1) a traditional training group who completed continuous running at
65–75% of maximal aerobic speed (MAS) and 10–12RM three times per
week, or (2) a polarized group that combined brisk walking of 35–40%
MAS and 15RM twice weekly; and brisk walking at 35–40% MAS, 15second intervals at 120% MAS and 5RM in the third session. Results
demonstrated similar strength and endurance improvements for both
groups; however, only the polarized group were able to maintain lowerbody explosive power by means of a jump test. In this regard, the results
suggest that the polarized distribution of training attenuates the interference
effect in respect to neuromuscular performance, which may be due to a
combination of factors such as a low weekly training frequency (4 rest days
per week) or superior programming related to employing low-intensity
brisk walking and reduced frequency of high-intensity training, thus
limiting fatigue. Interestingly, it has also been reported that high-intensity
aerobic training may minimize the interference effect due to the recruitment
of high-threshold motor units and a potential reduction in training volume.
For example, Wong et al. (2010) reported significant improvements in
strength, sprint speed, and aerobic performance after strength sessions were
utilized concurrently with high-intensity aerobic training (15:15 s at 120%
MAS and passive recovery). Notably, this training allowed for
approximately 5 hours between the morning strength session and the
afternoon high-intensity aerobic session, which may have also contributed
to the significant adaptations found; high-intensity interval training is
discussed further in Chapter 4.
Training frequency, volume, and mode
Optimal training frequency is also important as a number of studies
investigating concurrent training have reported varied conclusions on
whether endurance training attenuates strength and power adaptations
(Abernethy & Quigley, 1993; Craig et al., 1991; Hennessy & Watson, 1994;
Kraemer et al., 1995; McCarthy, Agre, Graf, Pozniak, & Vailas, 1995; Sale
et al., 1990). Jones et al. (2013) speculated that these differences may be
linked to endurance training frequency, as attenuated responses are more
often reported in studies utilizing a high (Craig et al., 1991; Hennessy &
Watson, 1994; Kraemer et al., 1995) vs. a low training frequency
(Abernethy & Quigley, 1993; McCarthy et al., 1995; Sale et al., 1990).
Jones et al. (2016) examined the effects of endurance training frequency in
a 6-week training intervention in which participants were randomly
assigned to one of four experimental conditions: (1) strength training only;
(2) concurrent strength and endurance training at a ratio of 3:1; (3)
concurrent strength and endurance training at a ratio of 1:1; or (4) a control.
Results demonstrated that an increase in the frequency of endurance
training and total training volume within the concurrent training paradigm
resulted in the attenuated development of lower-body strength when
compared with strength training alone. Moreover, earlier work from the
same research group demonstrated that recreationally trained men
completing high-frequency strength and muscular endurance training (both
3 × per week) resulted in lower strength and hypertrophy adaptations
compared to groups performing strength only (3 × per week) or lowfrequency strength and muscular endurance training (3 × strength and 1 ×
endurance per week) (Jones et al., 2013).
Subsequently, it may be important to evaluate the desired physiological
outcome and manipulate strength to endurance training ratio dependent on
the training goals. It seems prudent that if muscular strength or hypertrophy
is a priority, the frequency and ratio of endurance training should be low, as
endurance-training frequencies of greater than three times a week have been
shown to attenuate strength performance (Häkkinen et al., 2003; Izquierdo-
Gabarren et al., 2005; Jones et al., 2013, 2016; Kraemer et al., 1995). It
should be noted that methodological differences make comparing and
contrasting frequency research problematic due to manipulation of the acute
program variables and the amount of permutations available which mainly
affect training volume.
Wilson et al. (2012) produced a meta-analysis of concurrent training
studies that demonstrated negative significant and meaningful relationships
between endurance-training frequency, duration, and lower-body
adaptations in hypertrophy (r = −0.26; r = −0.75, respectively), strength (r
= −0.31; r = −0.34, respectively) and power (r = −0.35; r = −0.29,
respectively) indictaing an interfrenece effect. Whilst there were significant
negative relationships, the majority are weak and suggest minimal
interference effect for strength and power adaptations. Therefore,
prescription of training loads should be monitored, as when concurrent
training is necessary, the overall training load is likely to be higher, in both
frequency and duration, due to needing to meet this minimum-dose
response of two different fitness qualities (Figure 6.2).
The recommended decision-making process during periods of concurrent
training. SIT, sprint interval training.
Summary
In summary, the concurrent training research provides equivocal findings
on rate and magnitudes of adaptations (positive and negative in their
manifestation) across a number of physiological variables, including
strength, power, and cardiorespiratory functions. This wide range of
findings may be due to the wide range of acute program variables
contributing to the potential interference effect. Although it is not fully
understood, the research seems to support the concept that the interference
effect has its greatest effect on strength development (via hypertrophic
adaptations) and that the most likely mechanism of this interference is
linked to the molecular signaling activated from the type of training
undertaken. Athletes who require high levels of muscular strength and
hypertrophy, therefore, should endeavor to limit any long periods of
concurrent training.
During the planning of training, overall periodization, including
microcycles and mesocycles, needs to be cautiously managed to control
fatigue and minimize the interference effect (see Figure 6.1 for
recommendations). It would be prudent to determine off-season and inseason periods to establish specific training goals where as much focus can
be placed on a single training outcome as possible. It may also be optimum
to reduce the frequency of endurance training (and strongly consider total
accumulated fatigue) when hypertrophy adaptations are required. During
training cycles when concurrent training is unavoidable, it would be
sensible to consider the level of stimulus required of different modes of
training and determine a minimal dose–response. For example, detraining
or transition periods of up to 3 weeks from strength-training units may be
beneficial to allow supercompensation of other physical qualities, such as
speed and agility, to be prioritized.
Practical guidelines for concurrent training include: 24 hours of rest
between strength- and endurance-training units, though where this is not
possible, 6–8 hours would be sufficient. In addition, muscle recruitment and
mode of exercise should be considered, for example, where training
necessitates two training units in one day, upper-body strength could be
coupled with on-feet aerobic training. Alternatively, off-feet aerobic
training (cycling, rowing, and ski-erg) could be matched with lower-body
strength training to minimize extensive eccentric stress. In scenarios where
training sessions must be combined, and strength development is key, a
strength–endurance order should be used. Finally, to maximize strength
adaptations, two rest days should be provided and endurance training
frequency of less than three sessions per week is advised.
Applied training case study
Given the necessity for numerous elite sporting populations to develop
strength and aerobic capacity simultaneously, a significant demand has been
placed upon the practice of effective concurrent training methods. Working
within amateur or semi-professional sport this demand is even more
apparent due to varying external life commitments, e.g., employment,
especially those involving manual labor. Scheduling for appropriate
adaptations with little time available to train becomes a challenge;
therefore, there is a requirement to complete both strength and aerobic
capacity training within a single training session. In this applied training
case study, the population comes from an elite women’s rugby team in the
UK and their typical weekly in-season schedule can be seen in Table 6.1.
Table 6.1
Typical training week
Day
Combined sessions (semi-professional)
Monday
18:00–19:00
Upper-body strength
19:00–20:00
Off-feet conditioning
17:00–18:00
Lower-body strength
19:00–20:30
Combined conditioning + rugby
Tuesday
Wednesday
Active recovery
Thursday
17:00–18:00
Total body strength
19:00–20:30
Combined conditioning + rugby
Friday
Active recovery
Saturday
Game day
Sunday
Day off
Due to logistical constraints in the training environment (squad size, floor
space) this group of players were split into two training groups in one
continuous 120-minute session. One group performed resistance training
(RT) prior to aerobic capacity training (ACT), and the other group
performed ACT prior to RT. Session content for all players was the same
and training took place in-season three times per week. Table 6.2 provides
the programming variables used during an 8-week training block to provide
sufficient stimulus for the physiological adaptations required for
performance in their sport.
Table 6.2
Programming for concurrent training over an 8-week block
Training period
Weeks
1–3
4–6
7–8
Warm-up sets
2
3
3
Duration
3 min
3 min
3 min
Recovery
30 s
30 s
30 s
Sets upper body
3
3
3
Sets lower body
3
3
3
Repetitions
10
6
3
Intensity (% 1RM)
70%
80%
90%
Recovery
2 min
3 min
3 min
Repetitions plyometrics
6
6
6
Repetitions hamstrings
6
6
6
Short intervals
2 × 8 min of 30/30 s
2 × 10 min of 30/30 s
2 × 12 min of 30/30 s
Sprint intervals
4 × 30 s all-out
6 × 30 s all-out
8 × 30 s all-out
RT workload
Main exercise
Complementary exercise
Act workload
RT, resistance training; 1RM, one repetition maximum.
Resistance-training design
Every session began with a warm-up focused on movement skills. Strength
training included exercises of the lower body (squat, deadlift, and lunges)
and upper body (bench press, chin up, and bent-over row) (Table 6.2).
Training was divided into three periods, during which the intensity
progressively increased. The first period (weeks 1–3) aimed to prepare
participants for maximal-strength training. The second period (weeks 4–6)
and the third period (weeks 7–8) were designed to increase maximal
strength (Table 6.2). Each set of squats was immediately followed by
plyometric jumps. Exercises were alternated during each training session,
alternating lower- and upper-body exercises. Players were free to change
weight during the training period in order to achieve the programmed
repetitions.
Aerobic capacity training design
Two different ACT sessions were performed outside on an artificial pitch. A
specific 15-minute warm-up, consisting of moderate, cruising, and sprinting
runs, preceded each aerobic training session. The first consisted of short
intervals and included two sets of interval running. Players would alternate
30-s runs at 100% of their individual MAS with 30 s of active recovery at
50% MAS, where MAS was obtained from a 1200-m test. The second
sprint interval included repetition of 30-s running all-out efforts with 4 min
of passive recovery.
Table 6.3
Mean (± SD) values for performance measures conducted in elite women’s rugby
players pre- and post-8 weeks of concurrent training interventions
Performance test
Squat 1RM (kg)
Bench press 1RM (kg)
Maximal aerobic speed (m/s)
Pre
Post
% Change
RT-ACT group
93.1 (15.3)
98.5 (14.2)*
5.5%
ACT-RT group
97.5 (21.2)
101.5 (18.6)*
4.1%
RT-ACT group
61.0 (12.9)
65.0 (12.8)*
6.5%
ACT-RT group
60.7 (21.7)
63.1 (22.0)*
4.0%
RT-ACT group
3.5 (0.4)
3.7 (0.4)*
5.7%
ACT-RT group
3.5 (0.4)
3.7 (0.5)*
5.7%
* Denotes a significant difference compared to baseline (p < 0.05).
1RM, one repetition maximum; RT-ACT, resistance training–aerobic capacity training; ACT-RT,
aerobic capacity training–resistance training.
Player-monitoring data (Table 6.3) highlight that, despite having to
schedule the team into differing orders of concurrent training, they all
demonstrated large positive adaptations in both strength and aerobic
capacities over an 8-week block. From this applied training case study it is
clear that the sequence in which concurrent training is performed within a
120-min training session has minimal impact on the player’s physiological
development. We can, however, highlight from this applied example that
the greater improvements seen in the RT–ACT group are in line with
concurrent training recommendations in relation to training order and
weekly rest days.
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Part II
Programming and monitoring for
your athlete
7
Periodisation
Shyam Chavda, Anthony N. Turner and Paul
Comfort
DOI: 10.4324/9781003044734-10
Introduction
Periodisation (also referred to as phase potentiation) is regarded as a
superior method for developing an athlete’s performance (Haff, 2004a,
2004b; Stone et al., 1999a, 1999b, 2000). However, because peak
performance can only be maintained for 2–3 weeks (Stone, Stone, & Sands,
2007), the ability to phase training appropriately to ensure that the athlete’s
peak level of performance coincides with a competition date long into the
future (e.g. the Olympics, or key matches in team sports) is a skill
fundamental to all strength and conditioning (S&C) coaches. Such levels of
performance may only be attained following the appropriate application of
periodisation, whereby a calculated manipulation of training parameters
(e.g. frequency, intensity, duration, volume, exercise selection) ensures
optimal adaptations and minimal fatigue at the point of competition.
Despite an apparent lack of scientific rigour to govern its application (Kiely,
2018), periodisation is widely practised (Durell, Puyol, & Barnes, 2003;
Ebben & Blackard, 2001; Ebben, Carroll, & Simenz, 2004; Simenz, Dugan,
& Ebben, 2005) and recommended (Haff, 2004a, 2004b; Plisk & Stone,
2003).
As training is multifaceted in nature, it is important to understand that
athletes are committed to a process which prepares them not just physically,
but technically, tactically and psychologically, to enable them to achieve
high levels of performance in their sport (Stone, Stone, & Sands 2007).
Although the primary focus of this chapter is the physical preparation of the
athlete, when designing a periodised programme, a holistic approach must
ensue to account for the compounding effect of fatigue and overall stress
experienced by the athlete. This will require a multidisciplinary approach of
technical and tactical coaches working alongside sport scientists and
athletes, to help appropriately structure training cycles to align and
therefore optimise the primary focus of training for that period. Once this
overarching approach is taken, the distribution of training (i.e. gym-based
training, on-pitch training, etc.) (Figure 7.1) can be programmed
appropriately so as to ensure the distribution of mode and training is
appropriate to elicit the desired effects.
(a) Distribution of training load; (b) distribution of training modes in
Olympic fencers. (Adapted from Turner et al., 2015.)
We should also note that the science and practice of periodisation are
largely based on hypothesis-generating studies, anecdotal evidence and
related research, with most studies only being short-term experimental
periods (e.g. 5–16 weeks) using subjects with limited training experience
(Kiely, 2018). However, despite these challenges to an evidence-based
ideology, there is enough anecdotal evidence, case study reports and
empirically similar research to advocate its use across all population groups.
Therefore, the aim of this chapter is to provide the S&C coach with a
detailed overview of periodisation so that they may be cognisant of its
theory and methodology. It is hoped that this will further facilitate its
implementation and successful application.
Defining periodisation
It is often perceived that periodisation and programming are one and the
same. This misconception can lead to potential confusion and inconsistency
in communication between S&C coaches and therefore the differences
between the two need to be addressed. Periodisation may be defined as a
macromanagement of strategically aligned phases of training, whereby peak
performance is brought about through the potentiation of biomotors and the
management of fatigue and accommodation. This is governed by the
prescription of training frequency, exercise selection and order, intensity,
sets and repetitions (Cunanan et al., 2018a; DeWeese et al., 2015). These
constituent parts make up a programme, which, when appropriately
organised, should present an identifiable pattern based on the intended
objectives of the training phase (Cunanan et al., 2018a). The logical
manipulation of these variables will often display as an inverse relationship
between volume and intensity (volume load) (Figure 7.2), with the only
notable exceptions being during periods of planned overreaching (discussed
later). More recently, researchers have identified that manipulating training
load via cluster sets (Tufano et al., 2016, 2017a, 2017b) and higher-volume
(sets) powerlifting protocols (Schoenfeld et al., 2014) may also permit
higher volumes of training at higher intensities. (For a detailed review of
the use of cluster sets, see Chapter 13.) However, careful implementation of
such strategies should be considered, preferably away from competition, to
ensure that the higher training volumes do not negatively impact
performance due to the associated increase in fatigue.
Relationship between volume, intensity and training specificity over the
three main phases of training. GPT, general physical training; SSPT, sportspecific physical training; Comp, competition.
Plisk and Stone (2003) suggest that periodisation should be applied on a
cyclic or periodic basis, structured into macro-, meso- and microcycles, that
progress from extensive to intensive workloads. These cycles are often
defined by their allotted period of time, with a macrocycle typically
referring to a year, a mesocycle (each period/phase of focused training) 2–8
weeks, dependent on the competition schedule and a microcycle 1 day to 1
week (Figure 7.3). There is, however, large variability in the time course of
each, with, for example, macrocycles running 4 years in the case of
Olympic training programmes (quadrennial plan). Also, mesocycles are
often divided into 4 ± 2-week blocks as this appears to provide the optimal
time frame for adaptation in well-trained athletes (Matveyev, 1977; Plisk &
Stone, 2003; Stone, Stone, & Sands, 2007; Zatsiorsky & Kraemer, 2006).
Basic components of a periodised plan. GPT, general physical training;
SSPT, sport-specific physical training. (Adapted from Naclerio, Moody, and
Chapman, 2013.)
Periodisation is also often defined by its progression from general to
special tasks (Figure 7.2), whereby there is a conscious incorporation of
technique/sport-specific biomotors as the programme progresses and
competition nears. It is important to note that, in terms of sport specificity,
this refers to training, which results in adaptations that achieve specific, preestablished goals, and not mimicking the movements of sporting tasks.
Bompa and Haff (2009) also report three major phases of periodisation: the
preparatory phase, the competitive phase and the transition phase. In
addition, the preparatory phase has two sub-phases: general physical
training (GPT) and sport-specific physical training (SSPT) (Table 7.1). The
objective of the GPT is to improve the athlete’s work capacity and
maximise adaptations in preparation for future workloads (Graham, 2002).
This may typically be used in the off- or pre-season, where there are limited
skill-based sessions, therefore allowing for higher workloads and optimal
recovery. The importance of this phase is highlighted by Zatsiorsky and
Kraemer (2006), who use the analogy “soon ripe, soon rotten”. Along with
data from Fry, Webber, et al. (2000) and Stone et al. (2007), this suggests
that the average training intensity is inversely correlated with: (1) the time a
performance peak can be maintained; (2) the height of that performance
peak; and (3) the rate of detraining (Figure 7.4).
Table 7.1
The main phases and sub-phases of periodisation
Training
phase
Preparatory phase
GPT
SSPT
Phase
objective
• ↑ Work (aerobic and
anaerobic) capacity
• ↑ Neuromuscular
functioning
• Refine technique
• Develop sport-specific
biomotor ability
• Develop sport-specific
energy metabolism
GPT, general physical training; SSPT, sport-specific physical training.
Competitive
phase
Maintain biomotor
conditioning
Soon ripe, soon rotten. Training intensity is inversely correlated with: (1) the
time a performance peak can be maintained; (2) the height of that
performance peak; and (3) the rate of detraining. (Adapted from Stone et al.,
2007.)
The SSPT serves as a transition into the competitive phase, whereby
physical capacity is developed specific to the physiological profile of the
sport and where sport-specific biomotors are perfected. During the
competitive phase, the work capacity developed during the SSPT should be
maintained as a minimum objective. However, in team sports with regular
competition and extended competition phases, mesocycles may be
attributed to maintenance of some attributes and development of others.
This phased approach is also essential to ensure that the desired muscular
adaptations occur, as strength and power training result in different
architectural adaptations (discussed in detail in Chapter 2).
Following the SSPT, Bompa and Haff (2009) also presented the
transition phase (TP), which provides a period of restitution between
macrocycles or intense mesocycles. This phase serves as an opportunity for
athletes to actively rest and partake in recreational activity, complementary
to the movement patterns and motor skills experienced in their primary
sport (Haff, 2004a). The length of this phase and the number of times it is
used within a macrocycle will be dependent on the structure of the
periodised plan and the number of competitive phases the athlete will
partake in. For example, an athlete competing in weightlifting may only
have three major competitions in a year (i.e. regional qualifier, nationals
and an international). Therefore, following each competition phase, the
athlete will undergo a transition to allow for recovery, with each phase
lasting between 2 and 6 weeks, with longer transitions following the most
intense period of preparation and competition (i.e. following the
international competition). This momentary withdrawal from specific
training stressors coincides with Selye’s general adaptation syndrome
(GAS) model, in which he states that stress reactions are well tolerated for
short periods, although persistent long periods of stress are likely to cause
complications and therefore it is beneficial to withdraw stress (Cunanan et
al., 2018a). Given that stress is multifaceted, this phase provides
opportunity for both physiological and psychological restitution for the
athlete.
Recovery and adaptation
The foundation of periodisation is governed by the management of stress.
Stress is multifaceted in nature and therefore factors other than physical
stress brought about by training must also be considered when designing a
periodised plan (Kiely, 2018). If stress is compounded by external pyschoemotional factors experienced by the athlete, a significant reduction in
recovery and adaptation may present itself. For example, dual-career
athletes such as students will have added academic stress (i.e. examinations
and coursework), which may affect their readiness to train and increase
injury potential (Mann et al., 2016) during periods of demanding physical
training or high competition loads. Furthermore, their perception of the
training task may also be altered during periods of high pyscho-emotional
stress and therefore influence fitness adaptations based on the imposed
training stressor (Kiely, 2018). As S&C coaches, it is important to factor in
periods of external stress and accommodate this within the loading
paradigms used within a meso- and microcycle.
Mesocycle blocks are usually arranged in a 3:1 loading paradigm (Figure
7.5), whereby the load (volume or intensity depending on the goals of the
phase) gradually increases for the first three microcycles (weeks) before an
unloading phase in the fourth (creating the typical undulating appearance of
periodised programmes). The unloading phase reduces accumulated fatigue,
thereby allowing adaptations to manifest (Haff, 2004a, 2004b; Plisk &
Stone, 2003). The importance of appropriately planned work-to-rest ratios
(with respect to training sessions) should be noted, with Plisk and Stone
(2003) suggesting that the greater the number of progressive loading steps,
the greater the number of unloading steps required, e.g. a 6:2 paradigm.
Since the majority of training adaptations take place during recovery
periods (Haff, 2004a), the need to reduce accumulated fatigue to facilitate
the adaptation processes cannot be understated.
The 3:1 loading paradigm, illustrating the increase and then dissipation of
excessive fatigue.
The importance of recovery phases for the purposes of adaptation is well
established (Haff, 2004a, 2004b). The S&C coach must therefore ensure
that work-to-rest ratios are appropriately planned (e.g. utilising the 3:1 step
loading paradigm) to avoid excessive fatigue and a reduced stimulus for
adaptation. According to Stone et al. (2007), this trade-off is described by
three principal theories: (1) Seyle’s GAS; (2) stimulus–fatigue–recovery–
adaptation (SFRA) theory; and (3) the fitness–fatigue (fit–fat) theory.
General adaptation syndrome
The GAS paradigm describes the body’s physiological response to stress,
which, according to Selye (1956), is the same despite the stressor. The GAS
model assumes three distinct phases during stress, which, for the following
example, will be an exercise-training session. The alarm phase (phase 1)
represents the recognition and initial response to the session. This may be in
the form of fatigue, stiffness or delayed-onset muscle soreness, for example.
The resistance phase (phase 2) is then initiated, in which the body is
returned to either its pre-exercise session homeostasis or its new adapted
higher state (i.e. supercompensation occurs). Finally, and assuming the
accumulation of stress is too great (e.g. the absence of an unloading week),
the exhaustion phase (phase 3) occurs and may be considered synonymous
with overtraining if it continues over a prolonged period (Stone, Stone, &
Sands, 2007). The GAS model is depicted in Figure 7.6.
The general adaptation syndrome (GAS) model.
While GAS is the main underlying foundation on which periodisation
and the pursuit for adaptation are founded, some resistance towards its
application within sport has been raised (Buckner et al., 2017, 2018; Kiely
2018). The main argument exists that the original work by Hans Selye
focused on a pathological stress response induced by pharmaceutical
implementation and exercise in rodents, therefore raising the issue of
whether Selye’s experimental data can be related to resistance exercise in
humans (Buckner et al., 2018). It has been refuted as to whether the training
stressors experienced by athletes are indeed sufficient enough to cause an
alarm phase in which adaptation becomes a response (Buckner et al., 2018),
and therefore questions whether a periodised approach to programming is
more beneficial than a non-periodised approach (Buckner et al., 2017). In
addition, the lack of empirical evidence supporting the application of the
GAS model during training has been raised (Buckner et al., 2018). While
these are plausible arguments, Cunanan and colleagues (2018a, 2018b)
uphold a strong rationale as to why the application of GAS can help S&C
coaches develop highly efficient periodised programmes. Much of the
support behind the broad application of the GAS model and its use within
periodisation comes from the culmination of both experimental data (albeit
somewhat limited in elite athletes) and supporting literature, in addition to
anecdotal practice from coaches (Cunanan et al., 2018a, 2018b). Cunanan
and colleagues coherently discuss the applicability of GAS, highlighting
that: (1) GAS provides a mechanistic and conceptual model to help
understand the relationship between stress, adaptation and fatigue, as
experienced by athletes; and (2) Selye’s original work highlighted the need
for periodicity due to the cyclic stress–recovery response, implying that
training (i.e. resistance training) would also require planned variation and
recovery.
Stimulus–fatigue–recovery–adaptation theory
The SFRA concept (Verkhoshansky, 1979, 1981, 1988) suggests that
fatigue accumulates in proportion to the magnitude and duration of a
stimulus. Then, following the stimulus (e.g. an exercise session), the body
is rested, enabling fatigue to dissipate and adaptations (often referred to as
supercompensation) to occur. This concept also suggests that if the stress is
not applied with sufficient frequency (also known as density), detraining
(also known as involution) will occur. It is also important to note that if
competition frequency is high, then training frequency will have to reduce
to permit appropriate recovery. Moreover, involution time is influenced by
the length of the preparation period (Stone, Stone, & Sands, 2007), with
greater training programme duration increasing the duration of the residual
effects (Figure 7.4) (Zatsiorsky & Kraemer, 2006). In addition, and by
virtue of this, the duration of subsequent preparation phases can
progressively decrease. The importance of preparation has been previously
discussed within this chapter. The SFRA concept is illustrated in Figure 7.7.
The stimulus–fatigue–recovery–adaptation (SFRA) concept.
The SFRA concept is also used to describe the supercompensation observed
following periods of planned overreaching (Verkhoshansky, 1981, 1988).
For example, the accumulation of fatigue from the sequential execution of
similar training sessions (i.e. a concentrated, primarily unidirectional
loading of, for example, strength/power training), usually with a
progressive increase in volume, is superimposed on one another. This leads
to excessive fatigue and acutely (~4 weeks) diminished strength and power
capabilities. However, following the return to normal training, or a “deload” period (and by virtue of a delayed training effect phenomenon), they
then rebound beyond their initial values (Fry, Webber, Weiss, Fry, & Li,
2000; Stone & Fry, 1998). This strategy, however, is reserved for elite-level
athletes whose window for adaptation is small and therefore requires more
intense interventions to bring about a supercompensation response (Bompa
& Haff, 2009). Planned overreaching strategies are briefly discussed later in
this chapter.
Fitness–fatigue paradigm
Currently, this is the most prevailing theory of training and adaptation (Chiu
& Barnes, 2003; Plisk & Stone, 2003; Zatsiorsky & Kraemer, 2006) and is
considered the basic tenet of a taper (discussed later in this chapter) (Mujika
& Padilla, 2003). According to this paradigm, athlete preparedness may be
evaluated based on the main after-effects of training: fitness and fatigue
(Zatsiorsky & Kraemer, 2006). Unlike the GAS and SFRA concept, which
assumes fitness and fatigue share a cause-and-effect relationship, the fit–fat
model suggests they demonstrate an inverse relationship. This implies that
strategies that maximise fitness and minimise fatigue will have the greatest
potential to optimise athlete preparedness (Stone, Stone, & Sands, 2007).
The fit–fat concept is illustrated in Figure 7.8.
The fitness–fatigue paradigm.
An additional key difference between the fit–fat concept and the
aforementioned models is that it differentiates between the actions of
various stressors, such as neuromuscular and metabolic stress (Chiu &
Barnes, 2003), implying that the after-effects of fitness and fatigue are
exercise-specific (Stone, Stone, & Sands, 2007; Zatsiorsky & Kraemer,
2006). This suggests that if the athlete is too tired to repeat the same
exercise with acceptable quality, they may still be able to perform an
alternative exercise to satisfaction (Figure 7.9), which also aids in reducing
monotony for athletes. This, for example, provides the basic tenet to
hypertrophy programmes incorporating 3–5-day splits and concurrent
training involving both aerobic and resistance workouts.
Athlete preparedness based on the specific form of fatigue. (Adapted from
Zatsiorsky and Kraemer, 2006.)
Training monotony
The lack of “change” associated with monotonous training volume,
intensity or mode can predispose an athlete to stagnation (Stone et al., 1991;
Zatsiorsky & Kraemer, 2006). Also, as described by the principle of
diminishing returns (Zatsiorsky & Kraemer, 2006), as an athlete improves,
in whichever attribute they are developing, the room for adaptation
decreases and therefore so does the rate of adaptation (Figure 7.10). It is
therefore of utmost importance to incorporate variability within the design
of periodised S&C plans, and this serves as the rationale for the regular
application of novel and semi-novel tasks (exercise deletion and
representation) (Stone, Stone, & Sands, 2007); Table 7.2 illustrates how this
may be incorporated within a periodised plan. As a word of caution,
however: too much variability can reduce the opportunity for the body to
adapt to a given stimulus and reduce the development of skill acquisition
(Bompa & Haff, 2009).
The principle of diminishing returns.
Table 7.2
Exercise deletion and representation
Mesocycle 1
2
3
Example 1
Exercise
Countermovement
jump (CMJ)
Delete CMJ from
programme; replace
with drop jump
Reintroduce
CMJ into
programme
Example 2
Exercise
Depth jump (clear
flexion/extension of
joints, prolonged
ground contact time
[GCT])
Delete depth jump and
replace with drop jump
(reduced
flexion/extension of
joints, short GCT [<250
ms])
Reintroduce
depth jump
into
programme
Application of periodisation
Basic model of periodisation
The type of periodised model used should reflect the S&C training age of
the athlete and not their competition age or rank. It is considered prudent
therefore to initiate S&C programmes with basic periodised models. These
generally entail little variation and relatively flat workloads (Stone, Stone,
& Sands, 2007), with the main emphasis being on the logical and thus
potentiated progression of biomotors (e.g. strength-endurance → strength
→ power). Figure 7.11 illustrates a basic model.
Basic model of periodisation entailing little variation and relatively flat
workloads.
As an example of this basic strategy, the athlete completes a
hypertrophy/strength-endurance phase for 6 microcycles (i.e. 6 weeks or
one mesocycle), a strength phase for 4 microcycles and then a power phase
for 4 microcycles (Table 7.3). Note that the strength-endurance phase is
longest in duration; this is because volume is considered a key stimulus for
hypertrophy, which will also help to increase work capacity, ready for the
subsequent phases. It also provides the athlete with more time to master the
various movements required of the following phases. Each phase
(dependent on the prescribed volume loads) may be further separated by an
unloading week, as may happen following the power phase and before the
competition. In addition, higher- and lower-volume days may also be
prescribed where there is a notable change in intensity, therefore altering the
stimulus for strength adaptation. This strategy, considered appropriate for
athletes with a low S&C training age, introduces them to S&C (i.e. its
merits and the discipline required) and periodisation (i.e. the need to
systematically alter the emphasised biomotors and a quality-over-quantity
approach) and enables them to get a “feel” for gym-based training
interventions as well as developing their associated technique. As a final
note on this basic model (which is actually applicable to all models), to
ensure athletes get the most out of each phase, the S&C coach should
ensure they are technically sound to perform the exercise of each phase
before progressing on to it. For example, power cleans and snatches may be
part of the power phase; however, the athlete may have to start practising
and developing them, along with their derivatives, in the strength-endurance
phase and maintain them in the strength phase. In the strength-endurance
phase, cluster sets might be used, for example, to ensure maintenance of
technique and velocity. (See Chapter 13 for a detailed discussion of the
implementation of cluster sets.) In the strength phase, weightlifting pulling
derivatives using loads ≥ 100% one repetition maximum (1RM) power
clean might be used, as force production is key to their effective use during
the power phase (see Chapter 16) (Suchomel, Comfort, and Lake, 2017;
Suchomel, Comfort, and Stone, 2015).
Table 7.3
Example sessions used as part of a basic periodised model
Example
Example
Example power session
hypertrophy session strength session
3 × 8–15 @ 60–75%
1RM, working toward
MMF, < 3 min between
sets and exercises
4 × 4 @ 4–6RM
(~85–90% 1RM),
> 3 min between
sets and exercises
Exercises: Squats, Romanian deadlift,
bench press, pull-ups.
Weightlifting and plyometric
techniques may be developed as
part of the warm-up
Intensity: 5 × 3 @ variable loads (see below),
> 3 min between sets and exercises
Exercises: clean (70–90% RM), jump squats
(0–50% 1RM), plyometrics (body mass)
and medicine ball throws. Strength may be
maintained with 3 × 3 squats @ 85–90%
1RM.
Volume load presented as sets × repetitions × load.
1RM, one repetition maximum; MMF, momentary muscle failure.
Intermediate model of periodisation
As the athlete’s S&C age advances and adaptations begin to plateau, greater
variability becomes paramount. In addition, due to the enhanced work
capacity of the athlete, greater volume loads are undertaken, thus the need
for planned recovery sessions. The periodised programme begins to evolve
into wave-like increases in volume loads (Matveyev, 1972, 1977) that
typically fluctuate at the microcyclic level (Stone et al., 1999a, 1999b). This
is referred to as summated microcycles and is usually represented as the 3:1
paradigm previously discussed. In addition, and due to the need to
incorporate variability, each microcycle can incorporate multiple biomotors
(e.g. strength, power and speed work), some for the purpose of maintenance
and potentiation, and others for the purpose of development and adaptation.
Additional methods of incorporating variability and thus adaptation include
inter-session variability (e.g. heavy/high-volume and light/lower-volume
days and exercise deletion and re-presentation methods) and intra-session
variability (e.g. cluster sets and post-activation performance enhancement
protocols). Figure 7.12 illustrates this traditional approach to designing
periodised programmes, which is attributed to Matveyev (1972, 1977). An
example intermediate periodised programme is illustrated in Table 7.4.
The traditional, undulating approach to the design of periodised training,
which is attributed to the work of Matveyev (1977). Note the 3:1 loading
method within each mesocycle.
Table 7.4
Two example strength sessions and two example power sessions, which can be
implemented as part of an intermediate periodised programme
Strength
session 1
Strength
session 2
Power session 1
Power session 2
Volume load presented as sets × repetitions × load.
* Used to develop/maintain technique and strength/power; 1RM, one repetition maximum; CMJ,
countermovement jump; NHC = Nordic hamstring curls.
Strength
session 1
Strength
session 2
Power session 1
Power session 2
Back squats (5 ×
3 ~90% 1RM)
Clean pulls (3 × 3
~90% 1RM)*
Power snatch from
hang (5 × 3 ~80%
1RM)
Power clean from hang and
split jerk (5 × 3 ~75%
1RM)
Jump shrugs (3 ×
5 ~35%
1RM)*
Split squat (3 × 3
~85% 1RM)
Split jerk (3 × 4 ~80%
1RM)
Front squats (3 × 3 ~85%
1RM)*
Bent-over row (3
× 5 ~85%
1RM)
Romanian dead lift
(3 × 3 ~85%)
1RM
Deadlifts (3 × 3 ~85%
1RM)*
Drop jumps (5 × 5)
Bench press (3 ×
5 ~85% 1RM)
Pull-ups (3 × 3
~85% 1RM)
CMJ (5 × 5 (body
mass))
Bench press (3 × 3 ~85%
1RM)*
NHC (3 × 3
bodyweight)
Military press (3 × 3 Pull-ups (3 × 3 ~85%
~85% 1RM)
1RM)*
NHC (3 × 3 body weight)
Volume load presented as sets × repetitions × load.
* Used to develop/maintain technique and strength/power; 1RM, one repetition maximum; CMJ,
countermovement jump; NHC = Nordic hamstring curls.
Advanced model of periodisation
As the athlete’s S&C age advances and the windows of adaptation begin to
diminish further, more advanced strategies are required, which incorporate
yet more variability and greater volume loads. The majority of the emphasis
is now placed on the prescription of volume loads through advanced
strategies such as the conjugate system (Figure 7.13; also known as the
coupled successive system) (Verkhoshansky, 1986). Because this places the
athlete dangerously close to the overtraining syndrome, athletes undertaking
this system must be able to tolerate very high volume loads (Plisk & Stone,
2003) and the S&C coaches applying these interventions must be highly
skilled. Furthermore, it may be advisable to ensure athletes have at least 2
years’ formal S&C experience, with associated strength adaptations, as this
is usually associated with increases in the anabolic environment of the body
(by virtue of increased testosterone relative to cortisol) and thus greater
tolerance to demanding training.
The conjugate sequence system pioneered by Yuri Verkhoshansky (1986).
The conjugate system involves periods of planned overreaching,
followed by periods of restitution (Plisk & Stone, 2003). Plisk and Stone
(2003) suggest that this is best implemented in blocks of four microcycles
with only one primary emphasis (e.g. strength), and maintenance loads
allocated to other abilities (e.g. speed/power). This system aims to saturate
the emphasised training stress, causing cumulative fatigue and concurrent
decreases in performance; this of course can be difficult within team sport
environments where fixture congestion is common (e.g. soccer, basketball).
Then, during the following restitution blocks, the emphasis is reversed
(Figure 7.13). For example, the volume load for strength training markedly
drops whilst that for speed work is moderately increased. By virtue of a
delayed training effect phenomenon, the athlete’s strength capabilities
undergo supercompensation. A practical example of the conjugate system,
adapted from the work of Plisk and Stone (2003) and Stone et al. (2007), is
illustrated in Table 7.5.
Table 7.5
A practical example for applying and adapting the conjugate system
Training
emphasis
Accumulation Restitution
block 1
block 1
Accumulation Restitution
block 2
block 2
Duration
4 weeks
2–3 weeks
4 weeks
2–3 weeks
Strength and
power training
16 sessions @ 4
days/week
4–6 sessions @ 2
days/week
16 sessions @ 4
days/week
4–6 sessions @ 2
days/week
9 sessions @ 3
days/week
8 sessions @ 2
days/week
9 sessions @ 3
days/week
Speed and agility 8 sessions @ 2
training
days/week
Support for the conjugate system may be gleaned from studies
investigating the response of the endocrine system to prolonged (≥3 weeks)
and severe increases in volume load (Fry, Webber, Weiss, Fry, & Li, 2000;
Hakkinen, 1989; Hakkinen, Pakarinen, Kauhanen, & Komi, 1988; Pendalay
& Kilgore, 2001; Ratamess et al., 2003). In general, these researchers report
significant decreases in resting/pre-exercise testosterone concentration and
the testosterone:cortisol ratio, followed by supernormal levels and
corresponding performance improvements upon returning to normal volume
loads with a subsequent taper. These findings are considered significant as
testosterone concentration and the testosterone:cortisol ratio are indices of
the anabolic/catabolic state of the body (Fry, Kraemer, et al., 2000; Plisk &
Stone, 2003). As a word of warning, however, practitioners should limit the
duration of these concentrated blocks so that an overtraining syndrome does
not develop (Plisk & Stone, 2003). Also, S&C coaches should be attentive
to the potential signs and symptoms of overtraining with each passing week
(Foster, 1998; Jones, 1991; Stone et al., 1991).
A scoping review by Bell et al. (2020) outlines the literature looking at
ways to identify the threshold between functional overreaching and the
necessary avoidance of overtraining. By definition, functional overreaching
represents an acute decrease in performance (days) followed by a
subsequent supercompensation. Non-functional overreaching similarly
starts with a reduction in performance, but usually over a longer period
(weeks) and with no increase of performance following full recovery. As
previously mentioned, if exposure to high-volume load remains consistent,
overtraining syndrome can see the athlete face long-term reductions in
performance over several months (Bell et al., 2020). This opportunity to
increase performance in well-trained individuals is highly sought after, but
consideration as to the threshold that exists between functional
overreaching and non-functional overreaching can be a challenging task.
Much of the literature on overreaching has explored biochemical markers,
such as testosterone and cortisol and their ratio; however, these are likely to
be altered independently of performance, but may provide the acute training
state of the athlete (Bell et al., 2020). Another method to identify training
state that may help distinguish between functional and non-functional
overreaching is the use of surrogate performance tests such as maximal
jump tasks and isometric or dynamic mid-thigh pulls and their associated
variables (Haff et al., 2008; Suarez et al., 2019). Sensitivity of associated
variables attained from these tests has shown reductions in response to
high-volume resistance training and may therefore help differentiate
between fatigue and overreaching (Bell et al., 2020).
While “high-volume” is often associated with overreaching, the reader
should note that the interpretation of what is deemed high or low will be
governed largely by inter-individual variances. That is to say, what is highvolume for one athlete may only be moderate for another. Therefore, when
planning functional overreaching in well-trained athletes, a surrogate
measure and/or biochemical markers may serve as a guide to monitor the
training state of the athlete and better identify the individual’s threshold
between functional and non-functional overreaching and therefore elicit
greater improvements in performance. Where equipment to monitor
surrogate measures are not afforded, the use of historic volume loads via a
training diary may also help the S&C coach to identify the athlete’s reaction
to specific loading protocols and potentially help to determine a volume
load threshold to optimise performance increases.
Maintenance programmes
Maintaining peak performance for 35 weeks
The traditional periodisation strategies identified above are concerned with
athletes who need to peak for a single or acute (<2 weeks) phase of
competitions, e.g. track athletes and martial artists. Some athletes, however,
especially team sport athletes, must reach their peak as part of pre-season
training, and then maintain it for periods of up to 35 weeks, ideally peaking
for the final.
For example, Kraemer et al. (2004) showed that both starting and nonstarting soccer players experienced reductions in sport performance over an
11-week period of the competitive season. Although more pronounced in
the starters, the fact that performance reductions were observed in all
players indicates that performance adaptations may be independent of total
match play and that the volume load of practices/S&C sessions should be
carefully evaluated. Of significance was the fact that a catabolic
environment (increased cortisol and decreased testosterone) was initiated in
the pre-season and not obviated throughout the competition phase. This
may have determined the metabolic status of the players as they entered the
competitive period. While this may be exclusive to the training approach of
collegiate soccer, or those that require athletes to get into shape quickly, the
need for athlete restoration, particularly as they enter the competitive phase,
can be noted. In a professional sporting environment, where fixture
congestion can be a real concern over a prolonged duration, it is worth
noting that both an excessive total training volume and an obsession over
“recovery sessions”, while excluding an appropriate high-load, low-volume
strength stimulus, will result in a reduction in performance.
Further challenges associated with maintenance programmes may be
gleaned from studies undertaken by Kraemer et al. (1989) and Aldercrentz
et al. (1986). These investigators reported that sprint running increases
circulating concentrations of cortisol and decreases concentrations of
plasma testosterone. Therefore for sports such as rugby and soccer, which
may be categorised as high-intensity intermittent exercise, with a
prevalence of repeated bouts of maximal effort sprints, it is likely that an
adverse metabolic environment will present itself if training programmes
are not appropriately periodised.
Non-traditional approach to periodisation
It has been suggested that while the traditional form of periodisation
(discussed above) is appropriate during the off- and pre-season, a nontraditional form of periodisation is more viable for team sports during the
in-season (Gamble, 2006; Hoffman, Kraemer, Fry, Deschenes, & Kemp,
1990; Kraemer et al., 2000, 2003, 2004). At times, this may be out of
necessity because of its ability to adapt to a sport’s competition calendar
and its ease of administration within long seasons (Hoffman, Kraemer, Fry,
Deschenes, & Kemp, 1990; Kraemer et al., 2000, 2003). This form of
periodisation involves changes in volume loads and biomotor emphasis on a
session-to-session basis. An example of a non-traditional periodised
programme is illustrated in Table 7.6. One of the merits of this system is
suggested to be the ease with which sessions can be quickly tailored to the
competition schedule of the athlete (Haff, 2004a). If, for example, a
competition is suddenly cancelled or arranged, the athlete can switch to the
heavy or light training day, respectively. In addition, a microcycle and a
mesocycle can be defined by the number of completed sessions or rotations,
respectively, of the prescribed programme.
Table 7.6
Day
Example microcycle completed as part of a non-traditional periodisation strategy*
Monday
Wednesday
Friday
Day
Monday
Wednesday
Friday
Emphasis and
volume
load
Pushing strength:
4 × 4 @ 4–6RM
(~85–90% 1RM)
Pulling strength:
4 × 4 @ 4–6 RM (~85–
90% 1RM)
Power: 5 × 3 @ variable loads
(dependent on the exercise)
Example
exercises
Squats, bench press
and overhead
press
Romanian deadlift,
pull-ups and barbell
row
Weightlifting and derivatives,
and plyometrics
* Note that a mesocycle may be considered complete following a set number of rotations and
athletes can rearrange the order based on competition scheduling. Finally, hypertrophy sessions
are avoided due to the higher associated training volumes.
1RM, one repetition maximum.
Finally, for the purposes of maintenance, a training frequency of 2 days
per week is often recommended for training during the competitive phase
(Ebben & Blackard, 2001; Ebben, Hintz, & Simenz, 2005; Haff, 2004b;
Gamble, 2006; Simenz, Dugan, & Ebben, 2005). However, including even
two S&C sessions a week for team sport players involved in regular
competition may prove difficult. Gamble (2006) suggests that the issue of
limited training time may be addressed by combining S&C training with
sport practice. For example, speed, agility and plyometrics training can be
included in team practices, and metabolic conditioning can be maintained
through game-related conditioning methods. In addition, the skill element
specific to each, particularly the latter example, encourages its use by sports
coaches (Gamble, 2004). This tactical metabolic training approach can be
structured according to work:rest ratios of the specific sport (Gamble, 2007;
Plisk & Gambetta, 1997) and dominant energy systems.
The taper
The progressive increases in the volume load of periodised S&C
programmes are likely to accumulate excessive fatigue and overstress the
neuroendocrine system. This will reduce the stimulus for adaptation (as
previously discussed) and lead to adverse circulating hormonal
concentrations (Fry & Kraemer, 1997). However, a reduction in training
with a concomitant optimal anabolic environment (or reduced catabolic
processes) induced by a taper could potentially enhance performance
(Izquierdo et al., 2007). The taper requires a reduction in the volume (i.e.
exercises, sets or repetitions) of training in the final days before important
competition, with the aim of optimising performance (Bosquet, Montpetit,
Arvisais, & Mujika, 2007). It should be stressed that the objective of the
taper is to dissipate the accumulated fatigue (enabling performanceenhancing adaptations to become apparent) rather than advance the athlete’s
level of fitness (Mujika & Padilla, 2003). Significant improvements after
tapering have been reported in numerous sports and Table 7.7 gives details
of the associated performance gains, as summarised by Wilson and Wilson
(2008).
Table 7.7
Summary of performance gains following a taper
5–6% improvements in criterion competition performance gains
Up to 20% increases in neuromuscular function (i.e. strength and power)
10–25% increases in cross-sectional area of muscle tissue
1–9% improvements in V̇O2max (this is likely a consequence of hypervolaemia, up to a 15%
increase in RBC production and increased oxidative enzyme activity)
Up to an 8% increase in running economy
Serum testosterone may increase by 5%, with a corresponding 5% decrease in cortisol
Catecholamines may be reduced by up to 20%
Reduced creatine kinase concentrations (suggestive of decreased muscle damage following a
workout)
A 10% increase in anti-inflammatory immune cells, with a concomitant decrease in
inflammatory cytokines
Increased muscle glycogen stores (17–34%; often proportional to the reduction in volume
load) especially following CHO loading. However, care should be taken to match energy
intake with the reduced energy expenditure that characterises the taper
Reduced RPE, depression, anger, and anxiety and increased vigour
Decreased sleep disturbances
V̇O2max, maximal oxygen uptake; RBC, red blood cell; CHO, carbohydrate; RPE, rate of perceived
exertion.
Adapted from Wilson and Wilson (2008).
Taper strategies
Generally, three types of taper are used: a step taper, a linear taper and an
exponential taper (Figure 7.14). A step taper involves an immediate and
abrupt decrease in training volume, e.g. decreasing the volume load by 50%
on the first day of the taper and maintaining this throughout. A linear taper
involves gradually decreasing the volume load in a linear fashion, e.g. by
5% of initial values every workout. The exponential taper decreases volume
at a rate proportional to its current value (half-life), e.g. by 5% of the
previous session’s values every workout. In addition, exponential tapers can
have fast or slow decay rates. Also, Bosquet et al. (2007) suggested an
additional taper, referred to as a “two-phase taper”, which involves a
classical reduction in the training load, followed by a moderate increase
during the last days of the taper (Figure 7.15). The objective of this strategy
is to reduce the athlete’s fatigue before the reintroduction of more
prolonged or intense efforts. The efficacy of the two-phase taper may be
gleaned from anecdotal observations of the progressive improvement in
performance often observed in an athlete from the first round of a
competition to the final (Thomas, Mujika, & Busso, 2009). This form of
taper requires further investigation.
Schematic representation of the three principal tapering strategies. (Adapted
from Mujika and Padilla, 2003.)
Schematic representation of the two-phase taper. (Adapted from Thomas et
al., 2009.)
The optimal taper strategy
As previously mentioned, a taper involves a reduction in the volume load of
either of, or a combination of, the moderators or training, i.e. intensity,
volume and frequency. The optimal manipulation of these variables may be
best evidenced from the meta-analysis conducted by Bosquet et al. (2007);
Table 7.8 summarises their findings, measured as effect sizes, for which the
scale proposed by Cohen (1988) was used in their interpretation.
Accordingly, the magnitude of the difference was considered trivial (<0.20),
small (0.20–0.49), moderate (0.50–0.79) or large (≥0.80).
Table 7.8
Effect of training variables on the effect size of taper-induced performance adaptations
Variable
Effect size
p
d
95% CI
≤20%
−0.02
−0.32–0.27
0.88
21–40%
0.27
0.04–0.49
0.02
41–60%
0.72
0.04–1.09
0.0001
≥60%
0.27
−0.03–0.06
0.07
Yes
−0.02
−0.04–0.33
0.91
No
0.33
0.19–0.47
0.0001
Yes
0.24
−0.03–0.52
0.08
No
0.35
0.18–0.51
0.0001
≤ 7 days
0.17
−0.05–0.38
0.14
8–14 days
0.59
0.26–0.92
0.0005
15–21 days
0.28
−0.02–0.59
0.07
≥ 22 days
0.31
0.14–0.75
0.18
Step
0.42
−0.11–0.95
0.12
Progressive
0.30
0.16–0.45
0.0001
↓ in volume
↓ in intensity
↓ in frequency
Duration of taper
Pattern of taper
CI, confidence intervals; d, Cohen’s d effect size; p, significance value; ↓ magnitude of the
difference was considered trivial (<0.20), small (0.20–0.49), moderate (0.50–0.79) or large
(≥0.80).
Data from Bosquet et al. (2007).
The results from Bosquet et al. (2007) revealed that the optimal taper is
2 weeks in duration and consists of exponentially reducing the volume of
training by 41–61%, whilst maintaining both the intensity and frequency of
sessions. It should be noted that the large variability between studies, as
suggested by 95% confidence intervals, suggests that not all athletes will
respond favourably to this taper prescription, which may be attributable to
the differences in training status and accumulated fatigue prior to the taper,
i.e. greater volume reductions are necessary when previous training
durations are longer and more intense.
Summary and conclusion
Periodisation represents an optimal strategy for organising S&C
programmes. The selected strategy (i.e. basic, intermediate, advanced, nontraditional) should be based on the level of the athlete and the constraints of
the competitive season. A common theme throughout all periodisation
protocols is the need to manipulate volume loads, progress from general to
specific training and to dissipate fatigue, where pre-competition tapers
appear evidently beneficial. Also, the use of a taper appears to produce an
additional supercompensation effect following the accumulated fatigue of
the preceding training programme. For sports engaged in infrequent
competition, traditional periodisation may be best. For team sports, with
long seasons and frequent competitions, non-traditional periodisation may
better suit the demands placed on the athletes, with a reduction in volume,
but not intensity, in the training session immediately prior to competition.
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8
Strategies to enhance athlete recovery
Vincent Kelly, Patrick Holmberg and David Jenkins
DOI: 10.4324/9781003044734-11
Introduction
Defined as the restitution of the initial state, recovery implies a return to preceding form
(Hausswirth & Mujika, 2013; Kellmann, 2002). The restitution of deficit states (Kellmann,
2002) infers the reduction and renewal of performance which, relative to the extent and
nature of the imposed stress, are rate-dependent (Nedelec et al., 2012). Stress is
compounded when successive bouts compromise the innate rate of recovery (Bishop et al.,
2008; Minett & Duffield, 2014). Maladaptation in response to accumulated
psychophysiological stress can exacerbate performance decrements and increase the risks
of injury (Kentta & Hassmen, 1998; Soligard et al., 2016). The density of contemporary
training and competitive schedules can reduce recovery periods and thus potentially
compromise an athlete’s readiness for further training and/or competition (Skorski et al.,
2019). Various recovery modalities are used in sport to counter exercise-induced
homeostatic perturbations that could diminish performance (Barnett, 2006). However, the
interaction among workload and fatigue, muscle damage, soreness (and concomitant
perception), and recovery and adaptation is complicated (Sands et al., 2016) and may be
positively (Capps & Mayberry, 2009; Halson et al., 2014; Ihsan et al., 2015; MarquesJimenez et al., 2016) or negatively (Broatch et al., 2018; Higgins et al., 2011; Roberts et
al., 2015) affected or unaffected (Cheung et al., 2003; Costello et al., 2012; French et al.,
2008) by the intervention. The purpose of this chapter is to provide insight regarding the
physiological mechanisms that underpin prevalent recovery strategies to guide efficacious
practice.
Recovery strategies
Strategies that have been shown to support recovery (Barnett, 2006) after exercise include
water immersion therapy (cold [Halson et al., 2014], hot [Vaile et al., 2008a], contrast [Gill
et al., 2006], thermoneutral [Versey et al., 2013]), compressive techniques (compressive
garments [Marques-Jimenez et al., 2016], intermittent pneumatic compression [Cochrane
et al., 2013], massage [Poppendieck et al., 2016]), whole-body cryotherapy (WBC)
(Lombardi et al., 2017), and sleep (Halson, 2008). Although modalities have been
classified as short-term or long-term or peripheral (direct application to a body part) or
central (less direct systemic effect) (Minett & Duffield, 2014; Sands et al., 2016), it is
generally difficult to separate the effectiveness of individual strategies given that many are
used concurrently by athletes (Amann, 2011). Whether directly or indirectly, most of these
strategies enhance circulation (blood and lymphatic flow) (Barnett, 2006; Bishop et al.,
2008; Sands, 2016) to attenuate intramuscular fluid pressure (swelling), which is linked to
delayed-onset muscle soreness (DOMS) via the inflammatory cascade after exerciseinduced muscle damage (EIMD) (Appell et al., 1992), and aid the removal of metabolites
and cellular debris to restore acute (i.e., 0–72 hours post-exercise) function (Bishop et al.,
2008). Less well described are the adaptive effects of recovery over longer time periods. A
summary of practical recommendations for recovery strategies is provided in Table 8.1.
Table 8.1
Practical recommendations for recovery strategies
Recovery strategy
Practical recommendations
Water
immersion
therapy
CWI
1–3 sets of 5–15 min at 11–15°C (whole-body [head-out] immersion) immediately
following high-intensity exercise (Halson, 2011; Versey et al., 2013)
HWI
HWI may not enhance acute performance recovery; future investigation regarding
protocol characteristics (e.g., duration, temperature, depth) is needed (McGorm et al.,
2018)
CWT
3–6 (cold and hot) sets of 60 s at 8–15°C followed by 1–3 min at 38–42°C for 9–15 min
following high-intensity exercise (Versey et al., 2013)
CG
Apply immediately and for 72 hours after high-intensity muscle-damaging exercise;
custom-fitted CG exert greater pressure than standard-size CG, which may enhance
performance recovery effects (if blood flow is not restricted) (Kraemer et al., 2004)
IPC
Apply immediately for 72 hours after high-intensity muscle-damaging exercise; pulse
pressure of cells 1 (distal), 2–4, and 5 (proximal) are 70, 80, and 60 mmHg,
respectively; pulse time and rest time are typically preset (by the manufacturer) at 30 s
for 15 min (Cochrane et al., 2013; Hoffman et al., 2016; Sands et al., 2015)
Compressive
techniques
Massage 5–12 min after mixed-type exercise to enhance acute performance recovery (Poppendieck
et al., 2016)
WBC
30 s at −60°C followed by 2 min at −135°C with a 2-min break between bouts (Selfe et
al., 2014) immediate and recurrently following high-intensity muscle-damaging
exercise (Hausswirth et al., 2011; Pournot et al., 2011a).
CWI, cold-water immersion; HWI, hot-water immersion; CWT, contrast water therapy; CG, compression garments;
IPC, intermittent pneumatic compression; WBC, whole-body cryotherapy.
Water immersion therapy
Water immersion therapy, which consists of four modes based on water temperature (cold
[< 15°C], hot [> 36°C], contrast [alternation of immersion in cold and hot water],
thermoneutral-water immersion [15–36°C] [Versey et al., 2013]), is a popular recovery
strategy that has been the focus of several reviews (Bleakley & Davison, 2010; Broatch et
al., 2018; Tipton et al., 2017; Wilcock et al., 2006). In addition to analgesic effects (Coffey
et al., 2004), hydrostatic pressure elicits a cephalad redistribution of blood flow
(Arborelius et al., 1972) that elicits physiological alterations, including intracellular and
intravascular fluid shifts, reduction of muscle edema, and elevated cardiac output (Wilcock
et al., 2006) that supports the removal of metabolic end products and substrate
transportation post-exercise to restore acute function and assist tissue repair (Coffey et al.,
2004).
Cold-water immersion (CWI)
CWI complements the effects of hydrostatic pressure given that cold-induced
vasoconstriction may lessen muscle perfusion and interstitial fluid diffusion (Gregson et
al., 2011) and reduce cellular, lymphatic, and capillary vessel permeability to dissipate
edema (Cote et al., 1988). This decreases pain and mitigates the loss of force production
(Smith, 1991). Reducing edema can also reduce cellular oxygen demand as a consequence
of capillary constriction to lessen hypoxic cell damage and reduce immune cell infiltrates
that may augment cellular injury to moderate subsequent tissue damage and necrosis
(Capps & Mayberry, 2009; Wilcock et al., 2006). Additionally, metabolism can be slowed
by >50%, which may facilitate oxygen diffusion to damaged tissues (Capps & Mayberry,
2009). Whilst this response reduces peripheral blood flow to maintain core temperatures,
increases in central metabolism to offset the physiological responses to CWI may activate
the sympathetic nervous system, induce oxidative stress, proliferate cellular and systemic
free radicals, increase the production of waste products, and dissipate energy stores that
can further exacerbate muscle stress and hinder the recovery process (Bleakley & Davison,
2010; Wilcock et al., 2006). However, a decrease in body temperature slows nerve
transmission to stimulate an analgesic effect and reduce muscle spasm, which can lessen
the perception of pain after damaging exercise (Wilcock et al., 2006). Thus, largely
dependent on the protocol, CWI may hinder or hasten the recovery of exercise-induced
decrements in function and performance (Bleakley & Davison, 2010; Broatch et al., 2018).
While this is covered later, it is worth noting that this may be advantageous during periods
of intensive competition/fixture congestion, but not desirable if aiming to facilitate
positive adaptations. For example, athletic preparation staff may choose to limit the use of
water immersion therapy during the general physical preparation phase of an annual
training plan to enhance physical adaptations (Table 8.2) and increase its use during a
competition week to enhance recovery (Table 8.3).
Table 8.2
Example of a 12-week periodized training plan for college soccer and recommendations for use of water
immersion therapy
Fitness
phase
GPP
SPP
Phase
duration
9 weeks
3 weeks
Phase
objectives
Increase muscle mass, strength,
and general work capacity
Weekly
training
density
6–8
Increase sport-specific technical/tactical
proficiency and work capacity and
strength and rapid force production
10–12
Day of week
D1
D2
D3
Training
mode
ST
RT
Off COD
RT
TT
Betweensession
break
6–8
h
0h
Training
load
H
L
D4
RT
M-H
D5 D6
D7
D1
D2
D3
D4
ST
Off TTS
TTS
RT
TT RT
TTS
TTS
TTS
6–8
h
6–8 h
6–8 h
6–8 h
H
H
M
H-M
L
Water
immersion
therapy
D5
D6
D7
TTS
RT
Off
TTS TTS
L
*CWT **CWT *CWT
**CWI
**CWI
TTS
6–8 h
6–8 h
M-H
H
**CWI **CWI
*after the first training session; **after the second training session.
COD, change of direction; CWI, cold-water immersion; CWT, contrast water therapy; D, day; GPP, general physical
preparation; H, high; L, low; M, moderate; RT, resistance training; SPP, special physical preparation; ST, speed training;
TT, tempo training; TTS, technical/tactical session.
Table 8.3
Starter
Example of an in-season week for American football and recommendations for use of water immersion
therapy
Training load
D1
D2
D3
D4
D5
Game day
M
H
Off
M
L
H
Training mode
RT
RT
TTS
TTS
Between-session break
6–8 h
6–8 h
Water immersion therapy
*CWT
**CWI
*CWT
CWI
CWI
M-H
M
Off
TTS
Redshirt/
reserve
Training load
M
H
Off
Off
TTS
M-H
*after the first training session; **after the second training session.
CWI, cold-water immersion; CWT, contrast water therapy; D, day; H, high; L, low; M, moderate; RT, resistance
training; ST, speed training; TTS, technical/tactical session.
Training mode
TTS
Between-session break
RT
RT
RT
ST
TTS
TTS
TTS
RT
6–8 h
6–8 h
6–8 h
Water immersion therapy
*after the first training session; **after the second training session.
CWI, cold-water immersion; CWT, contrast water therapy; D, day; H, high; L, low; M, moderate; RT, resistance
training; ST, speed training; TTS, technical/tactical session.
Owing to methodological inconsistencies (e.g., immersion and exercise protocol,
participants’ training background, timing, performance outcome, length of the study) and
participant bias (Broatch et al., 2014), studies investigating the benefits of CWI have
produced mixed results (Broatch et al., 2018). Briefly, muscle strength and power (Higgins
et al., 2017; Vaile et al., 2008b), endurance performance (Ingram et al., 2009), intermittent
exercise (Roswell et al., 2009, 2010), markers of EIMD (Eston & Peters, 1999; Leeder et
al., 2012a), inflammation (Montgomery et al., 2008; Peake et al., 2008), DOMS (Higgins
et al., 2013; Vaile et al., 2008b), and perceptions of fatigue (Higgins et al., 2017; Leeder et
al., 2012a) have been shown to benefit from CWI. However, CWI has been shown to have
no benefit (Coffey et al., 2004; Higgins et al., 2017; Howatson et al., 2009; Jakeman et al.,
2009; King & Duffield, 2009; Kinugasa & Kilding, 2009) or a negative effect (Broatch et
al., 2018; Crowe et al., 2007; Schniepp et al., 2002; White et al., 2014) on these same
outcomes by others. Although immersion protocols that involve whole-body immersion
(head out) at a temperature of 11–15°C for 5–15 min (Halson, 2011; Versey et al., 2013)
have been generally shown to enhance post-exercise function (Mujika et al., 2018), the
effects of regular CWI on muscle adaptation are less clear (Tipton et al., 2017).
Accepting the proposition that recovery strategies can blunt the pro-inflammatory phase
of inflammation that is critical for muscle remodeling (Chazaud, 2016), regular postexercise CWI may diminish training adaptations. However, the outcome may depend on
the nature of exercise. For example, CWI has been shown to alter the adaptive response to
resistance training (Fuchs et al., 2020; Fyfe et al., 2019; Roberts et al., 2015) via decreases
in muscle blood flow (Gregson et al., 2011) that can subdue the acute inflammatory
response (Chazaud et al., 2003). In turn, this is believed to impair muscle protein turnover
(Fujita et al., 2006; Timmerman et al., 2010). The activation of adenosine monophosphatedependent protein kinase (AMPK) in response to cold-water temperatures (Oliveira et al.,
2004) may also suppress mammalian target of rapamycin (mTOR) (Roberts et al., 2015)
and inhibit ribosomal biogenesis to hinder muscle hypertrophy and strength gains. Roberts
et al. (2015) showed that CWI decreased acute satellite cell activity and the activation of
kinases that regulate muscle hypertrophy. Negligible improvements in isokinetic work and
type II muscle fiber cross-sectional area were also demonstrated. Over 12 weeks, these
effects may have been compounded to lessen the anticipated gains in muscle mass and
strength. Indeed, 7 weeks of regular CWI has been shown to attenuate increases in type II
muscle fiber cross-sectional area compared to passive recovery in resistance-trained males
(Fyfe et al., 2019). Basal protein degradation markers were increased, whereas mTOR1
signaling was blunted 1 and 48 hours post-training after CWI. In agreement with the
findings of Roberts et al. (2015), post-workout CWI attenuated muscle fiber growth.
However, lower-body muscle strength was improved to similar levels in each group, which
contrasts with the findings of Roberts et al. (2015). Collectively, the available data suggest
that CWI after resistance training may not be advised if muscle hypertrophy is desired
(Fyfe et al., 2019; Roberts et al., 2015).
Apart from Yamane et al. (2006), who reported attenuated improvements in maximal
oxygen uptake (V̇O2max) and endurance performance following 4–6 weeks of routine CWI
compared to passive recovery, the available evidence, on balance, does not indicate
deleterious effects of CWI on endurance performance or markers of adaptation resulting
from endurance training (Aguiar et al., 2016; Broatch et al., 2017; Halson et al., 2014).
Halson et al. (2014) showed that CWI completed four times per week over a 3-week
overreaching period followed by an 11-day taper significantly improved performance in a
high-intensity interval cycling test. Allan et al. (2017) and Ihsan et al. (2014) found that 15
min of lower-extremity CWI after near-maximal intermittent cycling and 30 min of
submaximal running followed by intermittent running to exhaustion, respectively,
enhanced the expression of peroxisome proliferator-activated receptor y coactivator-1α
(PGC-1α) compared to the control groups. Markers of mitochondrial biogenesis were not
confined to a single bout of exercise (Ihsan et al., 2015). Performance indices (V̇O2max,
running velocity), signaling kinase content (PGC-1α, AMPK, p38 mitogen-activated
protein kinase [p38 MAPK]), and enzyme activities indicative of mitochondrial biogenesis
were significantly greater in participants who employed CWI versus passive recovery over
4 weeks of endurance training. In contrast, however, endurance performance and similar
markers of mitochondrial biogenesis (PGC-1α, p53, heat shock 70 kDa protein 1, AMPK,
p38 MAPK) and function did not significantly differ between CWI (10°C for 15 min) and
passive recovery groups who completed 4 and 6 weeks of cycling sprint and high-intensity
training, respectively (Aguiar et al., 2016; Broatch et al., 2017). Ihsan et al. (2015) caution
that, whilst mitochondrial biogenesis may be enhanced, regular CWI can concomitantly
decrease mitochondrial efficiency. Although the results of studies do not indicate any
negative effects, the use of CWI to improve endurance performance and increase the
content of signaling proteins related to mitochondria biogenesis has been questioned
(Bleakley & Davison, 2010; Broatch et al., 2018; Tipton et al., 2017; White et al., 2014).
Hot-water immersion (HWI)
The influence of HWI on recovery has been less well researched, although it may be
acutely harmful (e.g., burns, rapid decrease in blood pressure, hypotension, faintness, loss
of vasomotor control, tachycardia: Nagasawa et al., 2001; Turner et al., 1980). However,
researchers have shown that HWI can provide acute restorative benefits (Kuligowski et al.,
1998; Peake et al., 2017a; Pournot et al., 2011a; Vaile et al., 2008a, 2008b; Viitasalo et al.,
1995) and may enhance training adaptations (Peake et al., 2015). Muscle strength and
power (Vaile et al., 2008b, Viitasalo et al., 1995), markers of EIMD (Vaile et al., 2008b;
Viitasalo et al., 1995), and inflammation (Kuligowski et al., 1998) have been shown to be
lower following HWI, although contradictory findings have been demonstrated in studies
that have used similar experimental protocols (Kuligowski et al., 1998; Pournot et al.,
2011a; Vaile et al., 2008b). HWI may benefit muscle adaptation as heat shock factor-1 and
its effectors (heat shock proteins) have been shown to protect against oxidative damage,
apoptosis, and adenosine triphosphate depletion (Hatade et al., 2014; Maglara et al., 2003)
and downregulate enzymes and transcription factors that cause protein degradation (Dodd
et al., 2009; Gehrig et al., 2012) and activate anabolic signaling pathways (Gwag et al.,
2013) that stimulate muscle remodeling (McGorm et al., 2018; Peake et al., 2015).
However, post-exercise HWI has been shown not to enhance acute recovery via heat shock
protein, cytokine, or macrophage response (Peake et al., 2017a). Following 10 weeks of
lower-extremity resistance training, relative gains in muscle mass were significantly lower
among participants who routinely employed HWI compared to passive recovery (Peake et
al., 2017a). Although strength significantly improved in each group, increases were
substantially less in the experimental condition (Peake et al., 2017a). Based on limited
data, HWI may not have a significant effect on post-exercise recovery and could mitigate
adaptations to training (Versey et al., 2013).
Contrasting water temperature (CWT)
Whereas cold and hot water temperatures cause vasoconstriction and vasodilation
respectively, it has been suggested that CWT alternates cold and heat to evoke a “pumping
action” that can increase blood flow and therefore lessen the extent and duration of
inflammation (Bieuzen, 2013; Hing et al., 2008). However, this notion has been
challenged, as CWT may not produce the intramuscular temperature changes needed to
elicit this effect (Higgins & Kaminski, 1998; Hing et al., 2008). Although beneficial
effects, including vasodilation and vasoconstriction, increased blood flow, reduction of
markers of muscle damage (creatine kinase [CK]) and inflammation, and decreased
swelling, pain, and muscle stiffness (Cochrane, 2004) have been demonstrated with CWT,
the physiological mechanisms that potentially underpin CWT have not been well described
(Hing et al., 2008).
In their review, Versey et al. (2013) stated that less than half of the studies that
investigated the effects of post-exercise CWT on recovery and performance found
beneficial effects. Whereas CWT elicited acute improvements in performance, muscle
strength and power (Vaile et al., 2007, 2008a, 2008b; Versey et al., 2011), endurance
(Higgins et al., 2011; Versey et al., 2012), intermittent exercise (King & Duffield, 2009),
markers of EIMD (Eston & Peters, 1999; French et al., 2008), inflammation (Eston &
Peters, 1999; Vaile et al., 2007, 2008b), DOMS (Dawson et al., 2005; French et al., 2008;
Gill et al., 2006; Ingram et al., 2009; Kuligowski et al., 1998; Vaile et al., 2008b),
perceived exertion (Higgins et al., 2017; Versey et al., 2011), and perceptions of fatigue
(Kinugasa & Kilding, 2009; Versey et al., 2011), the effects have been found to be
negligible (Dawson et al., 2005; Dupuy et al., 2018; Hamlin, 2007; Higgins et al., 2017;
King & Duffield, 2009; Kinugasa & Kilding, 2009; Pournot et al., 2011a) and detrimental
by others (Higgins et al., 2011, 2017; Pournot et al., 2011a; Versey et al., 2011, 2012).
Research that showed beneficial effects of CWT employed similar protocols that differed
substantially from studies that showed negligible or detrimental effects (Versey et al.,
2013). More recent meta-analyses have confirmed these overall findings (Dupuy et al.
2018; Higgins et al., 2017). Moreover, in contrast to other immersion modes, less is known
regarding the long-term adaptive effects of regular CWT. Despite largely positive acute
effects on anaerobic performance (Bieuzen, 2013), particularly in response to temporary
increases in workload, a disrupted adaptive response has been found with regular use
(Chazaud, 2016; Peake et al., 2017b). Evidence suggests that CWI and CWT elicit similar
acute positive recovery effects compared to HWI or thermoneutral-water immersion (Vaile
et al., 2008a, 2008b; Versey et al., 2013). However, it is not clear which immersion
protocol is most effective (Versey et al., 2013). Like CWI, no ideal prescription for CWT
exists; whether treatment ought to culminate with CWI or HWI is not clear. Nevertheless,
60 s at 8–15°C followed 1–3 min at 38–42°C for 9–15 min has been recommended
(Bieuzen, 2013; Versey et al., 2013). In summary, CWT and CWI are generally effective in
maintaining or limiting decreases in performance during condensed sport schedules
(Bieuzen, 2013). However, ongoing exposure may blunt adaptive responses to certain
modes of exercise and may be contraindicated during particular training periods (Chazaud,
2016; Peake et al., 2017b; Skorski et al., 2019).
Compressive techniques
Compressive techniques, including compression garments (CG), intermittent pneumatic
compression (IPC), and massage to facilitate recovery following exercise, are now
commonly accessible by athletes. However, disparate findings regarding the restorative
effects of these modalities can in part be attributed to differences in study design and interand intra-individual variations in participant training status, stress response to exercise,
post-treatment perception of recovery, preferential bias, and other confounding factors
(sleep, nutrition, mood, etc.). Compressive garments (Hill et al., 2014a; Marques-Jimenez
et al., 2016) and IPC (Couturier & Duffield, 2013) have been shown to elicit positive
psychophysiological effects in individuals of different physical activity levels in the days
after various modes of strenuous exercise. In contrast, massage, which is difficult to
standardize (Sands, 2016), has demonstrated equivocal findings, as indicated by several
meta-analyses (Dupuy et al., 2018; Moraska, 2005; Poppendieck et al., 2016; Weerapong
et al., 2005). Given the high heterogeneity between studies, recommendations relating to
IPC need to be made with caution.
Compression garments
Traditionally used to treat clinical pathologies, CG are now widely used for restorative
purposes; the induced external pressure gradient is believed to reduce swelling and pain,
and enhance lymphatic flow to remove myocellular debris following muscle-damaging
exercise (Hill et al., 2014b; Kraemer et al., 2001a). Studies have shown progressive
decreases in swelling at 24, 48, and 72 hours (Bovenschen et al., 2013; Brown et al., 2020;
Carling et al., 1995; Davies et al., 2009; Kraemer et al., 2001a,b) and positive moderate
effects on markers of EIMD (i.e., CK, lactate dehydrogenase [LDH]) at 24, 48, and 96
hours after compression treatment (Brown et al., 2020; Davies et al., 2009; Duffield et al.,
2008, 2010; French et al., 2008; Jakeman et al., 2010a, 2010b; Kraemer et al., 2001a,
2001b), although the effects appear to be dependent on time (reduced LDH only after 24
hours post-treatment) (Davies et al., 2009; Kraemer et al., 2001a), the primary site of
muscle damage (Kraemer et al., 2001a), participants’ training status (Maughan & Gleeson,
2010), and the mode and relative novelty of exercise (thus the degree of EIMD) (MarquesJimenez et al., 2016). However, given the high inter- and intra-individual variability of
these markers and their poor temporal relationship with muscle function (Friden & Lieber,
2001), it is difficult to reliably determine the progressive magnitude of post-treatment
effectiveness on EIMD.
CG have shown beneficial effects on muscle swelling at 48 and 72 hours after a range
of exercise protocols (Marques-Jimenez et al., 2016). According to Kraemer et al. (2004),
these effects are related to the time period in which intramuscular and subcutaneous
swelling is generally evident. As such, a reduction in swelling could attenuate the proinflammatory response that can elicit further muscle damage (Kraemer et al., 2001a) and
cause soreness (Jakeman et al., 2010a, 2010b). Thus, post-intervention reductions in
muscle swelling may align with demonstrated reductions in perceived soreness between 24
and 72 hours (Carling et al., 1995; Davies et al., 2009; Duffield et al., 2008, 2010; French
et al., 2008; Jakeman et al., 2010a, 2010b; Kraemer et al., 2001a, 2001b; Sands et al.,
2015) and attenuated performance decrements (as indicated by countermovement jump
and squat jump height, muscle strength and power, and sprint and change of direction) at
24, 48, 72, and 96 hours post-exercise (Brown et al., 2020; Duffield et al., 2008; Jakeman
et al., 2010a, 2010b; Kraemer et al., 2001a, 2001b).
Despite these positive results, researchers have demonstrated equivocal findings within
and between studies (Marques-Jimenez et al., 2016) owing to the mode of exercise,
application of the garment, outcome measures, subjective bias, and, notably, the exerted
pressure (Couturier & Duffield, 2013; Davies et al., 2009). Although results have shown
improvements in perceived muscle soreness post-exercise, inter-individual variations in
response to, and the complex nature of, EIMD (Clarkson & Hubal, 2002) may be
responsible for inconsistencies – inconsistencies that limited practical recommendations
relating to the practice (Couturier & Duffield, 2013; Marques-Jimenez et al., 2016).
Additionally, a range of pressures (15–35 mmHg) have been used in studies examining the
potential benefits of post-exercise muscle compression (Hill et al., 2015). Whereas lower
pressures (<25 mmHg) may not elicit physiological responses (e.g., increased blood flow
and osmotic pressure), greater pressures can restrict blood flow, which may hinder
recovery (Hill et al., 2015). As such, there may be an optimal level of pressure required to
elicit the greatest increase in venous blood flow (Driller & Halson, 2013). Determining
this is challenging given differences in limb and tissue size and individual variability in the
sensitivity to blood flow changes (Bishop et al., 2008; Couturier & Duffield, 2013).
Interestingly, Brown et al. (2020) showed that custom-fitted CG, which exerted
substantially greater pressures than standard-size CG, were associated with significantly
greater improvements in recovery (e.g., lower plasma CK activity and reduced muscle
swelling) in rugby players. Additional questions regarding the length of time CG should be
applied, the influence of posture relative to the exerted pressure, and how treatment may
affect longer-term recovery ought to be addressed so that more definitive
recommendations can be provided (Marques-Jimenez et al., 2016). Nevertheless, the
available evidence suggests that athletes can benefit from CG, particularly to facilitate
acute recovery, if applied immediately post-exercise and up to 72 hours following muscledamaging exercise (Kraemer et al., 2004).
Intermittent pneumatic compression
Pneumatic compression dynamically inflates and deflates sleeves secured around limbs to
elicit intermittent pulse compression (Cochrane et al., 2013). Similar to static compression,
IPC can increase arterial blood flow and venous and lymphatic return and reduce swelling
(Couturier & Duffield, 2013; Sands, 2016). However, compared to static compression, IPC
has been shown to exert greater pressures to enhance lymphatic drainage, which may
increase the velocity of blood flow and hasten the dissipation of swelling and removal of
cellular debris to improve soft-tissue healing (Capps & Mayberry, 2009; Havas et al.,
1997; Khanna et al., 2008). Recently, Zuj et al. (2017, 2019) showed that IPC enhanced
limb blood flow and tissue oxygenation during recovery, although it did not attenuate
muscle force loss in a range of muscle actions at low (30° per second) and high (180° per
second) angular velocities after muscle- damaging exercise (Cochrane et al., 2013) or
improve recovery following long-distance running (Draper et al., 2020; Heapy et al., 2018;
Hoffman et al., 2016; Overmayer & Driller, 2017). Collectively, the available data show no
significant effects of IPC on markers of EIMD (e.g., C-reactive protein [CRP]) (Draper et
al., 2020; Overmayer & Driller, 2017) or subsequent performance (Heapy et al., 2018) and
mixed results regarding subjective measures of recovery (Draper et al., 2020; Heapy et al.,
2018; Hoffman et al., 2016; Overmayer & Driller, 2017). IPC showed no effects on
performance, markers of inflammation, and non-significant improvements in self-reported
soreness in a group of American football players at 3 and 24 hours post-training (Chase,
2017). In addition to the inconsistent findings and the potential lack of accessibility of IPC
in most sport settings, specific recommendations to guide IPC pulse pressure, pulse time,
duration, and length of treatment are not clear.
Massage
Massage, which involves a range of different techniques, including vibration, is perceived
to improve blood flow and reduce muscle swelling, pain, and stiffness, and reduce
functional decrements post-exercise. However, excluding an ameliorated
psychophysiological response (Delextrat et al., 2013; Hemmings, 2001; Mancinelli et al.,
2006), and therefore a heightened sense of relaxation (Olausson et al., 2010), only limited
evidence supports these claims (Davis et al., 2020; Weerapong et al., 2005). Reviews have
shown that whilst massage is a popular recovery modality among athletes, its effects are
trivial and equivocal (Davis et al., 2020; Moraska, 2005; Nedelec et al., 2013;
Poppendieck et al., 2016). A meta-analysis that included 22 randomized control studies
showed that massage elicited a ~3% improvement in performance; more than half of the
included studies showed negligible effects, whereas five and four studies showed mixed
and negative results, respectively; larger effects were found for shorter massage durations
(5–12 min) and recovery periods (5–10 min) after and between high-intensity exercise
bouts in untrained athletes (although the average performance improvements were
considered relevant for elite athletes) (Poppendieck et al., 2016). A more recent metaanalysis concluded that massage did not enhance measures of performance or perceived
fatigue; however, it did have the potential to reduce DOMS (Davis et al., 2020).
Understanding that the sensitization of pain receptors (nociceptors) via inflammatory
cell infiltrates can to some degree underlie muscle soreness (Hyldahl & Hubal, 2014),
massage may provide an analgesic effect through a reduction in muscle swelling (Crane et
al., 2012; Smith et al., 1994). Immediately after and 2.5 hours following 10 min of
massage, muscle biopsies showed reduced inflammatory markers (nuclear factor kappa B,
prostaglandin E2 [PGE2], interleukin [IL]-6, tumor necrosis factor-α [TNF-α]) and
increased mitochondriogenesis which, taken together, may have reduced pain and hastened
muscle repair in participants who performed a 30-min exhaustive bout of upright cycling
(Crane et al., 2012). In a similar study, a 30-min massage (administered 2 hours after
eccentric exercise) showed reduced neutrophil accumulation and lower CK levels and
perceived soreness at 30-min intervals over 8 hours and at 8, 24, 48, 48, 73, 96, and 120
hours, respectively, compared to a control group (Smith et al., 1994). Thus, limited
massage durations may enhance acute recovery by suppressing inflammation.
According to Weeks and Horan (2009), the benefits of massage may be psychological
rather than physiological. Positive psychological effects on perceived recovery have been
repeatedly demonstrated (Davis et al., 2020; Dawson et al., 2004; Delextrat et al., 2013;
Farr et al., 2002; Hemmings, 2001; Hilbert et al., 2003; Mancinelli et al., 2006). However,
these findings should be interpreted with caution, as many studies investigating the effects
of massage have had methodological flaws relating to an assortment of massage
techniques, lack of a control group, and often a rapport between masseuse and athlete that
has the potential to influence subjective findings (Sands, 2016). Nevertheless, athletes’
partiality for massage should not be disregarded despite negligible and ambiguous
findings.
Whole-body cryotherapy
WBC was initially employed nearly 40 years ago to treat rheumatoid arthritis (Lombardi et
al., 2017). More recently, WBC has been equivocally shown to reduce muscle
inflammation and damage (Pournot et al., 2011b; Ziemann et al., 2014) and enhance
subjective recovery (Bleakley et al., 2014) and psychological parameters (Schaal et al.,
2015) following, and during periods of, rigorous training. Briefly, WBC has been shown to
induce peripheral vasoconstriction to enhance muscle oxygenation, lower heart rate, and
increase stroke volume, and stimulate parasympathetic nervous system activity, which can
favor post-exercise recovery (Kruger et al., 2015; Lombardi et al., 2017; Zalewski et al.,
2014). Additionally, WBC has been shown to evoke anti-inflammatory effects, indicated
by a reduction and increase in pro- (IL-2, IL-8, IL-1β) and anti- (IL-10, IL-1 receptor
agonist) inflammatory cytokines, respectively, and discordant effects on IL-6, and lessen
muscle damage, indicated by the inhibited release of intracellular enzymes (CK, LDH) and
PGE2 and CRP (Ferreira-Junior et al., 2014; Pournot et al., 2011b), which may underlie
subjective markers (Gregorowitcz & Zagrobelny, 1998; Pournot et al., 2011b; Schaal et al.,
2015) and function (Fonda & Sarabon, 2013; Hausswirth et al., 2011). However,
mechanistic underpinnings are widely debated (Ferreira-Junior et al., 2014; Lombardi et
al., 2017).
Based on conflicting findings (Costello et al., 2012; Fonda & Sarabon, 2013; Guilhem
et al., 2013; Hausswirth et al., 2011; Kruger et al., 2015; Vieira et al., 2015) and the limited
number of randomized studies, WBC may not improve functional recovery (Bleakley et al.
2014; Costello et al., 2015), although methodological heterogeneity, notably, the timing
and frequency of treatment, has confounded results (Lombardi et al., 2017). Given that the
pro-inflammatory process is evoked immediately following EIMD, delayed exposure to
WBC may be too late to elicit a favorable response (Ferreira-Junior et al., 2014). Muscle
damage, soreness, and function were not affected after WBC was applied 24 hours postexercise (Costello et al., 2012), whereas a single treatment immediately following
plyometric training reduced muscle swelling and improved the rate of strength recovery
compared to controls (Ferreira-Junior et al., 2014). In contrast, immediate post-training
exposure showed no effects on performance, soreness, or recovery (Guilhem et al., 2013;
Russell et al., 2017; Vieira et al., 2015). Thus, the timing of treatment (relative to exercise)
may or may not be impactful. Results that favor WBC are generally observed among
studies that repeat exposure over consecutive days. Successive treatments elicited positive
effects on muscle strength and soreness following long-distance running and eccentric
resistance training (Fonda & Sarabon, 2013; Hausswirth et al., 2011; Pournot et al., 2011b)
compared to a single exposure and three short sessions interspersed by a week in soccer
and rugby players, respectively (Russell et al., 2017; Selfe et al., 2014). Accordingly, a
single session prescribed immediately after eccentric exercise induced similar effects as
passive recovery (Ziemann et al., 2014). However, when exposure was repeated twice
daily over 5 days, enhanced physiological alterations (IL-6 and IL-1β were not changed
and IL-10 was substantially elevated) were shown compared to the control group
(Ziemann et al., 2014). It should be noted that the results may have been impacted by the
repeated bout effect (Ferreira-Junior et al., 2014). Nevertheless, a single session may not
be adequate to induce a beneficial effect (Lombardi et al., 2017). Despite widespread
differences in protocols (e.g., temperature, acute timing and duration of exposure,
participants’ training status, body composition, preceding exercise mode) (Lombardi et al.,
2017), WBC may be optimized via 30 s at −60°C followed by 2 min at −135°C with a 2min break between bouts (Selfe et al., 2014). Immediate and recurrent post-exercise WBC
exposure may elicit superior effects compared to a single delayed treatment (Fonda &
Sarabon, 2013; Hausswirth et al., 2011; Pournot et al., 2011b; Ziemann et al., 2014).
The results of a number of studies have shown that WBC has a positive effect on
subjective parameters (Gregorowitcz & Zagrobelny, 1998; Hausswirth et al., 2011;
Hausswirth, 2013; Lombardi et al., 2017; Pournot et al., 2011b; Schaal et al., 2015).
Improved psychological recovery, indicated by an enhanced perception of muscle fatigue,
pain, and well-being, has been shown in competitive endurance athletes and elite
synchronized swimmers (Hausswirth et al., 2011; Pournot et al., 2011b; Schaal et al.,
2015). Compared to passive recovery, WBC also significantly improved sleep duration and
latency during a week of intensified training (Schaal et al., 2015). Post-exercise
parasympathetic reactivation, induced biochemical release (e.g., dopamine, serotonin,
beta-endorphin), and decreased and increased pro- and anti-inflammatory cytokines,
respectively, speculatively contributed to improved mood and sleep patterns and therefore
the possible deterrence of non-functional overreaching (Schaal et al., 2015; Tipton et al.,
2017). In related findings, WBC has been shown to improve sleep, sense of relaxation,
mood, and symptoms of depression in patients undergoing treatment (Gregorowitcz &
Zagrobelny, 1998; Rymaszewska et al., 2003, 2008). Additionally, recurrent exposure
could strengthen the immune system and reduce the susceptibility to infection (Hausswirth
& Mujika, 2013). Given that overtrained athletes can present similar symptom profiles as
clinically depressed patients (Dishman, 1983) and demonstrate a weakened immune
function (Fry et al., 1994), WBC may potentially be useful during periods of extreme
physiological stress that result in psychological perturbation (Clow & Hucklebridge, 2001;
Slavich & Irwin, 2014). In summary, methodological inconsistencies make it difficult to
establish the efficacy of WBC and its application, particularly due to the financial costs
involved. However, the positive psychological effects (i.e., subjective indices) of WBC
exposure should not be overlooked.
Sleep
Surveys on recovery strategies in elite sport revealed that 95% and 100% of practitioners
and team sport athletes, respectively, considered sleep to be an effective recovery strategy
(Nedelec et al., 2013; Venter, 2014). Sleep regulates numerous physiological and
psychological functions that influence recovery (Nedelec et al., 2015b). Examination
regarding the impact of sleep deprivation has informed much about the function of sleep
(Nedelec et al., 2015a) and its relevance to recovery (Halson, 2008). The degree to which
sleep patterns are disturbed is related to physiological alterations that can affect
performance and adaptation (Halson, 2008). Several theories have been proposed
regarding the function of sleep (Frank, 2006), including the neurometabolic theory, which
posits that sleep assists in the restitution of the nervous and metabolic cost imposed by the
waking state (LeMeur et al., 2013). Sleep deprivation has been shown to delay glycogen
repletion (Skein et al., 2011) speculatively due to prolonged wakefulness and therefore
further energy expenditure (Skein et al., 2011; VanHelder & Radomski, 1989). The
hindered resynthesis of depleted muscle glycogen following high-intensity exercise
resulted in lower glycogen concentrations the next day compared to controls, which may
have negatively impacted subsequent intermittent sprint performance (Skein et al., 2011).
Additionally, sleep is theorized to elicit a restorative effect on the immune and endocrine
systems (Halson, 2008; VanHelder & Radomski, 1989). Fragmented sleep was associated
with an elevated pro-inflammatory cytokine response (IL-6, IL-1β, TNF-α) during an
intensive training period in competitive rowers (Main et al., 2010) and heightened CK and
CRP concentrations during the course of recovery in rugby league players (Skein et al.,
2013). Irwin et al. (2006), who demonstrated similar results in the morning following a
sleepless night, suggested that the intensified inflammatory response was mediated by the
nuclear factor κB inflammatory signaling system and through growth factor hormone
response pathways. Dattilo et al. (2011) suggested that sleep deprivation could elicit
reductions in insulin-like growth factor-1 and testosterone concentrations and increase
cortisol levels, thereby eliciting a catabolic state in which muscle damage and soreness are
manifested (Haack & Mullington, 2005) and muscle remodeling is impaired (Akerstedt &
Nilsson, 2003). In related findings, sleep restriction over several days has been shown to
lower muscle protein synthesis rates in recreationally trained males (Saner et al., 2020).
Collectively, disrupted sleep patterns can exacerbate EIMD and hinder adaptive
remodeling (Halson, 2008; Nedelec et al., 2015a, 2015b; Saner et al., 2020), which can
lower exercise tolerance (i.e., increased perceived exertion) (Fullagar et al., 2015),
decrease emotional well-being (Dinges et al., 1997), and increase injury risk (Milewski et
al., 2014).
Despite equivocal findings regarding its efficacy, recovery strategies may positively
affect sleep, which can have pronounced effects on psychophysiological functions believed
essential to the recovery process (Nedelec et al., 2015b). Although it is important to isolate
recovery strategies to evaluate their effects on recovery processes, investigation regarding
the interaction between recovery strategies and sleep is ecologically valid (Lovell et al.,
2013; Nedelec et al., 2013). According to Halson (2008), several different recovery
strategies may initiate sleep onset and decrease inflammation and DOMS – increasing the
quality of sleep. Accordingly, the use of CWI (15 min) and CG (3 hours post-training) in
conjunction with enhanced sleep hygiene was shown to improve sleep time (total time in
bed and minutes asleep) and increase time in play, stroke rate, and lower-body power and
reduce perceived exertion and fatigue following a twice daily, on-court training and matchplay sessions in highly trained tennis players (Duffield et al., 2014). Sleep duration was
largely affected by recommendations to improve sleep hygiene that included the
facilitation of a cool environment (~20°C) and the avoidance of light and electronic
stimulants (e.g., television, cellular phones, computers) 30 min prior to bed (Duffield et al.,
2014). Given that many athletes are vulnerable to regular disturbances in sleep (Leeder et
al., 2012b), there is value in educating them regarding the benefits of sleep and providing
them with individualized recommendations to enhance sleep hygiene so as to enhance
post-exercise recovery (Duffield et al., 2014; Nedelec et al., 2013). A summary of the
activities that will help enable good sleep is provided in Table 8.4.
Table 8.4
Practical recommendations to improve sleep
Schedule training
appropriately
Set intense training before 6 p.m.
Avoid early-morning training
Adapted from Le Meur et al. (2013) and Nedelec et al. (2015a, 2015b).
Maintain a consistent sleep
schedule
Set a regular bed and wake-up time, including on off-days
Participate in daytime activities and exposure to bright morning light on off-days
Nap briefly (i.e., 5–30 min) in the early afternoon and not during the morning or evening
Eat and drink appropriately Avoid large meals close to bedtime
Avoid caffeine after noon
Avoid alcohol
Avoid excessive water intake prior to bedtime
Maintain a bedtime routine
that promotes relaxation
Avoid exposure to bright light
Avoid electronic devices and television 30 min prior to bedtime
Take a warm shower or bath prior to bedtime
Avoid activities other than sleeping while in bed
Reduce noise
Ensure a cool room temperature (~20°C)
Have a comfortable bed
Manage
psychophysiological
stress
Employ recovery strategies to reduce soreness and enhance sleep quantity and quality
(e.g., cold-water immersion, contrast water therapy, whole-body cryotherapy)
Employ techniques to fall
and return to sleep
Assume a relaxed position while in bed
Focus on relaxation versus sleep
Remove the bedroom clock
Adapted from Le Meur et al. (2013) and Nedelec et al. (2015a, 2015b).
Conclusion
Although recovery strategies have been shown to lessen exercise-induced homeostatic
perturbations that can diminish acute function (Barnett, 2006), methodological
inconsistencies and inter- and intra-individual variations in response to, and the complex
nature of, EIMD (Clarkson & Hubal, 2002) may be responsible for differences in research
findings. These inconsistencies limit the practical recommendations that can be made
relating to a number of recovery techniques. In addition to accessibility and practicality,
recovery strategies are commonly preferred based on perception and past experience
(Crowther et al., 2017; Simjanovic et al., 2009), thus inherent bias may obscure the actual
effects (Sands, 2016). Nevertheless, the partiality for particular modalities should not be
disregarded despite equivocal findings and the potential for detrimental adaptive effects.
Stress-induced arousal, if persistent, can initiate a catabolic shift that athletes’ mood may
reflect (Anshel & Sutarso, 2007; Mujika et al., 2018). Essential to the resolution of arousal
is the reduction of stress via relaxation (Sands, 2016). As such, the inclusion or
withholding of preferential modalities may influence the stress response and therefore the
sensation of fatigue to preceding and subsequent exercise (Ament & Verkerke, 2009). As
psychological drives can underpin physiological mechanisms to initiate responses to
perceived homeostatic perturbations (St. Clair-Gibson et al., 2017), modalities may
enhance function because they positively influence subjective parameters (Sands et al.,
2016; Skorski et al., 2019). In summary, the astute and timely application of recovery
strategies may attenuate acute functional decrements via psychophysiological mechanisms.
Practical applications
When considering which recovery intervention to implement, practitioners should consider
the rocks, pebbles, and sand analogy to determine which intervention is most appropriate.
Once practitioners have decided on their “big rocks” of recovery they can use Figure 8.1 to
help determine when in the training cycle it is most appropriate to implement specific
recovery methods for their athletes.
Flow chart detailing factors to consider when determining the implementation of recovery
methods.
Whilst interventions to hasten recovery following exercise may disrupt some adaptive
processes (Chazaud, 2016; Peake et al., 2017b), inadequate recovery may affect the
quantity and quality of subsequent training sessions, hinder competitive performance, and
increase the chance for injury (Kentta & Hassmen, 1998; Soligard et al., 2016). Barnett
(2006) suggested that whilst sport-specific fitness is important, reducing fatigue and
improving post-exercise recovery will influence competitive success. Halson et al. (2014)
have provided two rationales that may inform practice. First, restorative strategies may
enable short-term intensive loading that could enhance training effects. Second, modalities
may be withheld and cycled during distinct training phases (Sands, 2016) to maximize
adaptive effects and lessen desensitization to certain techniques. Similar to exercise
programming, the prescription of recovery strategies is likely a trade-off in conflicting
demands (Zatsiorsky & Kraemer, 2006). Accepting this proposition, several factors should
be considered:
The prior training load (nature and extent of the exercise stimulus) should be assessed
in accordance with contextual factors (e.g., age, gender, training status, level of
performance, psychological profile) given its influence on acute and amassed fatigue
and therefore function (Mujika et al., 2018; Skorski et al., 2019).
The recovery intervention should consider the nature and extent of fatigue and the
time between training bouts or competition (and available resources) (Bieuzen, 2013).
Intervention may be contraindicated if there is adequate time for natural recovery
between exercise bouts (Skorski et al., 2019).
Consideration of the short- and long-term goals of the training session relative to the
individualized training plan is important. Withholding modalities during certain times
of year (e.g., general physical preparation period) or for certain athletes (e.g.,
reserves) may improve the adaptive response to particular modes of training (e.g.,
strength and hypertrophy) and enhance hormetic effects (Peake et al., 2015; Skorski et
al., 2019).
As psychological factors are important to performance, recovery strategies should
consider the athlete’s preference.
Recommendations for acute recovery
Several strategies, including water immersion therapy, compression techniques, and WBC,
have been shown to reduce perceived fatigue and hasten acute recovery via enhanced
circulation (directly or indirectly) to decrease inflammation, which is linked to DOMS
after EIMD (Appell et al., 1992; Barnett, 2006; Bishop et al., 2008; Sands, 2016). Among
compression techniques, massage can evoke a beneficial acute psychophysiological
response (Hemmings, 2000). However, CWI elicited comparable and greater
improvements in perceived fatigue and performance, respectively, 24 hours postcompetition (Delextrat et al., 2013). Additionally, CWI showed a larger average effect size
across studies for performance compared to massage (Poppendieck et al., 2013, 2016).
Custom-fitted CG, if worn immediately, and over successive days, following highintensity exercise can also enhance acute recovery (Brown et al., 2020), although CWT
more effectively attenuated soreness post-EIMD (French et al., 2008). Recurrent and
immediate post-exercise WBC may be useful to deter non-functional overreaching and
psychological perturbation as a consequence of concentrated loading (Schaal et al., 2015).
However, CWI more effectively reduced soreness, improved lower-body power, and
enhanced the perception of recovery at 48, 72, and 24 hours, respectively, compared to
WBC (Abaidia et al., 2016). Compared to CWI, CWT generally shows superior immediate
effects on fatigue after time trial, match, and damaging exercise (Bieuzen, 2013), whereas
CWI showed superior effects on performance and subjective measures at 24–72 hours
(Ingram et al., 2009). Accordingly, CWI elicited a significantly lower rating of perceived
fatigue over 4 days post-exercise (Bleakley et al., 2012). Additionally, cold exposure (e.g.,
CWI, WBC), along with recommendations to improve sleep hygiene, may initiate sleep
onset and improve sleep duration and quality (Halson, 2008), which has been shown to
support numerous physiological and psychological functions that may be essential to the
recovery process (Nedelec et al., 2015b). Given its accessibility and practicality in most
settings, CWI and CWT may be viable options to enhance acute recovery.
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9
Priming match-day
performance: strategies for
team sports players
Mark Russell, Natalie Brown, Samuel P. Hills
and Liam P. Kilduff
DOI: 10.4324/9781003044734-12
SECTION 1
Literature review
Depending on the sport and level of competition, team sport players may
commence competitive encounters anywhere between 09:00 and 11:00
(e.g., rugby 7s and academy football games) and 20:00–21:00 (e.g., elite
evening matches) local time. While start times are likely determined by
extraneous factors, including the demands of television (Drust et al., 2005),
athletes may experience changes in physical performance throughout the
waking day (Chtourou and Souissi, 2012; Teo et al., 2011a, 2011b). In
addition to the importance of appropriate non-match-day preparatory
strategies (e.g., tapered training, prior nutritional interventions such as
carbohydrate loading, etc.), a role exists for interventions performed on
match-day itself to acutely enhance subsequent performance (Kilduff et al.,
2013a; Russell et al., 2015b) and/or to offset any residual fatigue from the
training week or previous competition. This chapter provides practical
suggestions for modified practices regarding the match-day activities of
team sports players. Although not mutually exclusive, such strategies can
broadly be categorised as those which are implemented: (1) more than 3
hours before a match commences (e.g., prior priming exercises); (2) less
than 3 hours before a player’s pitch-entry (e.g., modified warm-up/rewarmup practices, ischaemic pre-conditioning [IPC], and hormonal priming); and
(3) during scheduled within-match breaks (e.g., half-time heat maintenance
strategies).
Strategies implemented more than three hours before a match
commences
Prior priming exercise
Testosterone (T) concentrations are positively related to indices of physical
performance deemed crucial to team sports performance, with positive
correlations existing between baseline T concentrations and indices of
muscular power production (Crewther et al., 2009, 2012a, 2012b; Cook and
Crewther, 2012a). Endogenous T may also be positively associated with
aspects of athletic behaviour related to motivation and confidence to
compete (Cook and Crewther, 2012b), and game-ranked performance
scores in rugby union players (Gaviglio et al., 2014). As T shows circadian
rhythmicity, with an early-morning peak followed by a transient decline
through the day (Kraemer et al., 2001; Teo et al., 2011a), offsetting this
circadian decline could benefit performance during sporting activities
performed in the afternoon or evening.
Resistance exercise can acutely raise T concentrations (Kraemer and
Ratamess, 2005), and may thus benefit subsequent competitive performance
if an event is commenced with elevated T. Ekstrand et al. (2013)
demonstrated that morning resistance exercise that included back squats
performed to failure and power clean exercises improved throwing distance
in well-trained shot-putters 6 hours later. Similarly, improved afternoon
performance was observed when rugby union players had completed sprints
(5 × 40 m) and whole-body resistance exercises (bench press and back
squat routines up to 100% of three repetition maximum values) 6 hours
beforehand (Cook et al., 2013b). Notably, the morning exercise attenuated a
circadian decline in T concentrations compared with a rested control
condition (Cook et al., 2013b). Such findings highlight a potential role for
specific modes of morning priming exercise to improve afternoon or
evening performance, and that such findings may be modulated by changes
in hormone status (Harrison et al., 2019).
Although the greatest benefits may be realised between 6 and 33 hours
after the priming stimulus, delayed effects could exist for 1–48 hours
following resistance exercise priming (Harrison et al., 2019). The literature
to date suggests that when progressively loading over multiple sets with
limited total volume, performing high-load (≥ 85% one repetition maximum
[1RM]) traditional resistance exercises or low-load (30–40% 1RM) ballistic
exercises may be the most beneficial for improving markers of strength,
power, and/or sprinting performance thereafter (Harrison et al., 2019).
However, acknowledging the practical considerations associated with the
pre-competition practices of professional team sport players, the methods of
morning exercise typically examined may preclude their use on competition
day. Whole-body resistance exercises, particularly if performed to nearmaximal load and/or momentary muscle failure, are unlikely to be tolerated
and routinely adopted in the pre-competition setting irrespective of potential
efficacy (Harrison et al., 2020). Such considerations may at least partly
explain the discrepant observations from high-performance sport
practitioners who indicated that they no longer used (30%) or had never
implemented (19%) prior priming exercise despite overwhelming support
from survey respondents (84%) who believed it was beneficial (Harrison et
al., 2020). Moreover, many practitioners also reported prescribing priming
strategies such as unloaded jumps, which although they are likely to be
better tolerated on match-day, have limited evidence supporting their
efficacy.
Russell et al. (2016) compared the effect of different, potentially more
feasible, methods of morning exercise on afternoon performance. Six 40-m
sprints (incorporating 180° changes of direction) performed ~5 hours before
subsequent exercise improved sprinting and jumping performance while
eliciting positive effects on salivary T compared with a passive control.
Additionally, upper-body resistance exercise augmented sprint performance
and elicited favourable T concentrations, whereas cycle sprints increased
countermovement jump performance. Such findings highlight a possible
role of priming methods that may be better accepted by players and coaches
on the day of competition and transfer to match-specific performance
indicators such as sprinting. Notably, 78% of practitioners surveyed by
Harrison et al. (2020) reported implementing some form of exercise on the
day of competition, a practice that could provide the opportunity to target a
priming response (e.g., by modifying existing field-based sessions) even if
heavy-resistance exercise is not possible or desirable.
The efficacy of priming for enhancing subsequent performance may vary
considerably between individuals, even when characteristics such as age,
mass, and strength are matched (Fry et al., 1995). Although Fry et al.
(1995) reported no overall performance improvements following resistance
exercises incorporating weightlifting derivatives, a group of ‘responders’
was identified for whom ~4.5–6.0% increases in jumping and weightlifting
performance were observed 5–6 hours after the priming session. Such
findings emphasise the importance of individualising match-day strategies
to optimise the preparations of any given player. Additionally, future
research opportunities also exist to explore the impact of prior priming
exercise on match-related key performance indicators.
Strategies implemented less than three hours before pitch-entry
Ischaemic pre-conditioning
Multiple bouts of skeletal muscle ischaemia (induced using a cuff or
tourniquet) interspersed with periods of reperfusion are known as IPC, a
practice that could acutely enhance muscle function when administered ~1–
2 hours before competition (Bailey et al., 2012; Jean-St-Michel et al., 2011;
Lisboa et al., 2016). These benefits may arise via mechanisms such as
increases in muscle blood flow resulting from changes in adenosine
concentrations and the function of intra-muscular adenosine triphosphate
(ATP)-sensitive potassium channels, improved oxygen delivery and
metabolite clearance, and/or potential increases in excitation–contraction
efficiency (de Groot et al., 2010; Pang et al., 1995).
With regard to athletic performance, IPC has produced improvements in
time to exhaustion (Crisafulli et al., 2011), anaerobic performance (Bailey
et al., 2012; Jean-St-Michel et al., 2011; Lisboa et al., 2016), and muscle
activation (Wilson et al., 2013b). Whilst not all studies implementing IPC
with regard to intermittent sports players have yielded positive results
(Gibson et al., 2013), inter-individual variability seems to exist and the
benefits of IPC may also be time-dependent. In support, Lisboa et al. (2016)
reported that the ergogenic effects of IPC (4 × 5-min bouts of occlusion at
220 and 180 mmHg for thighs and arms, respectively) manifested after a 2or 8-hour post-IPC recovery period, having been absent when IPC was
performed within 1 hour of subsequent exercise. Given such findings, it
could be notable that Cook et al. (2014) identified an occlusion-dependent
elevation in salivary T immediately following a resistance exercise session
that also utilised IPC. Although further research is required in this area, the
available evidence suggests that IPC could be used as a passive strategy on
the day of competition to improve subsequent physical performance, or
potentially in combination with prior resistance exercise to augment the
benefits of morning priming for attenuating circadian declines in T.
Hormonal priming
It is typical for key coaching messages to be delivered in pre-match talks
that outline tactical practices (<3 hours prior to competition) and aim to
motivate and instil confidence in players through the use of verbal
persuasion (<1 hour prior to competition), before being reinforced during
the team warm-up and the final 20 min before the start of competition.
Substitute players may also receive specific tactical information once the
match is under way whilst awaiting and preparing for pitch-entry. However,
the extent to which such practices influence a player’s performance remains
somewhat unclear.
When performed 75 min before a match, positive coach feedback
accompanying footage of a player’s successful skill execution has been
reported to benefit pre-game T concentrations and overall match
performance ratings (Cook and Crewther, 2012b). Conversely, cautionary
coach feedback and observing videos of an opponent’s success produced
larger cortisol (C) responses and inferior match-play performance. When
considered alongside observations that presenting highly trained males with
aggressive or intense training videos acutely raised T and improved 3RM
back squat performance 15 min later (Cook and Crewther, 2012a), these
findings suggest watching videos and receiving associated feedback could
influence hormonal and performance responses and provide a suitable
strategy for the preparation of team sports players before competition. In
the context of applied practice, it may be worthwhile including such
strategies during team briefings that often include the use of video footage
and performance analysis. Moreover, the foregoing data may suggest that
the environment to which substitute players are exposed (e.g., the state of
the game) prior to pitch-entry could influence their hormonal and/or
performance responses.
Modifying the warm-up
Increased intensity
The principal aim of a pre-match or pre-pitch-entry warm-up is to transition
players from a state of rest to a state of exercise readiness while minimising
accumulation of residual fatigue. Typical match-day warm-ups occurring
before kick-off often last between ~20 and 45 min, and begin with lowintensity activities including stretching and activation drills, before
progressing in intensity with the inclusion of sport-specific movement
patterns and technical/tactical drills (Towlson et al., 2013). However,
observations from beyond team sports suggest that warm-up intensity could
be modified in order to better enhance subsequent physical performance
(Cook et al., 2013a; Ingham et al., 2013). Changing warm-up exercise from
300 m of striding (6 × 50 m) to an equidistant bout of combined striding
(100 m) and race-pace running (200 m) enhanced subsequent 800-m
running performance by ~1% (Ingham et al., 2013), whilst a ~30% increase
in typical warm-up intensity improved mean 20-m resisted sprint
performance in elite bob-skeleton athletes (Cook et al., 2013a). Beneficial
effects on repeated sprint ability have also been observed in team sports
players following a warm-up that incorporated actions conducted above,
versus below, the anaerobic threshold (Anderson et al., 2014).
So long as tolerable limits are not exceeded (Bishop et al., 2001), it is
likely that increasing warm-up intensity may contribute to improved
exercise performance thereafter by inducing desirable physiological
responses (e.g., increases in body temperature) that are of a greater
magnitude than would be elicited from a lower-intensity warm-up. Whilst
the efficacy of such practices is yet to be confirmed with regard to more
prolonged competition durations (e.g., ≥45 min), and in a variety of
environmental conditions that may be faced on match-day (e.g., hot and
humid versus cold and dry), results of a systematic review highlight a
benefit to performing warm-up activities that reach ~90% of an individual’s
maximum heart rate for improving outcomes in isolated performance tests
of explosive team sports-specific tasks such as sprints and jumps (Silva et
al., 2018).
Protection of gains
A player’s own preferences (e.g., final kit and tactical preparations), prematch ceremonies (e.g., meeting with dignitaries, national anthems), and
specific rules and regulations (e.g., pitch protection policies or the use of
‘call rooms’) may result in a 10–20-min period that separates the end of the
warm-up and the start of competition. Notably, similar durations in
temperate conditions can elicit losses in body temperature with concomitant
declines in physical performance that largely negate the benefits of the
initial warm-up (Kilduff et al., 2013b; Russell et al., 2015a; West et al.,
2013b). These findings highlight the potential role for interventions that
attenuate such declines between warm-up cessation and onset of matchplay, both in the context of starting and substitute players entering a game.
Passive heat maintenance is a strategy that aims to minimise heat losses,
thus maintaining body temperature by applying specialised garments or
heating methods, and has shown efficacy in terms of body temperature
preservation and physical performance maintenance following active warmups (Kilduff et al., 2013b; West et al., 2016). For example, wearing a
survival garment during a ~15-min post-warm-up recovery period
attenuated core temperature losses by ~50% when compared with normal
training attire, while also benefitting lower-body power output and repeated
sprint ability in professional rugby league players (Kilduff et al., 2013b).
Additionally, combining passive heat maintenance with 3 × 5
countermovement jumps (20% body mass load) in the post-warm-up period
has provided further performance-protecting effects over either strategy
alone (West et al., 2016). These data highlight that the post-warm-up
transition period is an opportunity for practitioners to improve subsequent
performance by offsetting body temperature declines prior to kick-off. In
hot or humid conditions, combining lower-limb passive heat maintenance
with pre-cooling strategies such as ice slurry ingestion may preserve muscle
temperature while allowing core temperature to remain below a level that
could negatively affect performance (Beaven et al., 2018).
Although the precise timeframes for introduction may differ between
sports (e.g., depending on regulations and strategies), substitute players
typically face substantial delays between the end of the pre-match warm-up
and their entry on to the pitch. This extended period between the initial prematch warm-up and pitch-entry could allow further temperature and
performance decrements for substitutes compared with the ~10–20-min
transition experienced by members of the starting team (Hills et al., 2018,
2021; West et al., 2013b). For example, replicating the typical pre-pitchentry practices of soccer substitutes resulted in both core temperature and
indices of physical performance declining to pre-warm-up levels well in
advance of simulated second-half pitch-entry (Hills et al., 2021). Notably,
observations from professional soccer substitutes highlighted that
increasing the amount of rewarm-up activity performed prior to pitch-entry
appeared to benefit post-pitch-entry physical outputs and potentially
contributed to improved match scorelines compared with the
implementation of minimal rewarm-up activities that were akin to normal
practice (Hills et al., 2019, 2020). Practitioners should therefore consider
the unique demands of substitutes, as well as starting players, when seeking
to optimise match-day preparations relating to the warm-up.
Post-activation potentiation (PAP)
A muscle’s force production capabilities can be influenced by its recent
contractile history (Kilduff et al., 2008). As long as the mechanisms of
potentiation outweigh the residual effects of co-existing fatigue, performing
certain high-intensity contractions has the potential to acutely enhance
subsequent exercise performance via mechanisms including increased actinmyosin myofilament sensitivity to Ca2+, enhanced motor neuron
recruitment, and/or a more favourable central input to the motor neuron
(Tillin and Bishop, 2009; Wilson et al., 2013a) – a phenomenon referred to
as PAP and, more recently, post-activation performance enhancement
(PAPE). Acknowledging that PAP/PAPE may be modulated by the timing
of the intervention relative to subsequent exercise, alongside other factors
such as a player’s strength, training experience, or muscle fibre composition
(Hamada et al., 2003; Kilduff et al., 2008; Wilson et al., 2013a), this chapter
focuses on modifiable factors relating to the volume and type of preload
stimulus applied on match-day.
Most studies demonstrating PAP have employed moderate to heavy (i.e.,
60–95% 1RM) resistance exercise as the stimulus, with multiple sets
augmenting subsequent muscular power output to a greater extent than a
single set in trained individuals (Wilson et al., 2013a). However, similar to
the use of prior priming activities, practical considerations associated with
the pre-competition routines of team sports players mean that heavyresistance exercise is unlikely to be feasible immediately before a game.
Identifying alternative methods of inducing PAP that require less equipment
and/or might be better tolerated by players and coaches on the day of
competition is therefore appealing.
Ballistic activities such as weighted jumps are associated with the
preferential recruitment of type II motor units (Desmedt and Godaux,
1977), and may therefore be utilised as a PAP stimulus. Depth jumps are
able to increase subsequent strength (Masamoto et al., 2003) and explosive
performance (Hilfiker et al., 2007), while the use of isometric maximal
voluntary contractions can also induce PAP (Hamada et al., 2003).
Moreover, 3 × 3 ballistic bench throws at 30% 1RM improved upper-body
power output after an 8-min recovery period – improvements that were
similar in magnitude to those induced by a more traditional heavyresistance exercise bout (i.e., 3 × 3 bench press at 87% 1RM; West et al.,
2013a). A practical means of eliciting PAP within the constraints often
existing in team sports was examined by Turner et al. (2015), who observed
that 3 sets of 10 repetitions of alternate-leg bounding on an indoor surface
whilst wearing a weighted vest (incorporating 10% of body mass) improved
10- and 20-m sprint performance by 2–3% at 4 and 8 min post-bounding,
when compared with a walking control condition. Whether such responses
occur on surfaces more relevant to outdoor match-play (e.g., grass) remains
to be confirmed.
Regardless of whether ballistic or heavy-resistance exercise is used as a
preload, the optimal recovery time between stimulus and subsequent
performance appears typically to be ~7–10 min (Kilduff et al., 2008; West
et al., 2013a; Wilson et al., 2013a). Given the timeframe separating the end
of the warm-up and the match kick-off (i.e., typically >10 min), the benefits
of PAP could therefore be somewhat limited to the initial stages of a
player’s competition involvement. However, it has not yet been determined
whether the introduction of substitutes who have induced a PAP response
prior to pitch-entry (e.g., having performed targeted ballistic or isometric
exercises pitch-side) could subsequently influence markers of team sport
performance at varying stages of a game and/or whether PAP has promise
as a potential strategy for use at half-time or during other scheduled breaks
in play.
Strategies implemented during scheduled within-match breaks
(e.g., half-time)
Half-time typically includes players returning to the dressing room,
engaging in tactical discussion, receiving medical treatment, and consuming
nutritional ergogenic aids (Russell et al., 2015b; Towlson et al., 2013).
However, 20% of soccer players have their least intense 15-min period of a
match within the initial stages of the second half (Mohr et al., 2005) and
reductions in physical performance capacity are frequently observed
immediately after half-time compared with first-half values (Lovell et al.,
2013; Russell et al., 2015a, 2018). Half-time has therefore been proposed as
an opportunity to enhance subsequent performance (Russell et al., 2015b).
To avoid replication of information previously discussed, an overview of
studies reporting the specific use of half-time interventions now follows.
However, where practicalities allow, the aforementioned strategies (e.g.,
PAP, hormonal priming, etc.) may also wish to be considered at half-time as
well as during other scheduled breaks in play (e.g., quarter-time, drinks
breaks, before extra-time etc.).
Heat maintenance strategies
Muscle and core temperature may decline by >1°C during a 15-min passive
half-time (Lovell et al., 2013; Mohr et al., 2004), responses that were
related to decreases in physical performance capacity. As was the case postwarm-up, strategies to offset body temperature losses may represent
beneficial half-time interventions during matches played in temperate
conditions. For example, wearing a survival jacket throughout a 15-min
simulated half-time attenuated core temperature declines and better
maintained physical performance amongst professional rugby union players
compared with passive control conditions (Russell et al., 2015a, 2018).
Observed ergogenic effects notwithstanding, the logistics of passive heat
maintenance strategies must be considered in the context of applied practice
as some players (e.g., those receiving injury treatments) may be averse to
wearing additional clothing during half-time.
Alternative methods of heat preservation include short bouts of rewarmup activity. Seven minutes of moderate-intensity running commencing midway through half-time attenuated a 1.5°C reduction in muscle temperature
and offset the 2.4% decrements in mean sprint performance observed
during a passive control trial (Mohr et al., 2004). Beneficial body
temperature and/or physical performance responses (i.e., compared with a
passive half-time) have also been observed when rewarm-up activities
consisted of field-based agility exercise, resistance exercise, low-tomoderate-intensity jogging and calisthenics, or whole-body vibration
training (Edholm et al., 2014; Lovell et al., 2013; Zois et al., 2013).
Similarly, rewarm-ups that included sport-specific technical actions have
also been proposed to benefit subsequent skilled performances when
conducted during a ~15-min half-time period (Zois et al., 2013). Additive
effects of combining active rewarm-ups and passive heat maintenance have
also been demonstrated as ~8 min of wearing a survival jacket followed by
~7 min of jogging and ball skills produced more favourable temperature
and performance responses compared with either strategy alone (Russell et
al., 2018). That said, practitioners must consider the duration of half-time
activities performed with reference to players’ other half-time commitments
(e.g., tactical, medical, nutritional, etc.).
SECTION 2
Practical applications
Match-day itself provides opportunities to enhance competition
performance for team sports players (Kilduff et al., 2013a; Russell et al.,
2015b). Acute performance enhancements have been observed following
appropriate warm-ups, half-time and post-warm-up heat maintenance
strategies, IPC, hormonal priming, and prior priming exercise. As most
team sports competitions commence at times between 09:00 and 21:00, the
potential may exist for practitioners to combine several of these
interventions in pursuit of additive performance-enhancing effects.
Moreover, specific player populations may present their own unique
opportunities, such as the use of frequent rewarm-ups and/or PAP for
substitutes about to enter the field of play.
To understand the ‘windows of opportunity’ that may exist on matchday, it is important to contextualise current practice. A theoretical model of
the typical activities that may be performed by team sports players in the 12
hours before an away match (with overnight hotel stay), with a 20:00 kickoff (0 h), is presented in Figure 9.1. However, as the match-day practices of
professional sports teams are very often structured and rigid in nature, any
proposed modifications must complement existing protocols. Figure 9.1
presents a theoretical model of implementing the performance-enhancing
strategies outlined in this chapter to supplement existing practices.
Model of implementing the performance-enhancing strategies.
Summary
As the use of prior priming activities, a well-structured warm-up, and
appropriate post-warm-up, half-time, and pre-pitch-entry interventions have
each demonstrated performance benefits, a method which combines several
of these strategies whilst ensuring compatibility with existing match-day
routines might interest strength and conditioning coaches working with
team sports players. Acknowledging the constraints that often exist when
implementing modifications on match-day, a practical model that allows
combination of several interventions could theoretically elicit additive
effects over the use of any strategy in isolation.
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10 Fitness testing and data analysis
John J. McMahon, Paul Comfort and Anthony
N. Turner
DOI: 10.4324/9781003044734-13
Why fitness test?
Fitness-testing data should inform the strength and conditioning coach’s
decision-making process when developing and refining the athlete’s
training programme (Thornton et al., 2019). Conducting fitness-testing
batteries with an individual athlete or a squad of athletes provides
practitioners with an objective method of comparing, or monitoring changes
in, specific fitness qualities (e.g. strength, power, speed, etc.) that are key
performance indicators of the athlete’s sport. The specific fitness qualities
that are assessed as part of fitness-testing batteries should be determined
following a detailed needs analysis of the athlete’s sport, with, where
appropriate, consideration also given to different positional demands of the
sport. The results gleaned from fitness-testing batteries should be used to
inform the athlete’s upcoming training priorities and, if applicable, provide
insight into the success of the athlete’s previous training cycle(s). Fitnesstesting results should, therefore, be used by practitioners to facilitate the
construction of effective training programmes by identifying a given
athlete’s area(s) for improvement and highlighting what may or may not
have worked well for the athlete in the previous training cycle(s).
When to test
Fitness testing could initially take place at the beginning of the pre-season
training cycle, as the results of testing conducted at this time point would
provide a baseline of fitness data which will inform this initial training
block (based on identified strengths and weaknesses), and serve as a
reference point for data collected as part of further fitness-testing sessions
conducted throughout the remainder of the season. The fitness-testing
results obtained at the beginning of the pre-season training cycle would also
inform how much the athlete’s fitness has been compromised during the
preceding off-season period. However, it may be prudent to exclude certain
maximal-intensity fitness tests from the very beginning of the pre-season
training cycle to avoid unnecessary exposure to risk of injury after a period
of inactivity (i.e. the off-season). Instead, identifying an appropriate
window of opportunity for certain maximal-intensity fitness tests further
into the athlete’s training cycle may be preferable but the precise timing
would, of course, be team- and context-dependent (Buchheit and Brown,
2020). The latter approach could also be a solution for all fitness tests when
working with athletes who compete in a sport that does not incorporate a
specific pre-season period (e.g. combat athletes).
Where possible, the same fitness-testing battery would initially be
conducted twice (typically interspersed by a 5–7-day gap) at the beginning
of pre-season, or an alternative appropriate window of opportunity, in order
for the standard error of measurement (SEM) of each test to be established.
This would ensure that the within-subject variability of each fitness test
parameter is known for each athlete tested. The SEM can be used to inform
the practitioner of what a meaningful change in each fitness parameter
would be for a given athlete or squad of athletes and thus will help the
practitioner to identify ‘meaningful’ changes in a particular test score in
subsequent fitness-testing sessions. If it is not appropriate or feasible to test
the athlete(s) twice in fairly quick succession (i.e. after 5–7 days), and thus
for athlete/squad-specific test measurement error to be established, then
practitioners should use published (preferably sport-specific) test SEM
values to help them identify meaningful changes in subsequent
performance. The readers are referred to a relatively recent review article
and the associated supplementary digital materials for an excellent
overview of determining SEM and applying it to determining meaningful
performance changes (Swinton et al., 2018).
After testing at least once at the beginning of the pre-season training
cycle, or an alternative appropriate window of opportunity, the scheduling
of subsequent fitness-testing sessions will vary from sport to sport,
depending upon several factors such as the duration and scheduling of the
season. Generally, however, practitioners should at least aim to fitness test
athletes again at the end of the pre-season training cycle, or an alternative
appropriate period, so that athletes’ level of preparedness for competition
can be benchmarked against published/squad normative data (see Chapter
11 for information on how to go about this) and compared to the fitness test
results gathered during the previous fitness-testing session (i.e. to inform
the magnitude of improvement/decline in each assessed fitness quality).
Preferably, fitness testing will take place at some point within the
competitive season (particularly for sports whose season includes a break
from competition) to assess the physical demands of competition on
athletes’ fitness characteristics. If this is not possible then an alternative
solution could be to select one or two key fitness tests (e.g. the vertical
jump) to conduct on a frequent basis as part of continual athlete-monitoring
procedures.
Although fitness-testing scheduling throughout the season may vary
between sports, it should be conducted when athletes are ‘rested’, i.e.
sufficient time [~48 hours] must have lapsed after the last
competition/intense training session. Additionally, when periodic fitness
testing does take place, athletes should be tested at approximately the same
time of day to account for circadian rhythms and body temperature, which
impact several physical and morphological qualities such as muscle strength
(Gauthier et al., 2001; Teo et al., 2011), power output (Teo et al., 2011;
West et al., 2014) and tendon stiffness (Onambele-Pearson and Pearson,
2007; Pearson and Onambele, 2006).
Test selection
Once a rationale for conducting fitness testing has been determined and the
appropriate timing of fitness testing has been identified, it is important to
decide upon which test(s) to conduct. Strength and conditioning coaches
now have an overwhelming number of choices when it comes to deciding
which tests to conduct with their athletes (Gabbett et al., 2017).
Fundamentally, they must ask themselves what they hope to gain from
conducting the testing (Gabbett et al., 2017). With respect to recoverymonitoring test selection, practitioners working in soccer suggested that
practically employable and cost-effective (time and finance) monitoring
tools, which provide meaningful data, are most useful for guiding player
preparedness decisions (Harper et al., 2019). Ultimately, fitness test
selection will depend upon the previously identified demands of the sport
(as achieved through conducting an evidence-based needs analysis) and, if
applicable, will consider position-specific physical requirements.
Other factors, such as the athlete’s age and training status, should also be
considered when determining appropriate test selection. For example, a
commonly used and widely accepted measure of ascertaining an athlete’s
maximal dynamic strength capacity is the one repetition maximum (1RM)
test. This type of test requires athletes to perform up to five single-repetition
sets (after an appropriate warm-up) of a given exercise with a gradually
increasing load until an incomplete attempt occurs (Baechle et al., 2008).
The penultimate repetition (i.e. the last successful lift achieved) is then
considered to be the athlete’s 1RM load for that exercise. It may, however,
be deemed inappropriate to conduct a 1RM test with weaker or beginner
athletes. In this case, a 3RM or 5RM test of dynamic strength might be
more appropriate, assuming the athlete can perform the selected exercise
with correct technique, as it has been shown that the load lifted in these
multiple repetition tests of dynamic strength can be used to predict the 1RM
load (Reynolds et al., 2006). It should be noted, however, that the ability to
accurately predict 1RM loads from multiple-repetition tests of strength
depends upon the exercise used (Hoeger et al., 1990; Shimano et al., 2006)
and so this should be considered in advance of testing. It is worth noting,
however, that the 1RM power clean test, which requires a higher degree of
technical competency than commonly tested compound exercises such as
the back squat, has been shown to be reliable even in youth (Faigenbaum et
al., 2012) and inexperienced collegiate (Comfort and McMahon, 2015)
athletes, following a sufficient period of familiarisation, with a smallest
detectable difference of ~5%.
When an athlete does not demonstrate correct exercise technique at high
loads but determining maximal strength for the athlete is deemed to be a
requirement, then performing a multi-joint isometric ‘strength’ assessment,
such as the isometric squat or mid-thigh pull, could be a suitable option.
Isometric strength tests require minimal familiarity (providing that the
athlete is familiar with the dynamic performance of the associated task and
puts in maximal effort during each repetition), skill and time when
compared to dynamic strength tests, which arguably makes them better
suited to testing both beginner/weaker individuals and groups of athletes.
These factors also enable multi-joint isometric tests to yield high reliability
and low variability values (Blazevich et al., 2002; Comfort et al., 2015;
Dos’Santos et al., 2016; Haff et al., 2015; Thomas et al., 2015), thus
increasing the sensitivity of these tests for detecting ‘meaningful’
performance changes. Additionally, strong associations have been reported
between isometric and dynamic strength tests (Comfort et al., 2019), which
means that the values derived from isometric strength tests can be used to
inform dynamic load prescription for a given training cycle by applying the
relevant prediction equation (De Witt et al., 2018). A limitation of isometric
strength tests, however, is that they require a force platform, which,
although cheaper validated force platforms are now available (Lake et al.,
2018), could restrict accessibility for some athletes, and the capacity of
fixing a barbell at the required position (i.e. a custom rig or power rack).
However, strain gauge alternatives have been shown to be valid and
reliable, albeit that only peak force can be assessed in most cases (James et
al., 2017).
In addition to isometric tests offering a suitable alternative to dynamic
1RM testing, recent studies have shown that 1RM values attained in a range
of bench press (Bosquet et al., 2010; García-Ramos et al., 2016a; Jidovtseff
et al., 2011) and squatting derivatives (Bazuelo-Ruiz et al., 2015; Conceição
et al., 2016) can, in most cases, be almost perfectly predicted from the
barbell velocity measured using a linear position transducer during these
exercises performed with submaximal loads (and applying the relevant
prediction equations). This approach, like some of the other approaches
discussed earlier, may help to overcome the potential for safety/injury risk
issues associated with 1RM testing of beginner/weaker athletes. Similar to
isometric strength tests and equipment, linear position transducers have
been shown to yield valid and highly reliable measurements of system and
barbell velocity, which enables this method to be compared to gold-standard
methods of assessing velocity (e.g. force platforms if measuring system
velocity) and used to detect performance changes (García-Ramos et al.,
2016b; Garnacho-Castaño et al., 2015; Giroux et al., 2015). It is worth
noting, however, that these predictions tend to be less reliable than direct
measures, meaning a greater magnitude of change is required to identify a
meaningful change.
Maximal sprint performance is highly regarded as an important
determinant of performance in many sports, but the distances over which
maximal sprint performance should be assessed will depend on the typical
sprint distances covered during competitive sport play and preferably,
position-specific sprint distances should be considered. Similarly, if jump
testing is deemed to be important to include within a testing battery for a
given sport, then attention should be given to the type(s) of jumps
performed in competition. For example, are the jumps performed in the
sport usually performed unilaterally or bilaterally, with or without a
countermovement, with or without arm swing, vertically or horizontally?
Each of these factors should be considered when deciding upon the type(s)
of jump test(s) to conduct.
There are also other reasons why specific jump tests may be selected as
part of the fitness-testing battery, even if they are not commonly performed
as part of the athlete’s sport. For example, the squat jump (SJ) might be
tested along with the countermovement jump (CMJ), even if the former is
not typically performed as part of the sport, simply in order to provide an
indication of how well an athlete can utilise the stretch-shortening cycle
(SSC). As such, an eccentric utilisation ratio (EUR) can be calculated (EUR
= CMJ height ÷ SJ height), with a ratio of >1.0 demonstrating that the use
of the SSC results in a greater jump height; however, if the ratio is ≤1.0 the
SSC needs to be developed (McGuigan et al., 2006). It should be noted that
the EUR can be influenced by differences in the distance through which the
athlete’s centre of mass moves from the bottom of the squat (or
countermovement) to take-off. Thus it would be prudent to report
propulsion displacement, as it is commonly referred to, alongside EUR
results to aid interpretation (McMahon et al., 2021). In summary, fitness test
selection will be informed by both the typical demands of the sport and the
general athletic qualities that underpin these demands.
Equipment selection
Once it has been decided which test(s) will be conducted, the next step is to
decide which equipment to use for the selected test(s). Ideally, the goldstandard equipment for testing each fitness quality should be used where
possible; however, this may be unrealistic from both an accessibility and
time perspective for many practitioners. An example of the latter is that
although some practitioners working with a team sport may have access to
expensive direct gas analysers for measuring maximal aerobic capacity, it
would take a very long time to assess a full squad on this parameter.
Instead, practitioners should consider using alternative equipment that has
been validated against the currently considered gold-standard equipment
when access to the latter is either impossible or unrealistic. In referring back
to the aforementioned example of measuring maximal aerobic capacity,
basic equipment such as cones, a measuring tape and an audio device could
be used to conduct the yo-yo intermittent recovery test (YIRT) or multistage fitness test (MSFT), which have both been shown to provide a valid,
field-based alternative to direct gas analysis (Krustrup et al., 2003;
Ramsbottom et al., 1988).
In terms of quantifying jump performance, a force platform is
considered to be the gold-standard equipment (García-López et al., 2013),
particularly when using the take-off velocity method of calculating jump
height (Moir, 2008), but similar to direct gas analysers, force platforms may
be inaccessible for some practitioners due to their general cost, despite
cheaper commercial force platforms now being available. In recent years,
however, many cheaper alternatives (that calculate jump height using the
flight time method) have been validated. For example, optoelectronic
systems have been shown to yield similar jump height values to those
attained using a force platform (García-López et al., 2013; Glatthorn et al.,
2011). Jump mats have generally been shown to yield inaccurate but
reliable measurements of jump height (García-López et al., 2013;
McMahon et al., 2016a; Nuzzo et al., 2011), meaning that their values can
be easily and correctly converted through published equations (GarcíaLópez et al., 2013; McMahon et al., 2016a). It is worth taking into
consideration that the accuracy of jump height values attained from jump
mats depends on the type of jump being performed and the level of
performer, with lower accuracy seen for short-contact jumps such as the
drop jump (Kenny et al., 2012) and for athletes who can jump very high
(Whitmer et al., 2015). An even cheaper alternative method of measuring
jump height from flight time is through smartphone applications, with jump
height attained using the My Jump app, for example, showing almost
perfect agreement with values attained from a force platform (BalsalobreFernández et al., 2015). It must be noted here that the flight time method of
calculating jump height is prone to errors when compared to the take-off
velocity method (Moir, 2008; Yamashita et al., 2020) due to, for example,
tucking of the legs during the flight phase and so standardising the
instructions given to athletes regarding the flight phase of the jump is
especially important when assessing jump height in this manner (see the
‘Standardising protocols’ section, below, for more information).
Fully automatic timing systems, such as those used at international
athletics events, are considered to be the gold-standard equipment for
measuring linear sprint speed (Haugen and Buchheit, 2016; Haugen et al.,
2012b). These systems are, however, very expensive and impractical for
most practitioners to utilise (Haugen and Buchheit, 2016). Due to this,
several alternatives of varying practicality have been suggested in the
literature, such as electronic timing gates, laser guns and high-speed
videography (Haugen and Buchheit, 2016). Of these suggestions, electronic
timing gates are perhaps the most practical in terms of accessibility and
speed of data processing and thus are frequently used in both research and
applied settings (Haugen and Buchheit, 2016). The accuracy of sprint times
recorded by electronic timing gates does, however, depend on several
factors, including the type of photocells used (e.g. single- versus dualbeam). Unlike single-beam electronic timing gates (Earp and Newton,
2012; Haugen et al., 2014), dual-beam electronic timing gates have been
shown to reduce the likelihood of an athlete’s arms or legs breaking the
beams, rather than their hips, as is preferred (Yeadon et al., 1999).
Nevertheless, single-beam electronic timing gates are still commonly used
in both research and applied settings (Carr et al., 2015; Dos’Santos et al.,
2017), possibly due to them being cheaper to purchase (Earp and Newton,
2012), and they have been validated against fully automatic timing systems
(Haugen et al., 2012b). Split-beamed and post-processing timing gates are
also available for use, although the errors in sprint times attained by splitbeamed timing gates are similar to those measured via single-beamed
systems (Haugen et al., 2012a, 2013) and the test–retest reliability of postprocessing timing gates is currently unknown (Haugen and Buchheit, 2016).
Although gold-standard equipment can provide more detail about each
fitness characteristic, in reality, the type of equipment selected by
practitioners to test specific fitness qualities depends upon accessibility,
feasibility and affordability. Whether using gold-standard equipment or
validated alternatives, it is vitally important to understand the associated
SEM to allow accurate decisions to be made regarding training adaptations
(this is discussed in more detail in Chapter 11). As some validated
equipment alternatives of a similar cost have larger measurement error than
others, it would be prudent to choose the alternative equipment that has the
highest degree of accuracy.
Another important consideration when selecting equipment for testing
certain fitness characteristics is sampling frequency capability. For example,
if assessing vertical jump height using a force platform, it has been
suggested that a minimum sampling frequency of 1000 Hz should be used
(Owen et al., 2014; Street et al., 2001). On the other hand, a sampling
frequency range of 500–2000 Hz had no effect on force–time variables
assessed during the isometric mid-thigh pull (Dos’Santos et al., 2019).
Alternatively, it has been recently suggested that the minimum sample
frequency of linear position transducers for yielding quality movement
velocity data is 25 Hz and that sampling above this frequency does not
improve recording precision and may, if an excessively high sample
frequency is selected, have adverse effects on data quality (Bardella et al.,
2017). Each of these factors should be considered in order to inform the
best equipment choice for a given purpose and budget.
Standardising protocols
Another very important factor to consider as part of the fitness-testing
process is the standardisation of protocols for the test(s) to be conducted, as
this will affect the reliability, variability and comparability of the data
collected. For dynamic strength tests, the standardisation required might be
as simple as ensuring correct barbell placement (e.g. high or low barbell
position in the back squat; Wretenberg et al., 1996), the range of motion
(e.g. squat depth) is consistent (Bryanton et al., 2012) and athletes put in a
maximal effort. The latter point is, indeed, a requirement of all maximalintensity fitness tests. Additionally, the rest period prescribed between trials
may affect the results gathered. For example, during 1RM back squat
testing, there were no significant differences in the ability to lift a maximal
load when subjects were given 1, 3 or 5 minutes’ rests between lifts
(Matuszak et al., 2003), although a greater percentage of the subjects lifted
successfully after the 3- versus the 1-minute rest period (76 versus 94%),
suggesting that a minimum of 3 minutes’ rest should be prescribed between
1RM attempts. Therefore, adequate test-specific rest periods should be
prescribed between recorded trials to improve test accuracy.
For jump tests, many factors need to be standardised to glean consistent
data. For example, when jump testing it is important to consider whether or
not athletes are permitted to swing their arms, as this has been shown to
augment jump height (Hara et al., 2006, 2008; Walsh et al., 2007) but
slightly reduce measurement reliability (Markovic et al., 2004). Also, the
range of motion (e.g. countermovement or starting depth) (Gheller et al.,
2015; Kirby et al., 2011; McBride et al., 2010) and movement/contact time
(Arampatzis et al., 2001; Walsh et al., 2004) will influence the resultant
jump height and associated force–time variables, if using a force platform.
This highlights the importance of being clear and consistent with the
coaching cues used (e.g. ‘jump as fast and as high as possible’) when jump
testing athletes (Louder et al., 2015; McMahon et al., 2016b).
Sprint testing typically has even more methodological factors than
strength and jump testing that need to be standardised. For example, the
accuracy of sprint times recorded by electronic timing gates will depend
upon the height at which they are set up (Cronin and Templeton, 2008;
Yeadon et al., 1999), the starting distance from the first beam (Haugen et
al., 2015; Altmann et al., 2015) and the starting stance (Frost and Cronin,
2011; Frost et al., 2008; Johnson et al., 2010). Thus, the standardisation of
protocols can relate both to the equipment setup and the instructions given
to the athlete. Both should be ‘optimised’ to increase the quality of the
collected data.
Testing order
The order of testing is largely dictated by the amount of recovery required
following a given test and so usually baseline measurements of height,
mass, body composition and range of motion would be performed first,
followed by skill- and/or speed-based tests (jumps, change of
direction/agility and sprints), then maximal-strength tests (dynamic or
isometric) and finally, muscular endurance and/or aerobic capacity tests. In
reality, the order of fitness testing will depend upon time/equipment
availability and the number of athletes being tested and so a ‘round-robin’
approach might be adopted by practitioners when larger groups of athletes
are being tested in a single session. If this is the case, then the testing order
for a given athlete should remain the same in subsequent testing sessions
and, ideally, the aerobic capacity tests should be performed last by all
athletes. The latter is much more feasible when the YIRT or MSFT is
conducted in a large space, allowing several athletes to be tested at the same
time. Of course, these recommendations for order of testing assume that all
fitness tests will be conducted within a single testing session or day but, as
mentioned earlier, there may be differing windows of opportunity for
conducting certain maximal-intensity fitness tests which will be determined
on an individual sport and context basis.
Data analysis
After all testing has been completed, at least some (if not most) of the data
will need to be processed, as most equipment/software does not provide
instantaneous results. Like the testing protocols, the way in which data are
analysed post-testing will also greatly influence the accuracy, reliability and
variability of the results. The analysis of force–time data is probably the
main type of commonly collected data that varies most between published
studies and, most likely, in practice. Thus, the standardisation of force–time
data analysis is of paramount importance to allow for accurate
interpretation of these data. For example, when analysing vertical jump
force–time data, the method of determining bodyweight and the thresholds
used to identify the onset of movement and the instants of take-off and
touchdown will greatly influence factors such as jump height and reactive
strength index modified, in addition to variables calculated through forward
dynamics procedures such as velocity and power (Eagles et al., 2015; Owen
et al., 2014; Street et al., 2001). Additionally, correctly identifying the
beginning and end of the braking (if a countermovement is included) and
propulsive phases of the vertical jump (Figure 10.1) is important for
ensuring correct calculations of several variables in each of these phases
(McMahon et al., 2018), including mean and peak force, time to peak force,
rate of force development and impulse. Analysing rate of force
development attained in the isometric mid-thigh pull at predetermined time
bands rather than as an average between the onset of force production and
peak force has been shown to be superior from a reliability perspective
(Haff et al., 2015), which further justifies standardisation of the analysis of
force–time data for specific tests.
Example of correctly identifying the unweighting, braking and propulsive
phases of a countermovement jump force–time curve (solid grey line) by
overlaying the velocity–time curve (dotted black line). The dotted grey line
represents zero centre of mass velocity.
Another consideration when analysing force–time data is how much
detail is wanted from the data. For example, only gross measures of a given
performance (e.g. mean and peak values of force and related data) are
typically reported and compared between fitness-testing sessions, whereas
comparing performance data sampled throughout the entire movement
(which is typically referred to as a temporal phase analysis or statistical
parametric mapping) can yield far more detailed information about how
performances/changes in performances are achieved. Indeed, the latter
approach has been shown to provide detailed information about
neuromuscular fatigue in the countermovement jump (Gathercole et al.,
2015), the effect of external load on jump squat performance (Cormie et al.,
2008), the effect of weightlifting derivatives on expressions of force
(Suchomel and Sole, 2017) and differences in neuromuscular function
between senior and academy rugby league players (McMahon et al., 2017).
Even if a full temporal-phase analysis is considered to be too complex,
there is an often underutilised abundance of additional variables that can be
calculated from force–time data, with just a basic understanding of forward
dynamics procedures, that can further inform practitioners of their athletes’
capacity.
To conclude, the standardisation of data analysis is very important and
must be applied consistently within and between testing sessions. Where
possible, the criterion method (e.g. Owen et al., 2014) for analysing a
particular dataset should applied. If a criterion method has not yet been
established for analysing a given dataset or if certain equipment is used that
provides instantaneous results via undisclosed data analysis methods, then
practitioners should at least be consistent and transparent with their data
analysis procedures. When comparing data collected through fitness-testing
batteries to the normative data from published studies, practitioners should
pay particular attention to the methods of data analysis employed in those
studies before forming their conclusions. Another point to consider is the
normalisation of strength and kinetic data for body mass (or employing
other appropriate scaling techniques such as those that consider body height
and fat-free mass) before comparing these results between sessions and
athletes, and to published studies, as these data in particular are largely
influenced by an athlete’s size (Folland et al., 2008).
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11 Analysis and presentation of
fitness test results
John J. McMahon, Anthony N. Turner and
Paul Comfort
DOI: 10.4324/9781003044734-14
Introduction
There is no ‘gold standard’ or ‘one size fits all’ method of analysing and
presenting results of fitness tests to key members of an athlete’s
training/performance team (McMahon and Mundy, 2018). Instead, the
precise method(s) of analysing and presenting fitness test results that best
suits the team you are working with will likely be determined based on
several factors. For example, it is important to remember that sports
coaches are unlikely to be statistically trained (Robertson et al., 2017) or
have the time available to synthesise text-dense written reports, which will
make them less impactful (Buchheit, 2017). Therefore, it is of paramount
importance to present fitness test results to sports coaches in an intuitive
(i.e. by avoiding complicated numbers or scientific terms) and visual format
(McGuigan et al., 2013; Buchheit, 2017; Lockie et al., 2018).
The exact method of analysing and then visually presenting fitness test
data may vary slightly depending upon the individual preferences of the
audience to which the fitness test results will be presented (Buchheit, 2017;
Robertson et al., 2017). The number of fitness test results to be included in
the report will also be considered. Ultimately, it is likely that different
modes of visually impactful presentation of performance test results will be
employed by strength and conditioning coaches, depending upon the target
audience and relative priority (i.e. urgency) of results. With the above in
mind, this chapter will explore some of the different fitness test result
analysis methods and visual formats in which key data may be presented to
athletes and the key members of their training/performance team. The
chapter begins with data analysis options, followed by data presentation
options in which applied case-study examples are provided.
Data analysis
Including several fitness tests as part of athlete fitness-testing batteries
results in the accumulation of many different types of data. Most of these
data, once analysed, will be reported with different units of measurement.
Some of these data and their units of measurement are relatively easy to
understand, such as change-of-direction time reported in seconds (s) and
jump height reported in metres (m) or centimetres (cm). However, other
fitness test data, such as isometric peak force reported in Newtons (N) and
sprint momentum reported in kilograms-metre per second (kg·m/s), are less
intuitive. Similarly, several variables with different units of measurement
can be reported from a single test, such as when the countermovement jump
test is performed using a force platform. To overcome the difficulty of
presenting several fitness test results, with many different units of
measurement, to athletes and coaches, one may benefit from reporting
standardised data presented on an intuitive scale. In this section, different
options on how to convert fitness test result data to a standardised form and
how to compare athletes’ performances to the squad mean score are
introduced.
z-scores
A z-score (sometimes referred to as a standard or standardised score)
represents how many standard deviations an individual athlete’s test score is
from the mean test score (usually the squad mean when applied in teamsport settings). It is calculated using the following formula (McGuigan et
al., 2013; Lockie et al., 2018):
z-score = (the individual athlete’s test score – the squad mean
[average] test score) ÷ the squad standard deviation for the test score
Applying the above equation, if a rugby athlete acehived a vertical jump
height of 42 cm and their squad attained a mean ± standard deviation
vertical jump height of 36 ± 4 cm, the z-score would be 1.5. In other words,
the athlete achieved a vertical jump height score that was 1.5 standard
deviations higher (i.e. better, in this example) than the squad mean score.
The first assumption of the z-score calculation is that the squad mean
and squad standard deviation values for the fitness test score are normally
distributed. This can be assessed via a test of normal data distribution such
as the Shapiro–Wilk test. The second assumption of the z-score calculation
is that the sample size (i.e. number of individual athlete’s data) from which
the squad mean and standard deviation are derived is ≥30 (Turner et al.,
2019). Additionally, it is important to select an equivalent time-period from
which the squad mean and standard deviation for each fitness test score
were calculated (Thornton et al., 2019). For example, one should compare
an athlete’s pre-season test score to the squads’ current or pooled-historic
pre-season test score, as one may expect fitness test scores to vary across
different phases of the sport season.
When calculating z-scores, it is worth remembering at this point that
~68%, ~95% and ~99.7% of normally distributed values attained for a
given fitness test will fall within 1, 2 and 3 standard deviations of the mean,
respectively (Figure 11.1). Therefore, most z-scores range between −3 and
3, accounting for ~99.7% of normally distributed values (Turner et al.,
2019). A z-score of −3 may be assumed to be undesirable as it represents a
result that is 3 standard deviations below the mean score, but for some
fitness test results, such as the time taken to complete a linear sprint or
change-of-direction task, a negative z-score is preferable (because this
would represent a faster performance in those tests). To avoid possible
confusion caused by this, it has been suggested that absolute z-scores (i.e.
positive z-scores for positive outcomes) should be presented for all
performance test results (Pettitt, 2010; Lockie et al., 2018). Therefore, from
this point forward, the reader is to assume that a positive z-score reflects a
better performance with the opposite being true for negative z-scores,
unless otherwise stated.
A typical normal data distribution curve with z-scores and the corresponding
percentage of data that they comprise.
The z-score can be calaculated for all fitness test results, which
overcomes the aforementioned difficulties associated with reporting several
fitness test results that contain many different units of measurement.
Furthermore, it has been suggested that a total score of athleticism (TSA)
can be calculated for athletes by calculating the average of the z-scores
attained for a range of fitness tests (Turner et al., 2019). The TSA is said to
provide insight into how ‘well rounded’ athletes are with respect to the key
fitness tests associated with their sport. The TSA can be used as an
alternative or an accompaniment to presenting individual test scores for
every single test performed, with the individual test data used to identify
key training priorities. As an example, the earlier example of the rugby
athlete’s z-score of 1.5 for vertical jump height has been added to Table
11.1, along with z-scores for other performance test results and the TSA.
The athlete, whose data are shown in Table 11.1, demonstrated superior
vertical jump and relative strength ability (as denoted by positive z-scores)
but inferior short sprint and absolute strength ability (as denoted by
negative z-scores) compared to the squad mean. However, on balance, the
athlete compared averagely overall within the squad, as denoted by the TSA
of zero (Table 11.1). This highlights the importance of inspecting the
individual z-scores that comprised the TSA calculation, as it can be
achieved in several ways (i.e. consistent z-scores for each test that are close
to the TSA value, or several high and low z-scores that are not aligned with
the TSA value).
Table 11.1 Example performance test results, corresponding z-scores and total score of athleticism
Sprint test
5-m time (s)
10-m time (s)
Athlete’s result
1.18
1.88
Squad mean
1.07
1.81
Squad standard deviation
0.07
0.08
z-score
−1.5
−1.0
Vertical jump test
CMJ height (cm)
CMJ, countermovement jump; SJ, squat jump.
SJ height (cm)
Sprint test
5-m time (s)
10-m time (s)
Athlete’s result
42
38
Squad mean
36
35
Squad standard deviation
4
6
z-score
1.5
0.6
Isometric mid-thigh pull test
Peak force (N)
Rel. peak force (N/kg)
Athlete’s result
3630
42
Squad mean
3667
38
647
6
Squad standard deviation
z-score
Total score of athleticism
−0.1
0.7
0.0
CMJ, countermovement jump; SJ, squat jump.
Modified z-scores
The term modified z-score yields similar information to the traditional zscore presented above, but can have different meanings. For instance, the
term modified z-score can be used to indicate the replacement of the mean
with the median in its calculation. This modified z-score may, therefore, be
considered more robust than the standard z-score because it is less
influenced by outliers (extreme scores, as detected via a test of normal data
distribution) within a squad data set. This type of modified z-score can be
calculated using the following equation:
In addition to the above purpose, McGuigan et al. (2013) also used the
term modified z-score to describe the comparison of an individual athlete’s
fitness test result to a predetermined ‘benchmark’ mean and standard
deviation result for the same test using the following formula:
The predertermined benchmark mean and standard deviation may be
derived from peformance test results that have been publishsed in the
scientific literature (e.g. normative data). It is important to ensure, where
possible, that the benchmark data are derived from the same methods
employed to collect and analyse the athlete’s data, or to at least understand
the margin of error expected when comparing fitness test results obtained
via different methods before interpreting the results. For example, the just
jump system, which is used to quantify jump performance, has been shown
to overestimate jump height values but they can be converted to accurate
values (McMahon et al., 2016), which would need to be done before being
used for benchmarking purposes. There are benefits to comparing the
athlete’s data to benchmark data, not least the fact that comparing the
athlete’s data to the squad mean alone may under- or over-represent
athletes’ performances depending on the ability of the squad as a whole. For
example, an athlete may achieve a large z-score with respect to the squad
mean but their performance could be substandard when compared to
benchmark data if the squad mean score is below average or poor.
Alternatively, the mean squad performances in each test can be compared to
published normative data, rather than each individual athlete’s scores, and
the data interpreted with any differences to published norms in mind. It is
also worth being mindful that no athlete wants to be average and therefore
just because they achieve a performance in line with the mean of the squad,
or a specific benchmark, this does not mean that the performance is
sufficient.
More recently, the term modified z-score was used to describe the
comparison of within-athlete data between different testing occasions
(McGuigan, 2017). This alternative modified z-score can be calculated
using the following formula:
The above method helps to quantify the magnitude of improvement the
athlete demonstrated for each performance test between testing occasions. It
has been suggested that magnitudes of <0.20, 0.20–0.49, 0.50–0.79, ≥0.80
for standardized differences in means (e.g. z-scores) between testing
occasions can be interpreted as trivial, small, moderate and large,
respectively, much like when interpreting effect sizes (Cohen, 1988). Using
this scale can help to guide consistent use of language when communicating
such results to the athlete’s performance team or writing fitness test reports.
Given that the term modified z-score has been used to describe several
modifications to the traditional z-score equation, one should be transparent
with how modified z-scores have been calculated to enable them to be
accurately interpreted by others involved with the performance testing of
athletes. It could be argued, however, that z-scores do not produce the most
intuitive numbers or scale for athletes and coaches; thus we will now
discuss alternative options which may be superior to z-scores from an
intuition standpoint. We have also provided a conversion table to illustrate
how z-scores correspond to the alternative approaches discussed (Table
11.2).
Table 11.2 Corresponding percentile, standard ten (STEN) and t-score values for a given z-score
z-score
Percentile
STEN
t-score
5.0
100.0
10.0
100
4.5
100.0
10.0
95
4.0
100.0
10.0
90
3.5
100.0
10.0
85
3.0
99.9
10.0
80
2.5
99.4
10.0
75
2.0
97.7
9.5
70
1.5
93.3
8.5
65
1.0
84.1
7.5
60
z-score
Percentile
STEN
t-score
0.5
69.1
6.5
55
0.0
50.0
5.5
50
−0.5
30.9
4.5
45
−1.0
15.9
3.5
40
−1.5
6.7
2.5
35
−2.0
2.3
1.5
30
−2.5
0.6
0.5
25
−3.0
0.1
0.0
20
−3.5
0.0
0.0
15
−4.0
0.0
0.0
10
−4.5
0.0
0.0
5
−5.0
0.0
0.0
0
Standard ten scores
To make z-scores easier for coaches and athletes to understand, they can be
converted to a standard ten (STEN) score which allows them to be
presented on a scale of 1–10 (Thornton et al., 2019). As with z-scores, the
STEN score is derived from the typical bell-shaped curve of normally
distributed data (Figure 11.1), thus is it is important to check that the fitness
test data obtained from the squad or published source conform to this
assumption. The average STEN score is 5.5, thus the formula for converting
a z-score to a STEN score is shown below:
STEN scores are always rounded up, so a score of 9.5 would be rounded
up to 10. The conversion of typical z-scores to the corresponding STEN
score is presented in Table 11.2, where each STEN unit corresponds to 0.5
standard deviation. A potential benefit of converting a z-score to a STEN
score is that it removes the inclusion of negative numbers and it involves a
scale of values that is likely to be more intuitive to most coaches and
athletes (i.e. a performance scale of 0–10).
A potential limitation of STEN scores is that several upper- and lowerbound z-scores will share the same STEN score and so they distinguish a
relatively narrow range of performances. For example, a z-score of ≤ −3.0
and ≥ 2.5 will share a STEN score of 0 and 10, respectively (Table 11.2).
Therefore, while STEN scores may be more intuitive for coaches and
practitioners to understand than z-scores, some of the other alternatives
described below may be preferable.
t-scores
In a similar manner to STEN scores, t-scores avoid the use of small and
sometimes negative numbers and can be easily calculated from the z-score
using the following formula:
The conversion of typical z-scores to the corresponding t-score is presented
in Table 11.2, where each t-score increment of 10 corresponds to 1 standard
deviation. It has been suggested that t-scores, like STEN scores, are more
conventionally appreciated by coaches and athletes because they ‘rank’
fitness test data on a scale of 1–100 rather than, for example, a z-score
range of −5.0 to 5.0 (Turner et al., 2019). Turner et al. (2019) also highlight
that t-scores, if preferred to z-scores, can be calculated directly from the
fitness test score by using the following formula:
A different t-score calculation to the one presented above can also be
made if the sample size from which the squad mean and standard deviation
are derived is <30 and when the population standard deviation is unknown.
It is thought to be inaccurate to estimate the population standard deviation
from the sample itself (i.e. the standard deviation of the fitness test data
collected with a squad of athletes) when the sample size is small (i.e. <30).
Fitness test data obtained from fewer than 30 athletes are likely to adhere to
a t-distribution rather than a normal distribution (Turner et al., 2019). A tdistribution of data points is shorter and wider than data that are normally
distributed and, because this t-score calculation depends on the sample size,
reference tables must be used to interpret the magnitude of the athlete’s
score relative to the squad mean. Fortunately, however, in software such as
Microsoft Excel we can simply use the t.dist function where we state the
sample size and Excel will assess our value against the appropriate table,
illustrating the data as a percentage. We can then assess that percentage in
terms of where our athlete places, as per z-scores, and as illustrated in
Figure 11.2. Before using the t.dist function, the value must first be
converted to a t-score using the formula presented below:
A typical normal data distribution curve with z-scores, corresponding
standard ten (STEN), t-score and percentile values and integrated traffic-light
system example.
One way of overcoming a squad sample size <30 is to create a larger
database of squad fitness test scores over time. For example, this could be
achieved by adding fitness test scores that have been obtained from
equivalent athletes (e.g. same age and performance level) using identical
methods (e.g. equipment and coaching cues) and time periods of testing
(e.g. pre-season) to a digital repository or database. If increasing sample
size over time is logistically difficult, using the aforementioned t.dist
function in Microsoft Excel is a suitable alternative approach.
Percentiles
Percentiles are another option for making fitness test results more intuitive
for athletes and coaches to understand. Like STEN scores and t-scores, they
avoid the use of small and sometimes negative numbers. Percentiles can be
easily calculated from z-scores in applications such as Microsoft Excel via
the following formula:
A percentile represents the value below which a percentage of data falls.
For example, the 20th percentile is the value below which 20% of
observations may be found. Percentiles have been routinely calculated for
fitness test results obtained from a range of populations, particularly for
children to track as they grow over time. More recent applications of
percentiles include those that have been applied to key countermovement
jump variables obtained from force platforms (Sole et al., 2018; McMahon
et al., publish ahead of print) and fitness-testing results for law enforcement
officers (Lockie et al., 2018, 2020). Like with z-scores and STEN scores,
percentiles can be calculated for normally distributed data, so again, it is
important to check for normal data distribution before proceeding with
percentile calculations.
As with STEN scores, several upper- and lower-bound z-scores will
share the same percentile. For example, a z-score of ≤ −3.5 and ≥ 3.5 will
share a percentile of 0 and 100, respectively (Table 11.3). This is unlikely,
however, to alter decision making based on typical thresholds used to
distinguish performance ‘bands’ when benchmarking an athlete’s results to
their peers/normative data (e.g. poor, average, good, excellent, etc.).
Table 11.3 Example performance test results and corresponding individual and average percentiles
Sprint test
5-m time (s)
10-m time (s)
Athlete’s result
1.18
1.88
Squad mean
1.07
1.81
Squad standard deviation
0.07
0.08
Percentile
6.7
15.9
Vertical jump test
CMJ height (cm)
SJ height (cm)
Athlete’s result
42
38
Squad mean
36
35
4
6
93.3
72.6
Squad standard deviation
Percentile
Isometric mid-thigh pull test
Peak force (N)
Rel. peak force (N/kg)
Athlete’s result
3630
42
Squad mean
3667
38
647
6
Squad standard deviation
Percentile
Total score of athleticism
46.0
50.0
(percentile)
CMJ, countermovement jump; SJ, squat jump.
Data presentation
75.8
Once athletes’ fitness test results have been converted to a standardised
format to facilitate intuitive reporting of the test scores, using any of the
options discussed in the previous section, there are several options for
presenting them in a visually appealing manner. It is beyond the scope of
this chapter to discuss all data presentation options available to the
practitioner, but we do provide some common, yet impactful, examples
based on both the limited published research available and our applied
experience.
Traffic-light system
A traffic-light system (TLS) refers to a method of colour coding fitness test
results in red, amber or green (sometimes including various shades of each
colour) corresponding to a negative, neutral or positive change in a test
result (or low-, average- or high-achieving test results if used to
‘benchmark’ the athlete’s performance to others). It has been suggested that
TLSs are an appealing option for strength and conditioning coaches who
tend to work in a time- and resource-constrained environment (McMahon
and Mundy, 2018). This is because a TLS is quick to produce (e.g. use of
conditional formatting in Microsoft Excel), visually appealing and intuitive
for coaches and athletes to interpret (Robertson et al., 2017). Although easy
to construct and interpret, determining the TLS’s red, amber and green
performance ‘bands’ for a given fitness test result usually requires
comparison with extensive historical data obtained from the team you are
working with or published normative data sets that were collected and
analysed using equivalent methods (Robertson et al., 2017). However, once
the fitness test data have been converted to a standardised form, based on
any of the methods described in the data analysis section, it is somewhat
easier to determine the TLS’s red, amber and green performance bands or
thresholds. While there is no criterion method of identifying performance
bands that denote a negative (amber–red, depending on magnitude), neutral
(no colour or amber, depending on application [discussed further below]) or
positive (green) fitness test score, in this section we propose one approach
that may be benefical to practitioners.
The first thing to point out is that our method of constructing
performance bands based on standardised units (rather than absolute
benchmarks) that may then feed into a TLS requires the athlete’s individual
performances in the fitness tests to be compared to an appropriate mean and
standard deviation (e.g. from the squad or normative data), in line with the
recommendations provided in the data analysis section. Assuming,
therefore, that the selected mean and standard deviation are appropriate, our
proposed method is based on the typical scale used to interpret standardised
scores. Specifically, we consider what magnitude of difference (when
comparing an individual athlete’s fitness test scores to the squad mean or
normative data) or change (when comparing an individual athlete’s fitness
test scores post-intervention to their pre-intervention scores) is likely to be
required for it to be greater than the associated tests’ measurement error.
The standard error of measurement (SEM), which is commonly referred to
as the typical error within the profession of strength and conditioning, of
each fitness test score is likely to exceed the smallest worthwhile change
(0.2 × the squad or normative data standard deviation, which is equivalent
to a z-score of 0.2) associated with each test. Thus, constructing
benchmarks and the associated TLS based on a small z-score of ≤0.2 (or
equivalent number for the other standardised scores presented in the
previous section) is probably nonsensical. However, most of the typical
fitness tests conducted within strength and conditioning (based on published
research and our own data analyses) yield an SEM that falls below the
moderate worthwhile change (0.5 × the squad or normative data standard
deviation, which is equivalent to a z-score of 0.5). Therefore, our suggested
approach is to use 0.5 z-score (or equivalent) increments when constructing
the performance bands that feed into a TLS, as this should account for the
worst-case-scenario SEM values for most (but ideally all) fitness tests. In
other words, most fitness test scores should have an associated SEM that is
low enough to enable moderate differences (between athletes) or changes
(within athletes) to be determined with confidence. With this in mind, an
illustration of our suggested approach for constructing TLS performance
bands, which includes the associated z-scores, STEN scores, percentiles and
t-scores, is presented as Figure 11.2. Of course, practitioners could quantify
the SEM associated with each of the fitness tests that they conduct with
their athletes to determine the precise z-score (or equivalent) that denotes a
‘meaningful’ difference or change and instead use those values to construct
a TLS. However, the SEM when expressed as a standardised score is going
to be different for each fitness test result and so it would be very difficult to
produce a quick (preferably automated) fitness test report with an integrated
TLS if one was to adpot this approach.
A TLS can be used to colour-code fitness test results according to
performance band attainment irrespective of the format in which the key
fitness test results will be reported to the athlete and coaches. For example,
a TLS can be included with tabulated fitness test results. If presenting
fitness test results as in Table 11.3 with an integrated TLS, we advocate the
presentation of important data only and removing unnessary decimal points
from reported values, along with the other excellent suggestions provided
by Buchheit (2017). Even if the recommendations of Buchheit (2017) have
been followed, data tables are generally considered to be less visually
appealing and intuitive than graphical data representations. Thus, some
options for reporting fitness test results in graphical formats are discussed in
the following sections.
Radar charts
Radar charts (sometimes referred to as spider charts) allow three or more
fitness test results for an individual athlete to be presented on axes with an
equal origin. Therefore, radar charts can be constructed using z-scores,
percentiles, STEN scores and t-scores. Radar charts are particularly useful
when reporting baseline fitness test scores by comparing each athlete’s
score to the squad or normative data mean and standard deviation, or
changes in an individual athlete’s fitness scores between two occasions (e.g.
pre- and post-training intervention). We will discuss both applications of
radar charts in this section. We have used t-scores in the examples provided
to facilitate ease of interpretation (i.e. an intuitive 0–100 scale), but the
principles discussed may be applied to any other standardised score that has
been discussed in this chapter.
Example results of a pre-season fitness-testing battery that was
conducted within rugby league are presented as a radar chart using a
standardised t-score scale with integrated TLS in Figure 11.3. As can be
seen, the benefit of converting multiple individual fitness test results to
standardised scores and then presenting them within a single radar chart is
that the athlete’s relative strengths and weaknesses can be easily visually
identified, even when a lot of fitness test scores are presented at once. In
this example, a white band for t-scores ranging from 45 to 55 has been
applied to represent the squad mean score, plus and minus half a standard
deviation to account for the (hopefully) upper limit of each test’s
measurement error. For example, the athlete’s result for left-side change-ofdirection time (actual t-score of 48) and eccentric utilisation ratio (actual tscore of 46) is interpreted as being equivalent to the squad mean.
Conversely, all other fitness test scores may be confidently interpreted as
being better (various shades of green) or worse (amber or various shades of
red) than the squad mean, with their obvious best peformances seen for the
maximal strength (isometric mid-thigh pull) and sprint momentum (owing
to their larger than average body mass, given that their sprint times are
below average) tests and their obvious worst peformance seen for the
countermovement jump height test. The TSA indicates that the athlete’s allround performance in the fitness-testing battery was comparable to the
squad mean, albeit comprised of several better and worse performances in
the individual fitness tests. Such intuitively presented fitness test results
should enable audiences (e.g. coaches and athletes) to quickly identify areas
for the athlete’s future improvement which can then be addressed in their
upcoming training programme (such as ballistic training in the present
example).
Example results of a pre-season fitness-testing battery conducted within
rugby league and presented as a radar chart using a standardised t-score scale
and integrated traffic-light system.
As well as presenting three or more fitness test results for an individual
athlete within a single radar chart, it is possible to present several results
from the same or a few fitness tests. This approach may be particularly
useful when conducting force platform assessments with athletes, as
practitioners may identify several force platform variables of interest from a
single force platform assessment (e.g. when conducting the
countermovement jump test) or wish to combine results from two force
platform assessments (e.g. when calculating dynamic strength index). To
that end, example results from force platform assessments that were
conducted as part of a pre-season fitness-testing battery within rugby league
are presented as a radar chart using a standardised t-score scale with
integrated TLS in Figure 11.4. As can be seen, the athlete included in this
example performed very well compared to his peers, as noted by him being
ranked first in the squad for the TSA. Upon visual inspection of the force
platform assessment results, eccentric utilisation ratio (calculated as
countermovement jump height divided by squat jump height) is the only
score that falls below the squad average and in the amber performance
band. That is not to say that the athlete would not benefit from further
improving the physical qualities that he has excelled at in comparison to his
peers, but that eccentric utilisation ratio is the only test score that is
evidently below the standard set by the squad mean.
Example results from force platform assessments that were conducted as part
of a pre-season fitness-testing battery within rugby league presented as a
radar chart using a standardised t-score scale and an integrated traffic-light
system.
Upon further insepection of the force platform assessment results, it can
be seen that the joint highest t-score of 69 was obtained for reactive strength
index modified and squat jump height. As reactive strength index modified
is calculated from the countermovement jump data as jump height divided
by time to take-off, the larger t-score for reactive strength index modified
than for countermovement jump height (t-score of 66) suggests that this
athlete performed the countermovement jump with a shorter time to take-off
than the squad mean. Reducing time to take-off in the countermovement
jump can reduce jump height, thus the reason why the athlete jumped
higher in the squat jump than in the countermovement jump (hence
generating an eccentric utilisation ratio of less than 1) could have been due
to them restricting their propulsion displacement in the countermovement
jump to facilitate a shorter time to take-off (McMahon et al., 2021).
Therefore, the eccentric utilisation ratio of less than 1 may merely be a
reflection of the athlete’s preferred countermovement jump strategy rather
than an indication of a poor utilisation of the stretch-shortening cycle
(which is what the eccentric utilisation ratio supposedly reveals). Thus, the
informed practitioner may not wish to place too much emphasis on the
athlete’s below-average eccentric utilisation ratio alone, but rather focus on
a combined maximal strength and ballistic training programme given the
overall balance of the athlete’s mostly positive results and his dynamic
strength index score of 0.7 (Figure 11.4).
As mentioned in the data analysis section, modified z-scores (and
thereafter any of the other standardised scores discussed) can be calculated
to illustrate changes in an athlete’s fitness-testing scores from baseline
testing, such as after a training intervention, for example. To that end,
example results from a countermovement jump assessment that was
conducted using a force platform as part of a pre-season fitness-testing
battery within rugby league are presented as a radar chart using a
standardised t-score scale with integrated TLS in Figure 11.5. In this
example, the white band for t-scores ranging from 45 to 55 has been applied
to represent the athlete’s baseline mean score, plus and minus half a
standard deviation to account for the upper limit of each score’s
measurement error. Also, a reduction in countermovement time,
countermovement displacement and propulsion time was considered a
positive outcome but, to avoid possible confusion, arrows have been added
next to the variable labels to denote whether the absolute score for these
tests increased or decreased between testing occasions (e.g.
countermovement time in seconds decreased, hence the downward arrow,
but this is shown as an increased t-score due to it being considered a
positive outcome). Again, the radar chart with integrated TLS makes it easy
for the audience to quickly interpret within-athlete changes in key fitness
test results. In this example, the athlete improved in all aspects of
countermovement jump performance (Figure 11.5). Even though the
upward arrow denotes an increase in countermovement displacement, the tscore of 47 falls within the white performance band comprised of the
baseline mean ± SEM, thus it should be interpreted as no change. If
subsequent countermovement jump tests were to be performed with this
athlete, the latest test results could be compared to the baseline results alone
(as in Figure 11.4), to the previous results alone or overlaid with the
previous test results so that an additional data series showing the latest
results is presented alongside the previous test results, depending upon the
practitioner’s preference.
Example results from a countermovement jump assessment that was
conducted using a force platform as part of a pre-season fitness-testing
battery within rugby league presented as a radar chart using a standardised tscore scale and an integrated traffic-light system.
Conclusion
This chapter has discussed some of the data analysis options available to
practitioners to facilitate the sometimes difficult task of presenting multiple
fitness test results, often containing unfamiliar units of measurement, in the
form of standardised scores. Standardised scores enable several fitness test
results with different units of measurement to be presented on the same
intuitive scale, such as 0–100 (i.e. t-score). Some methods of visually
presenting standardised scores were then discussed in the form of
developing a TLS, including suggestions on how to construct colour-coded
performance bands, and then plotting key results in a simple radar chart
with integrated TLS. Examples of radar charts with integrated TLS to
present baseline fitness test results attained across multiple fitness tests,
several baseline force platform assessment results and within-athlete
changes in key countermovement jump assessment results were then
provided and discussed. It is hoped that this chapter will provide some
guidance to practitioners who are charged with generating quick and
intuitive fitness test reports across the sporting season to disseminate
valuable feedback to athletes and coaches.
References
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12 Eccentric training: scientific
background and practical
applications
Mellissa Harden, Paul Comfort and G. Gregory
Haff
DOI: 10.4324/9781003044734-15
A central theme of this chapter is focusing on eccentric muscle actions and the use
of eccentric exercise as a tool for enhancing strength and athletic performance.
Several eccentric resistance-training modalities are available to the strength and
conditioning coach, each of which has unique biomechanical characteristics that
can stimulate unique physiological and performance adaptation. It is well
documented that habitual use of eccentric exercise, usually with isolated singlejoint tasks, can result in a larger and stronger muscle that has the potential to
generate higher-power outputs when compared to traditional isotonic training.
Unfortunately, many of the methods incorporated in these eccentric training studies
lack ecological validity and are therefore not easily applied to normal multi-joint
resistance-training exercises. In contrast, accentuated eccentric loading (AEL) may
be a viable method of providing eccentric overload during traditional multi-joint
exercises.
To assist coaches with their understanding of eccentric muscle actions and
training, section 1 will provide a summary of the theoretical basis for employing
eccentric training. This part of the chapter is designed to help strength and
conditioning coaches better understand the unique characteristics of eccentric
muscle actions and how integrating this type of muscle action into training may
translate to an enhanced physical performance capacity. The second part of this
chapter explores various eccentric training modalities and specific eccentric
resistance-training methods to assist practitioners with the application of eccentric
training within an athlete’s training programme.
Introduction
Strength and conditioning coaches prescribe numerous resistance-training methods
with the aim of enhancing athletic performance and reducing injury risk. Training
usually draws upon a variety of exercises that emphasise different muscle actions
(i.e., eccentric, isometric, concentric, and coupled eccentric–concentric [isotonic]).
Training that incorporates different types of muscle action will not only improve
sporting movements that draw upon these specific muscle actions, but will also take
advantage of the beneficial effects of the physiological adaptations that are unique
to each muscle action (e.g., increased fascicle length associated with maximal
eccentric actions: [Franchi et al., 2014, 2015; Geremia et al., 2019]), potentially
leading to higher maximal shortening velocity and therefore power (Narici, 1999;
Lieber and Fridén, 2000).
Muscle actions vary in their neural, mechanical, metabolic, and cardiovascular
characteristics, and therefore tend to result in distinctive physiological adaptations
following routine training. It is important that strength and conditioning coaches are
aware of the unique characteristics and adaptations resulting from different modes
of training and understand the potential role these adaptations play in the physical
and performance development of athletes, as well as their potential for reducing
injury risk. A greater understanding of the unique characteristics associated with
eccentric training will ensure that the strength and conditioning coach can develop
relevant and effective training programmes and more effectively interpret research
in this area.
While the benefits of traditional isotonic strength-training methods are generally
well accepted (Cormie et al., 2011a, 2011b; Suchomel et al., 2016, 2018), it is
important to consider the limitations of such strategies when the aim is to increase
eccentric muscle strength. (Traditional training principles for the development of
strength and power are discussed in detail in Chapter 2.) During traditional modes
of strength training the maximal load lifted is determined by the maximal
concentric strength, thereby limiting the ability to take advantage of the increased
force generation capacity that is possible during eccentric muscle actions. While
both concentric and eccentric strength increase in response to traditional strengthtraining methods, eccentric training can permit loads up to 150% of the load used
during the concentric phase (Hortobágyi and Katch, 1990; Dufour et al., 2004;
Harden et al., 2019), which provides unique opportunities to apply greater load
during the eccentric muscle action. However, it is important to note that this higher
level of eccentric force production varies between individuals, likely due to
familiarity with the task and the athlete’s relative strength levels (Harden et al.,
2018; Hody et al., 2019).
SECTION 1
Unique characteristics associated with eccentric muscle actions
Eccentric muscle actions occur when the force generated by the muscle is less than
the force imposed by an external stimulus, causing the muscle to lengthen whilst
active. In this instance, work is done on the lengthening muscle and the associated
connective tissues store mechanical energy (Lindstedt et al., 2001). During tasks
such as running, sprinting, and reactive jumping (i.e., stretch-shortening cycle
[SSC] actions), elastic potential energy is stored within the connective tissues of the
muscle–tendon unit during the eccentric phase, then released and utilised during the
propulsive phase, supplementing the force produced from concentric muscle action
(LaStayo et al., 2003). In this instance, the muscle–tendon unit acts as a spring and
the release of stored energy acutely enhances force production characteristics
during the concentric phase, when compared to a concentric-only muscle action.
Additionally, when a muscle is lengthened during SSC tasks, the muscle spindle is
stimulated via both the rate and magnitude of muscle lengthening and results in an
increased force and rate of force production via the stretch reflex. However, during
tasks such as landing and braking (i.e., decelerative actions), stored elastic energy is
dissipated as heat, via hysteresis. In such instances muscles and tendons act as
‘shock absorbers’ to dampen impact forces upon ground contact (LaStayo et al.,
2003). Enhancing the function of muscle via eccentric training can therefore
facilitate performance during tasks that utilise the SSC or enhance the capability to
decelerate the body (Liu et al., 2020). It is worth noting that in individuals who do
not have well-developed strength, traditional strength-training methods are an
effective means of enhancing SSC function, to a greater extent than jump training
alone (Cormie et al., 2007, 2010a, 2010b, 2010c; Earp et al., 2011). So, for these
individuals the application of traditional strength-training methods should be the
priority.
Eccentric muscle actions are characterised by a combination of distinct
mechanical, neural, metabolic, and circulatory qualities. In terms of mechanical
qualities, there are increased cross-bridge forces and passive forces from the
contribution of structural elements within the sarcomere. During eccentric muscle
actions, active lengthening of the muscle results in a different interaction of actin
and myosin filaments (Linari et al., 2004; Herzog, 2014). The forcible detachment
of cross-bridges does not rely on adenosine triphosphate (ATP) splitting, as per the
normal cross-bridge cycling processes, and leaves the myosin filaments in an active
state such that they are able to rapidly reattach back to actin (Lombardi and
Piazzesi, 1990). Along with the activation of the second head of myosin, and
possible increased number of stronger attachments to the actin filaments, this can
result in a greater number of cross-bridge attachments at a given time, thus
increasing cross-bridge force (Linari et al., 2000). Furthermore, contribution of
passive tension from the inherent stiffness of structural elements within the
sarcomere can further contribute to force enhancement during eccentric muscle
actions (Nishikawa, 2016).
It is accepted that muscles are stronger during eccentric versus isometric (i.e.,
constant muscle length) or concentric (i.e., shortening) muscle actions. Researchers
have documented that individuals are up to 50% stronger during maximal eccentric
exercise versus maximal concentric exercise (Hortobágyi and Katch, 1990; Dufour
et al., 2004; Harden et al., 2019). Coaches should be mindful, however, that there is
clear variability in the magnitude of additional force that can be produced during
eccentric actions compared to concentric and isometric actions (Harden et al.,
2019), which may be attributable to both the athlete’s relative strength levels (Hody
et al., 2019) and their familiarity with the eccentric task. When considered
simplistically, an individual is generally able to lower a weight that is much heavier
than what they can lift. Therefore, during traditional exercise whereby loading is
limited by concentric strength, eccentric strength is challenged to a much lesser
extent given that maximum eccentric strength is much greater than maximum
concentric strength. This distinct characteristic of eccentric muscle actions enables
the application of greater loads during the eccentric phase, well beyond what can be
applied during concentric muscle actions. Interestingly, Refsnes (1999) reported
that strong athletes tolerate lower eccentric loads relative to their one repetition
maximum (1RM), providing an example of eccentric loads of 105–110% 1RM in
world-class power lifters, while lower-level athletes may tolerate loads of 120–
130% 1RM. Similar results highlighting a greater discrepancy in eccentric and
concentric loads between weaker and stronger individuals have also been reported
by researchers (Hollander et al., 2007; Harden et al., 2019).
In a practical context, when looking to develop eccentric strength, information
regarding the enhanced force production capability of eccentric muscle actions has
led to the application of loads that exceed conventional coupled eccentric–
concentric 1RM during multi-joint exercise. During multi-joint eccentric exercises
loads of up to 150% 1RM have been used for trained individuals (Harden et al.,
2018), when using AEL (e.g., additional load from hydraulics in research, or in
applied settings the use of weight releasers, so that the additional load is removed at
the end of the eccentric phase, resulting in a load that is <1RM during the
concentric phase of the lift). However it is important to note that not all trained
individuals are able to tolerate such high relative loads (Harden et al., 2018, 2019),
with weaker individuals demonstrating a greater discrepancy between concentric
and eccentric load (Hollander et al., 2007; Harden et al., 2019), meaning that a
conservative approach to eccentric loading should initially be adopted.
Interestingly, for a given force output, muscles require less energy and activation
(per unit of force) during eccentric versus concentric or isometric actions (Abbott et
al., 1952). For the same level of submaximal force output, muscle activation is
notably lower during eccentric versus concentric muscle actions (Franchi and
Maffiuletti, 2019). Researchers have also shown that for the same work output,
energy expenditure is approximately four-fold less during eccentric versus
concentric exercise; eccentric actions are associated with markedly lower oxygen
uptake for a given submaximal mechanical power output (Bigland-Ritchie and
Woods, 1976; Overend et al., 2000; Meyer et al., 2003).
Dufour et al. (2004) provide additional insight into the distinct metabolic and
circulatory response associated with eccentric exercise. When comparing eccentric
and concentric cycling at a similar mechanical power output, the authors reported
that eccentric muscle work induces lower metabolic and cardiovascular responses
(lactate accumulation, oxygen consumption, cardiac output, and heart rate) than
concentric muscle work. However, eccentric and concentric cycling performed at a
similar submaximal metabolic power output (i.e., oxygen uptake), resulted in
greater cardiovascular stress (cardiac output and heart rate) during eccentric cycling
as the mechanical power required to achieve the target metabolic power output was
five times greater than that required during concentric cycling. Subsequently, the
authors attributed the increased cardiovascular stress to thermoregulatory or muscle
tension-induced responses.
In terms of unique neural qualities, it has been suggested that the preparation,
planning, and performance of eccentric muscle actions appear to differ from
concentric muscle actions due to differences in the onset of brain activity and
associated brain area that are involved immediately before and during movement
(Fang et al., 2001). This is a unique strategy for control of motor unit activation and
discharge rate. At a given force output or when under similar loading conditions,
eccentric muscle actions are associated with reduced muscle activation and
discharge rate of the activated motor units when compared to concentric muscle
actions (Bigland-Ritchie and Woods, 1976; Pasquet et al., 2006; Aagaard, 2018).
Unlike concentric muscle actions, there is evidence of incomplete muscle activation
during maximal eccentric muscle actions (Aagaard, 2018; Aagaard et al., 2000;
Spurway et al., 2000). The activation shortfall has been attributed to inhibitory
mechanisms (Aagaard, 2018), potentially due to stimulation of the Golgi tendon
organ, attributed to the magnitude and rate of strain to which the tendon is subjected
(Chalmers, 2002). The inhibitory response and subsequent voluntary activation
deficit are modifiable by targeted strength training, which can reduce or diminish
the degree of inhibition (Amiridis et al., 1996; Aagaard et al., 2000; Aagaard,
2018). Additionally, it is common for eccentric muscle actions to be associated with
the preferential recruitment of higher-threshold motor units (Nardone and
Schieppati, 1988; Nardone et al., 1989); however, this is not widely accepted and
remains a topic of debate within the scientific literature (Chalmers, 2008;
Duchateau and Enoka, 2016).
In summary, when using eccentric muscle actions there is potential to perform a
given submaximal force (and even when performed with supramaximal loads) with
metabolic, neural, and circulatory efficiency compared to isometric and concentric
muscle actions. Furthermore, individuals can produce greater muscle force and
tension during eccentric versus concentric muscle actions. The practical
implications of these features are:
individuals can perform greater work at a given submaximal exercise intensity
individuals can tolerate greater external load during eccentric exercise versus
conventional isotonic training methods, i.e., individuals can lower more than
they can lift so movements can be loaded to a greater extent when using certain
eccentric or eccentrically biased training approaches, such as AEL.
During eccentric exercise, muscles can experience unique muscle strain which
could stimulate cascade of distinct physiological events resulting in increased
fascicle length associated with maximal eccentric actions (Franchi et al., 2014,
2015; Geremia et al., 2019), leading to higher maximal shortening velocity and
therefore increased potential for power development (Narici, 1999; Lieber and
Fridén, 2000).
Eccentric training has also been reported to result in fibre shifts to faster myosin
heavy-chain isoforms (Friedmann et al., 2004; Friedmann-Bette et al., 2010),
associated with increased force and power production (Aagaard and Andersen,
1998; Friedmann-Bette et al., 2010). Exploiting these unique characteristics of
eccentric muscle actions has the potential to stimulate distinct and potent,
neuromuscular, and physiological adaptations. The nature of these adaptations,
which will be discussed next, could prove beneficial for rehabilitation, physical
development of athletes, and performance during sport.
SECTION 2
Classification of eccentric exercise modalities
In 1972, Arthur Jones wrote the article ‘Accentuate the negative’ which was
featured in IronMan magazine (Jones, 1973). Jones (1973) suggested that readers
think about how much they can lower, rather than how much they can lift. Jones
(1973) appeared to have coined the term ‘negative training’, for what is now more
commonly referred to as ‘eccentric training’. Although he popularised the training
method for developing strength and stimulating hypertrophy (predominantly in
bodybuilding), the idea is likely to be based upon scientific findings that were
published in the preceding years (Abbott et al., 1952; Petersen, 1960; Doss and
Karpovich, 1965; Huxley, 1969; Mannheimer, 1969). Since this first notation of
eccentric training in the applied literature, the scientific basis explaining the use of
eccentric training methods has continued to evolve. There are potential benefits
related to emphasising the eccentric phase during training:
increased time under tension ([TUT]: e.g., tempo training, where the duration
of the eccentric phase of isotonic exercises is prolonged, albeit that this method
does not take advantage of the higher force production capability of eccentric
actions) potentially benefitting hypertrophic adaptations
increased load during the eccentric phase (e.g., AEL, where additional load is
provided by weight releasers during the eccentric phase), which may enhance
strength-related adaptations due to unique architectural adaptations, which may
also reduce injury risk.
Technologies used to apply eccentric training are becoming more advanced, and
equipment that facilitates the ability to perform eccentric training is becoming
increasingly more accessible. For example, flywheel devices are readily available
(Petré et al., 2018), in addition to weight releasers (Merrigan et al., 2020a, 2020b;
Doan et al., 2002), with some more advanced techniques including motorised
devices to increase eccentric loads used in research (Frohm et al., 2005; Harden et
al., 2018, 2019). The availability of such devices to accentuate the eccentric load
has prompted a large influx of information regarding the efficacy of eccentric
training for the purpose of advancing physical performance. It is worth noting that
flywheel devices appear to result in forces during the eccentric phase that are
comparable to those during the concentric phase, but generally not greater than the
concentric phase (Suchomel et al., 2019).
Eccentric training is an umbrella term used for several different eccentric
training modalities. Eccentric training modalities include modifying the eccentric
phase of an exercise, such that it differs from the conventional application of load.
This provides an option for introducing training variety by offering a novel training
stimulus. Recently, Franchi and Maffiuletti (2019) made a distinction of eccentric
training modalities and recognised the unique underpinning biomechanical
demands and neuromuscular profiles of the different modalities. The following
eccentric training modalities were identified: isoweight, isokinetic, and isoinertial,
whereby each modality comprises a different constant: weight, velocity, and inertia,
respectively, and therefore differ in their variability and demand for self-adjustment
during movement. The piece stimulated a number of comments and viewpoints
from several other researchers regarding the distinction and classification of other
forms of eccentric activity, for example, isopower (i.e., constant power output)
(Coratella et al., 2019). A summary of this information is presented in Table 12.1.
Table 12.1 Four eccentric training modalities and specificities underpinning each modality
Classification/modality Isoweight
Isoinertial
Isokinetic
Isopower
Constant
External
load/bodyweight
Inertia
Velocity
Power output
Examples
Free weights, landings Flywheel and
(vertical entry),
conic pulley
deceleration
(horizontal entry
using augmented,
accentuated, or
eccentric
only/negatives
approaches)
Dynamometry Cycle and
step
ergometry
* Supramaximal intensity results from using non-specific measures of ECC strength to prescribe intensity.
** Potentially possible with technique modification.
*** Supramaximal intensity does not apply as the intensity is specific to ECC strength.
More + signs indicate more evidence in this area.
ROM, range of motion; CON, concentric; ECC, eccentric; MVC, maximal voluntary contractions.
Adapted from Franchi, M.V. and Maffiuletti, N.A. 2019. Distinct modalities of eccentric exercise: Different
recipes, not the same dish. Journal of Applied Physiology (1985), 127, 881–883.
Classification/modality Isoweight
Isoinertial
Isokinetic
Isopower
Factors affecting output
Tempo/cadence,
ROM, drop height
(landings),
running/entrance
velocity
(decelerations)
Tempo/cadence,
ROM, target
intensity/effort
during CON
phase, technique
(timing/position
of onset of
deceleration
during ECC)
Intensity of
effort,
ROM
Cadence
Possible movement
Coupled ECC-CON,
ECC only
Coupled ECCCON
Coupled
ECC-CON,
ECC only
ECC-only
movement
Eccentric intensity
Submaximal
Maximal
Supramaximal*
Submaximal
Maximal
Supramaximal**
Submaximal
Maximal***
Submaximal
Maximal***
Eccentric loading
During coupled ECC- Determined by
CON, ECC load
CON capacity
can be dissociated
and inertial of
from CON load
flywheel/conic
using specialised
pulley
equipment or
techniques. For
ECC only, ECC
load can be applied
using specialised
equipment or safety
racks and spotters
Dependent on
preset
target force
output
relative to
ECC MVC
Dependent
on preset
target
power
output
Eccentric load prescription
Commonly based on
non-ECC-specific
measures of
strength
Based on CON
output
Considers
ECCspecific
strength
Considers
ECCspecific
strength
Prevalence of use
Research +
Practice +++
Research +++
Practice +++
Research
++++
Practice +
Research
+++
Practice ++
* Supramaximal intensity results from using non-specific measures of ECC strength to prescribe intensity.
** Potentially possible with technique modification.
*** Supramaximal intensity does not apply as the intensity is specific to ECC strength.
More + signs indicate more evidence in this area.
ROM, range of motion; CON, concentric; ECC, eccentric; MVC, maximal voluntary contractions.
Adapted from Franchi, M.V. and Maffiuletti, N.A. 2019. Distinct modalities of eccentric exercise: Different
recipes, not the same dish. Journal of Applied Physiology (1985), 127, 881–883.
During isokinetic exercise, an individual is simply required to produce force,
ideally with maximal intent, without having to control the speed of the movement,
as the velocity of the movement is controlled by the isokinetic dynamometer. In
contrast, a greater degree of self-adjustment is required during isopower exercise,
where movement velocity is not regulated via equipment. Instead, an individual
must produce a force whilst attempting to voluntarily control the movement by
matching a predetermined cadence. An isopower ergometer adjusts in response to
an individual’s cadence to maintain a constant power output. A given power output
can be achieved by applying a greater force output using a lower cadence or vice
versa. Similarly, a high degree of self-adjustment is required during isoweight
exercises whereby controlled movement is an interplay of acceleration and
deceleration. During isoweight exercise, an individual must act to produce
sufficient force and under voluntary control to match a predetermined performance
constraint, for example, over a set range of motion (ROM) (e.g., during a squat) or
fall height (e.g., during a drop jump) in order to produce a sufficient force at an
appropriate rate to accept, equal, or overcome an anticipated mechanical force that
is imposed on the musculoskeletal system. For example, during AEL one research
group has recommended high loads, with a large relative difference (≥40% 1RM on
weight releasers), creating a 80–120% ratio of concentric (80% 1RM) to eccentric
loading (120% 1RM) (Merrigan et al., 2020a), which is in line with suggestions
from over 30 years ago (Poliquin, 1988). These distinctions are particularly
important because the different characteristics associated with the range of
eccentric exercise modalities are likely to alter the neuromuscular control strategy
(Duchateau and Enoka, 2016), and thus lead to distinct adaptive responses, and
neurological and architectural adaptations (Guilhem et al., 2010; Coratella et al.,
2015; Doguet et al., 2016). It is important for practitioners to understand the distinct
qualities of the different approaches to eccentric training so that more accurate
decisions can be made about the most appropriate form of eccentric training to use
within a training programme based on the target adaptations.
SECTION 3
Physiological basis for eccentric training
Eccentric muscle actions, which occur during eccentric training, occur when the
force generated by the muscle is less than the force imposed by an external load.
This is in contrast to concentric muscle actions, which are prevalent during
concentric training, occurring when the force generated by the muscle is more than
the force imposed by an external load. Eccentric muscle actions are associated with
unique neural control strategies (Enoka, 1996) and distinct mechanical processes
(Lieber, 2018) compared to concentric and isometric muscle actions. Therefore,
training using eccentric muscle actions may offer a novel stimulus which can result
in distinct neuromuscular and morphological adaptations.
Acute responses
Acute physiological and performance responses are manifested immediately
following or in the days after performing an exercise or series of exercises. The
acute physiological responses associated with eccentric exercise can impede or
enhance performance, depending on the application (i.e., load and volume), and can
be indicative of potential longitudinal adaptation. For example, numerous
researchers have demonstrated immediate myofibrillar disruption associated with
unaccustomed eccentric exercises, which can last for 2–3 days (depending on the
volume) and which manifests as delayed-onset muscle soreness (DOMS) (Hody et
al., 2019). During this time performance is impaired; however, this initial bout of
eccentric exercises can have a protective effect for subsequent eccentric training,
known as the repeated-bout effect (RBE) (McHugh et al., 1999; Nosaka and Aoki,
2011). In contrast, if the athlete is familiar with eccentric exercises and acute
soreness is not evident, enhanced neurological stimulation and changes in muscle
architecture can result in enhanced force production capabilities (Blazevich and
Babault, 2019).
Repeated eccentric action of muscles whilst undergoing high tension can cause
disruption to the contractile and non-contractile elements of the muscle, resulting in
temporary muscle soreness and reduction in force output (Morgan and Allen, 1999).
Whilst this could be interpreted as a negative effect, it is important to highlight that
an element of microdamage is essential to stimulate tissue repair and growth,
providing protection against future damage (Nosaka and Aoki, 2011). Importantly,
this disruption stimulates muscle protein synthesis, increases intracellular anabolic
signalling, and upregulates gene expression (Krzysztofik et al., 2019), whilst
creating the RBE (McHugh et al., 1999; Nosaka and Aoki, 2011). These responses
are indicative of the potential for muscle hypertrophic response if the exercise is
performed habitually, and importantly, are heightened following eccentric exercise
compared to traditional loading approaches or concentric muscle actions (Moore
and Schilling, 2005; Friedmann-Bette et al., 2010; Franchi et al., 2015; Suchomel et
al., 2019). The myofibrillar disruption associated with unaccustomed eccentric
exercises (Lauritzen et al., 2009; Hody et al., 2019) has notable implications for the
prescription of such tasks, which should be conservative and progressive in nature,
to avoid excessive muscle soreness. Such discomfort can discourage individuals
from performing specific activities (Hody et al., 2019) and therefore needs to be
carefully considered when introducing focused eccentric exercise. Fortunately, a
clear RBE is evident with eccentric training, whereby reduced myofibrillar
disruption, swelling, and muscle soreness occur in subsequent bouts of the same
activity, even after an initial single bout of eccentric exercise (McHugh et al., 1999;
Nosaka and Aoki, 2011).
Alternatively, accentuating the external load during the descending phase of an
exercise can result in an acute enhancement of concentric performance (commonly
referred to as post-activation performance enhancement [PAPE]; [Blazevich and
Babault, 2019; Merrigan et al., 2020a]). This effect has been attributed to
physiological responses such as increased neural stimulation (i.e., more potent
myotatic reflex and/or increased motor unit recruitment); storage and subsequent
release of energy in elastic structures (i.e., from stretch and recoil of parallel and
series elastic components); and increased muscle active state at the onset of
concentric action (i.e., greater number of attached cross-bridges) during the
propulsive phase (Doan et al., 2002; Moore and Schilling, 2005; Ojasto and
Häkkinen, 2009a; Ojasto and Häkkinen, 2009b). These features facilitate forceproducing characteristics particularly during the onset and early phase of the
ascending portion of the movement, which is likely to manifest as an improvement
in performance outcomes, for example, load lifted, propulsive velocity, or jump
height. Performance enhancement can also occur shortly after exposure to a highintensity eccentric conditioning stimulus. The high-intensity nature of the
conditioning stimulus can result in continued excitation of the nervous system and
enhanced contractile function at a physiological level which, from a performance
perspective, can lead to an increase in muscle force output and rate of force
development for a given level of stimulation (Blazevich and Babault, 2019).
Despite much evidence supporting PAPE in a general training context
(Blazevich and Babault, 2019), research investigating the PAPE effects associated
with eccentrically biased loading is less prominent. The research that is available is
indeterminate; however, recently published research findings indicate that PAPE
outcomes are very sensitive to the combination of eccentric and concentric load
applications (Merrigan et al., 2020a). The authors suggest that PAPE occurs when
there is a large relative difference (≥40% 1RM on weight releasers) between
concentric to eccentric load, which provides useful insight for prospective
investigations. Moreover, they reported concentric power increased when total load
was 120% 1RM, with only 65% 1RM during the concentric phase (55% 1RM on
weight releasers), while there was no change when total load was 120% 1RM and
80% 1RM during the concentric phase (40% 1RM on weight releasers). In contrast,
other researchers have reported increased eccentric work (unsurprisingly),
concentric work, and eccentric and concentric rate of force development (RFD)
during AEL loaded squats (105% 1RM eccentric phase, 80% 1RM concentric
phase: 25% 1RM on weight releasers), especially when performed as cluster sets,
compared to traditional loaded (80% 1RM) sets (Wagle et al., 2018a, 2018b).
However, it is not currently known how the acute performance-enhancing effects
may translate into chronic neuromuscular adaptations, or whether the increased
loads during the eccentric phase result in chronic adaptations as reported with
increased eccentric loads during other eccentric training modalities.
This section has provided a brief overview of the acute physiological responses
to eccentric training. For a more comprehensive review the authors recommend
reading the review article by Douglas et al. (2017).
Longitudinal responses
There is a wealth of evidence indicating that habitual use of eccentric exercise
reduces neural inhibition (Aagaard, 2018); increases muscle activation (Higbie et
al., 1996; Hortobágyi et al., 1996); increases agonist neural drive; and decreases
coactivation of antagonist muscles (Seger and Thorstensson, 2005), and also
appears to facilitate the recruitment of type II motor units and shifts the muscle
towards a faster phenotype (Hortobágyi et al., 1996; Friedmann-Bette et al., 2010),
with Friedman-Bette et al. (2010) using AEL. Habitual use of eccentric exercise has
shown to increase eccentric, isometric, and concentric force-producing capacity
(Higbie et al., 1996; Hortobágyi et al., 1996; Cadore et al., 2014), resulting in
enlargement of muscle cross-sectional area (Vikne et al., 2006; Bogdanis et al.,
2018), with some researchers observing a bias towards the development of fasttwitch muscle fibres (Friedmann-Bette et al., 2010). It is worth noting that, when
matched for load or work, the hypertrophic adaptations appear comparable between
concentric and eccentric muscle actions (Franchi et al., 2014; Schoenfeld et al.,
2017); however, the advantage of eccentric training is that loads greater than those
used during traditional concentric or isotonic training are possible, resulting in
higher forces, which likely result in greater stimuli for adaptation (Walker et al.,
2016, 2017).
Researchers have reported that eccentric exercise stimulates a distinct myogenic
response for architectural remodelling (Franchi et al., 2014), which has been
associated with an increase in fascicle length (Baroni et al., 2013; Franchi et al.,
2014; Timmins et al., 2016), resulting in an increased potential for fascicle
shortening and lengthening velocities and therefore increased power. Furthermore,
the use of heavier loads made possible by eccentric training results in greater force
production, tendon load, and therefore tendon adaptations, such as cross-sectional
area and stiffness (Malliaras et al., 2013). An increase in tendon stiffness could
reduce the delay time between muscle activation and movement onset to facilitate
the rapid transmission of muscle force to the skeletal system (Lindstedt et al., 2001;
Brumitt and Cuddeford, 2015), thereby enhancing RFD and SSC function. A
summary of the physiological responses to eccentric training is given in Table 12.2.
Although there is not a clear consensus within the scientific literature, these
adaptive responses appear to lend towards a stronger, larger, faster contracting
muscle. These features enhance the muscles’ potential to rapidly produce force and
therefore generate greater power. Given this, there is a great deal of interest from
athletes, coaches, and practitioners in the different methods and applications of
eccentric training. However, much of the research lacks ecological validity due to
the use of varying protocols that are rarely, if ever, applied in practice, e.g., singlejoint isokinetic training, high training volumes, exclusion of other modes of training
rather than used as a supplemental mode of training.
Table 12.2 Summary of the physiological responses to eccentric training regimes and the role of these
responses in developing muscle hypertrophy, strength, and power output
Hypertrophy
Strength
Power output
Hypertrophy
Strength
Power output
↑ Anabolic signalling
↑ Motor unit recruitment
↑ Motor unit recruitment
↑ Satellite cell activation
↑ Activation of motor cortex
↑ Activation of motor cortex
↑ Motor unit recruitment
↑ Force production capacity
↑ Force production capacity
↑ Activation of motor cortex
↑ Motor unit discharge rate
↑ Motor unit discharge rate
↑ Force production capacity
↑ Muscle–tendon unit stiffness
↑ Muscle–tendon unit stiffness
↑ Fast-twitch motor unit
preferential recruitment*
↓ Inhibitory response
↑ Type IIx fibre composition
(phenotype shift)
↑ Tendon cross-sectional area
↑ Preferential fast-twitch motor
unit recruitment*
↓ Inhibitory response
↑ Muscle fascicle length
↑ Type IIx fibre composition
(phenotype shift)
↑ Excitation–contraction coupling
rates
↑ Muscle fibre shortening velocity
↑ Preferential fast-twitch motor
unit recruitment*
*Questionable.
Adapted from Suchomel, T., Wagle, J.P., Douglas, J.H., Taber, C.B., Harden, M., Haff, G.G. & Stone, M.
(2019). Implementing eccentric resistance training. Part 1: A brief review of existing methods. Journal of
Functional Morphology and Kinesiology, 4, 38.
There are a few exceptions to the longitudinal laboratory-based approaches to
eccentric training, with two interesting AEL studies, conducted by Walker and
colleagues (2016, 2017). Walker et al. (2016) conducted a 10-week intervention
comparing traditional training performed twice per week (including 6RM loads on
day one and 10 RM loads on day two) with AEL training with an additional 40%
load during the eccentric phase of each exercise, in trained men. After completion
of the 10-week training period there were comparable increases in muscle mass and
eccentric torque between groups, but the AEL group demonstrated greater increases
in isometric torque and repetitions to failure. In another study, using a comparable
training protocol, Walker et al. (2017) reported greater increases in maximum
voluntary isometric contraction and lower-limb muscle mass in response to training
with AEL when compared to training with traditional resistance-training methods.
Harden et al. (2020) recently presented an interesting 4-week training study
comparing traditional training and AEL using a customised leg press, with an
additional group of sprint track cyclists also performing AEL. All groups
demonstrated significant and meaningful improvements in concentric and eccentric
strength and 1RM squat, but the AEL training resulted in the greatest
improvements. In contrast to most other studies, eccentric loads were based on an
eccentric 1RM performed on the leg press. Patterson and Raschner (2020) also
present an interesting case study demonstrating the longitudinal benefits of
supramaximal eccentric training in an alpine ski racer, albeit using a specialised
device (intelligent motion lifter) which permits eccentric and isokinetic training
during traditional free weight exercises.
This section has provided a brief overview of the longitudinal physiological
responses to eccentric training (Table 12.2). Several resources are available that
discuss the adaptive response in greater detail. The authors recommend
comprehensive review articles by Douglas et al. (2017), Wagle et al. (2017) and
Suchomel et al. (2019) for more detailed information.
SECTION 4
Practical application of isoweight eccentric training methods
Due to the extent of the discussion that is possible for each of the classifications
mentioned in the previous section, the focus will be on isoweight modalities (e.g.,
tempo training, augmented eccentric training, AEL, eccentric-only training) that are
likely most accessible in applied settings (Table 12.3). With this approach, the
constant is the applied load/system mass (body mass + external load), although this
will change between the eccentric and concentric phases when weight releasers are
used. Performance of specific methods requires constant self-adjustment of force
application and movement velocity throughout the range of movement. The degree
of self-adjustment is determined by the type of method used and the constraints set
out in the programme. The intensity of the task is dictated by the interaction of
several variables, for example, tempo/movement velocity, ROM, system load, all of
which affect the force imposed on the musculoskeletal system, with increased ROM
and decreased velocity increasing TUT. It is very important to note that for multijoint isoweight exercises, if velocity of the eccentric phase is increased, the result is
a decrease in force production during the initial unweighting, with a force equal to
system mass during any period of constant velocity, resulting in a higher braking
force to effectively decelerate at the end of the repetition, which may negatively
affect the stimuli if a prolonged period of high eccentric forces is required.
Table 12.3 Examples of different isoweight eccentric training methods and application examples for differentlevel athletes
Method
Tempo
Augmented Accentuated
Eccentriconly/negative
Movement
type
Coupled
ECC-CON
Coupled
ECC-CON
Coupled ECC-CON
ECC only
Main feature
Submaximal
ECC load
Equal ECC
and CON
load
Submaximal
ECC load
ECC load >
CON load
Maximal or supramaximal
ECC load
ECC load > CON load
Maximal or supramaximal
ECC load
No or minimal CON load
ECC, eccentric; CON, concentric; TUT, time under tension;
ROM, range of motion; RFD, rate of force development; CMJ,
countermovement jump.
Method
Tempo
Augmented Accentuated
ECC velocity
Slow ECC
Fast
Aim
Increase
ECC TUT
CON velocity
Fast
Key
Load is not
considerations maximal
(e.g., <100%
1RM) and
does not
exploit the
capacity for
↑ ECC
loading/force
production
Slow
Eccentriconly/negative
Fast
Slow
Enhance CON Emphasise
output
ECC
neuromuscular
control and
ECC TUT,
whilst
maintaining
an element of
natural
movement
mechanics
Minimal
time delay
between
transition
maintaining
natural
movement
mechanics
Emphasising
ECC force
ECC
output and
neuromuscular ECC RFD
control
throughout
full ROM and
↑ ECC TUT
Fast
Fast
Fast
/
/
If ECC or
CON load is
too high, or if
ECC and
CON load are
not too
dissimilar this
will
negatively
affect
enhancement
of CON
output
Total load
should be
>100% CON
1RM
Total load
should be
>100%
CON 1RM
Total load
should be
>100% CON
1RM
Generally
achieved via
plyometric
style tasks
ECC, eccentric; CON, concentric; TUT, time under tension;
ROM, range of motion; RFD, rate of force development; CMJ,
countermovement jump.
Fast
Method
Tempo
Augmented Accentuated
Example for
advanced
athlete
As
preparation
for
augmented
or
accentuated
ECC
training. Sets
of 3
repetitions at
85–90%
1RM. ECC
phase ~3
seconds,
CON phase
maximal
intent
Weight
releasers (e.g.,
total 80%
1RM – ECC
40%, CON
40%) ECC
and CON
phases fast
Weight
releasers
(100–150%
1RM, e.g.,
total 120%
1RM – ECC
40%, CON
80%)
Weight
releasers
(100–120%
1RM, e.g.,
total 120%
1RM –
ECC 60%,
CON 60%)
In power rack
with safety
bars
Depth
landing: ↑
drop height
> max. jump
height. Add
weight vest.
Bilateral to
unilateral
Example for
intermediate
athlete
Hypertrophic
stimulus.
Sets of 8
repetitions at
~65% 1RM.
ECC phase
~5 seconds,
CON phase
maximal
intent
CMJ with
handheld load
release (i.e.,
resistance
bands or
dumbbells
[jump to box
if using
dumbbells, to
avoid landing
on them])
Weight
releasers
(~100% 1RM,
e.g., ECC
50%, CON
50%)
Weight
releasers
(~100%
1RM, e.g.,
ECC 60%,
CON 40%)
In power rack
with safety
bars
Depth
landing:
moderate
drop height
~ max. jump
height
Prerequisites
for novice
Controlled
Bodyweight
ECC phase
CMJ
of movement
through full
ROM with
clear pause
prior to CON
phase
Repeated
CMJs
Submaximal
load and
tempo
Depth
landing:
CMJ and
stick landing
Deceleration
following
submaximal
effort short
sprint
ECC, eccentric; CON, concentric; TUT, time under tension;
ROM, range of motion; RFD, rate of force development; CMJ,
countermovement jump.
Eccentriconly/negative
Tempo
Tempo training is characterised by purposefully reducing the ‘natural’ velocity of
the exercise during the eccentric (lowering) phase, while using the same external
load throughout both phases (eccentric and concentric). In the context of eccentric
training, the duration of the lowering phase is prolonged, and the duration of the
lifting phase can be performed, in a controlled manner, at a low velocity, or
explosively (this should depend on the desired adaptive response, e.g., low velocity
to increase TUT for hypertrophy, with maximal intent for strength and power
development). However, practitioners must consider that extending the duration of
the lowering (eccentric) phase can result in a reduction in key outputs (e.g., velocity
and power) during the lifting (concentric) phase. For example, Wilk et al. (2019)
reported that an imposed 6-second lowering duration had an adverse effect on
movement velocity and therefore power output during the concentric phase of
bench press exercise, versus a 2-second lowering duration. Therefore, if
maintenance of velocity and power throughout the concentric phase is required,
then the time spent performing eccentric muscle actions should not be excessive. In
contrast, if the eccentric phase of resistance training is performed at a high velocity,
this results in a decrease in force production, until braking occurs in the later stages
of the lowering phase, which may be counterproductive in terms of an eccentric
stimulus. This may explain why slow eccentric training demonstrated greater
improvements in performance than fast eccentric training in a cohort of rugby
players (Douglas et al., 2018).
However, this method does not make use of the higher force-producing capacity
of eccentric muscle actions and therefore is unlikely to result in many of the
previously discussed adaptations. Instead, tempo training results in overload via
TUT, which can be effective for developing neuromuscular control around key
joints and reinforcing exercise technique by promoting maintenance of muscle
tension and correct body segment positioning throughout a target ROM. This is a
particularly useful approach with novice athletes and can also be an effective way
to familiarise a more experienced athlete to eccentric training prior to implementing
the exercise with heavier or ‘supramaximal’ load (e.g., >100% 1RM).
Given that tempo training does not make use of the greater force-producing
capacity of eccentric muscle actions, this method is not the most effective at
increasing eccentric strength versus other methods. However, as TUT is positively
related to muscle hypertrophy and the premise that training biased towards
eccentric muscle actions may stimulate greater muscle hypertrophy than training
biased towards concentric muscle actions (Burd et al., 2012; Marzilger et al., 2019,
2020), tempo training could prove beneficial for muscle growth. Improved tendon
adaptations may also be achieved as a further benefit of increased TUT (Arampatzis
et al., 2010).
An example of an approach to tempo training is provided in Table 12.3 and
Figure 12.1. The loads used should be <100% 1RM, with corresponding repetitions
based on the relative load, keeping in mind that the lower the velocity used during
the eccentric phase, the greater the duration and associated fatigue. As such, either
the number of repetitions or the relative load may need to be reduced if the duration
of the eccentric phase is increased between microcycles. Numerous options are
available for progression, including decreasing the movement velocity of the
lowering (eccentric) phase, thereby increasing the TUT, increasing the relative load
or increasing the number of repetitions; however, only one of these should be used
as a progression at any one time, dependent on the primary focus of the period of
training. For example, it would make sense to increase load if strength is the
primary aim, whereas an increase in duration through a decrease in velocity would
make sense if hypertrophy is the primary goal.
Schematic diagram illustrating an approach to tempo training.
Augmented
The primary purpose of augmented eccentric training is to acutely enhance the
output during the concentric phase, via stimulation of the neuromuscular system
and potentially the SSC. During the eccentric phase a higher load is used (e.g., via
weight releasers during squats, or holding and releasing dumbbells during jumping
tasks) compared to the concentric/propulsion phase, resulting in enhanced
neurological stimulation, in an attempt to enhance the force production
characteristics during the concentric phase. To permit an appropriate velocity
during the eccentric phase the load used would normally be ≤90% 1RM, with the
weight releasers (usually loaded with 30–50% 1RM) set to make contact with the
floor and release 5–10 cm prior to the bottom of the movement, to permit sufficient
time for deceleration prior to the start of the concentric phase (performed with a
load of 40–60% 1RM).
When using weight releasers, the additional eccentric load can be applied
throughout all repetitions if a cluster set approach is utilised (see Chapter 13 for a
detailed discussion of cluster sets), which permits time for two ‘loaders’ to lift the
weight releasers and simultaneously load them back on to the barbell (Figure 12.2).
In contrast, the weight releasers can be used for additional eccentric overload
during the initial repetition and then all subsequent repetitions within the set
performed with the reduced load. Figure 12.3 provides such an example, with the
final four repetitions within the set performed as speed squats (if the back squat is
the exercise used). This approach is beneficial if time is limited or there are
insufficient coaches or athletes to reload the weight releasers on to the barbell
during each set. It is also worth noting that this may induce a PAPE effect and will
be less fatiguing than performing all repetitions using AEL.
Schematic diagram illustrating augmented eccentric training using weight releasers,
with a total of 80% 1RM as an example. # = time for loaders to place the weight
releasers back on the ends of the barbell
Schematic diagram illustrating augmented eccentric training during back squats
using weight releasers, with a total of 80% 1RM as an example.
Accentuated
The primary purpose of AEL is to permit loads >100% 1RM to be used during the
eccentric phase (Walker et al., 2016, 2017), to take advantage of the higher forces
associated with eccentric muscle actions and therefore provide the unique stimuli
discussed earlier, to elicit the unique adaptations to eccentric training. (Note: due to
the loads involved, it is essential that athletes demonstrate excellent technique on
any exercise where such loading is implemented.) When strength-speed
development is the primary focus of training, the eccentric phase should be
prolonged using a low movement velocity during the eccentric phase and the
concentric phase performed with maximal intent, albeit with a sufficient load (e.g.,
≥80% 1RM) to result in a relatively low velocity (Figures 12.4 and 12.5). In
contrast, if the primary goal is the development of speed-strength, the high total
load should still result in a low velocity during the eccentric phase, but the load on
the weight releasers should be a higher percentage of the total load, to result in a
lower total load during the concentric phase enabling higher velocities during the
concentric phase (Figures 12.6 and 12.7).
Like the format described for augmented eccentric training, two approaches can
be employed. Additional eccentric load can be used during the eccentric phase of
each repetition, in a cluster set format (Figures 12.4 and 12.6), or the additional
eccentric load can be applied during the first repetition of each set, with the
subsequent repetitions performed in the normal format, with no inter-repetition rest
(Figures 12.5 and 12.7).
Schematic diagram illustrating accentuated eccentric training using weight releasers.
# = time for loaders to place the weight releasers back on the ends of the barbell
Schematic diagram illustrating accentuated eccentric training using weight releasers.
Schematic diagram illustrating accentuated eccentric training using weight releasers.
# = time for loaders to place the weight releasers back on the ends of the barbell
Schematic diagram illustrating accentuated eccentric training using weight releasers.
Progressions within a mesocycle would usually emphasise an increase in total
load via an increased load on the weight releasers, resulting in a progressive
increase in eccentric loading. Small increases in load during the concentric phase
may also be appropriate during the concentric phase if the training focus is
strength-speed. As previously mentioned, it is possible to progress up to loads of
~140% 1RM during the eccentric phase; however, such loads should be achieved
progressively, ideally across numerous sessions. In addition, a more conservative
approach may be advantageous in stronger individuals due to the lower discrepancy
between concentric and eccentric strength compared to weaker individuals
(Hollander et al., 2007; Harden et al., 2019). As previously mentioned, an effective
eccentric load, in trained individuals, implemented by Walker et al. (2016, 2017),
was 40% greater than the concentric load (using concentric loads that corresponded
to 6RM [~85% 1RM] and 10RM [~70% 1RM] loads).
If weight releasers are not available, but a power rack is, it is possible to lower
the higher eccentric load to pins and then have training partners/teammates remove
some additional load prior to commencing the concentric phase with an
appropriately reduced load. It should be noted that while this method permits
appropriate eccentric overload, it likely nullifies any SSC benefits due to the pause
with the barbell of the pins of the power rack. This may also result in the concentric
phase feeling more difficult than when weight releasers are used. To address this,
coaches can consider loading the concentric phase relative to concentric 1RM,
which is performed from a dead stop from the pins of the power rack, to ensure an
appropriate intensity is applied to the concentric phase, given the absence of the
contribution of the SSC to concentric force output.
Eccentric only
Eccentric-only approaches can also be adopted to emphasise the musculotendinous
adaptations to supramaximal eccentric loads, although these approaches exclude
any potential acute benefits during a subsequent concentric phase, which may
manifest from neurological stimulation (e.g., acute PAPE) or utilisation of the SSC.
These approaches can more easily be applied to focus on specific muscle groups
during single-joint tasks (e.g., knee flexion and extension), especially if a specific
deficit in muscle mass or strength has been identified, most commonly in
previously injured athletes. It is also possible to adopt this approach with numerous
multi-joint exercises (e.g., front squat, split squat, bench press), when power racks
are available, or in some cases with no additional equipment (e.g., pull-up
variations).
For single-joint eccentric training, isokinetic dynamometers are commonly used
by researchers; however, even if these devices are available it takes a notable period
for individual athletes to conduct some of their training in this manner and would
not be feasible for an entire team of athletes. A simple approach for single-joint
eccentric training is to perform these exercises on standard resistance machines,
using a load >100% 1RM for a single limb, performing the concentric phase with
two limbs and then the eccentric phase with one limb. For example, if the
concentric 1RM for a single-leg knee extension is 50 kg, perform the concentric
phase with 55 kg (110% 1RM) and then lower in a controlled fashion with a single
leg. While there is a concentric component to this, it would equate to only a
bilateral 55%1RM.
For multi-joint tasks, the safe option is to perform exercises (e.g., squat
variations, Romanian deadlift, bench press) in a power rack, taking the barbell
(>100% 1RM) out of the rack and then performing a controlled eccentric phase,
throughout the desired ROM until the barbell rests on the safety pins. The height of
the safety pins should be carefully set during the warm-up sets prior to the start of
the eccentric repetitions. Ideally, spotters should be used throughout, and the
spotters can then lift the bar back to the starting position, prior to the start of the
next repetition. This approach generally results in a cluster set approach, due to the
period of rest between the end of a repetition and the bar being placed back in the
start position.
Important considerations for exercise prescription
It is important to highlight that the unique qualities mean that when training
using eccentric muscle actions, performance capacity is unlikely to conform to
recommendations that are commonly used to guide traditional, concentrically
biased exercise prescription. Therefore, different approaches to training
applications may be required to optimise eccentric training regimes, especially
in terms of the volume (sets and repetitions) due to the higher loads and
increased potential for muscle damage, especially in weaker athletes and those
unfamiliar with supramaximal eccentric exercise, or eccentric exercise in
general.
The unique features of eccentric muscle actions allow for much greater force to
be produced during muscle lengthening versus shortening. However,
traditional applications of exercise utilise the same absolute load for the
descending (eccentric) and ascending (concentric) phase of an exercise,
whereby load prescribed is limited to concentric performance. This approach
to loading does not appropriately stimulate the eccentric force-producing
capacity of muscle, as the descending portion of the lift is not loaded in
relation to the individual’s eccentric maximal force capacity. Instead,
practitioners must apply alternative methods to prompt greater force output
during the eccentric phase of exercise. This usually involves heavy external
loads and demands a very high exercise intensity.
There are a multitude of ways to apply and categorise eccentric exercise in
research and practice. Usually, isotonic eccentric exercise intensity is
prescribed as a percentage of 1RM during coupled eccentric–concentric or
concentric-only action, whereby the load will exceed, equal, or be within the
force-producing capacity of the traditional 1RM. This is typically categorised
as supramaximal (>100% 1RM), maximal (~100% 1RM), or submaximal load
(<100% 1RM), respectively.
Eccentric training volumes should be employed conservatively, due to the
associated muscle damage and DOMS, but can be easily progressed to take
account of the RBE. A conservative approach with appropriate progressions is
important to ensure compliance and to mitigate any potential negative impact
on subsequent training activities.
It is common practice for strength and conditioning practitioners, rehabilitation
professionals, and sports science researchers to prescribe eccentric training
loads grounded on traditional 1RM strength tests (Brandenburg and Docherty,
2002; Barstow et al., 2003; Friedmann-Bette et al., 2010; English et al., 2014;
Walker et al., 2016; Douglas et al., 2018). This approach to load prescription,
however, overlooks task-specificity and the possibility that some individuals
have a different tolerance for eccentric exercise. For this reason, a number of
researchers have adopted an eccentric-specific RM assessment (Spurway et al.,
2000; Gillies et al., 2006; Vikne et al., 2006; Franchi et al., 2014), in the
endeavour to increase the efficacy of eccentric training regimes or enable the
comparison of eccentric-only or concentric-only isotonic exercise. The use of
eccentric 1RMs may help to account for the individual discrepancies in the
deficits between concentric and eccentric force production; however, specific,
accessible methods to achieve this with traditional multi-joint exercise are yet
to be determined.
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13 Cluster sets: scientific
background and practical
applications
G. Gregory Haff and Mellissa Harden
DOI: 10.4324/9781003044734-16
Introduction
When constructing resistance-training programmes there are numerous
factors that must be considered in order to optimise the training stimulus.
These include exercise choice, training load, number of repetitions and sets,
exercise order, training frequency, movement velocity, and duration of rest
between sets. Largely guided by the periodised training plan, programming
of the aforementioned factors is used to deliver novel training stimuli in
order to stimulate improvements in a performance or physiological outcome
(Haff et al., 2008b). When a novel training stimulus is incorporated into the
training programme there is a greater rate of performance gain, whereas the
more familiar the athlete is with the imposed training demands, the slower
the overall gain in performance (Hodges et al., 2005). As such, the ability of
the strength and conditioning coach to construct programmes that include
appropriate training variation (to introduce novelty) is essential for guiding
the training process and maximising training outcomes. This is especially
true for the advanced or elite athlete (Haff et al., 2008b).
One potential part of the training programme where variation can be
introduced, that is often overlooked, is the structure of the set (Haff et al.,
2008a, 2008b; Tufano et al., 2017a). Traditionally, resistance-training sets
are performed in a continuous manner where no rest is taken between the
repetitions contained within the set (Haff et al., 2003, 2008b) and rest is
prescribed between each individual set (i.e., inter-set rest) (Figure 13.1a).
Example set structures used in resistance training.
While the traditional set is the most commonly used programming
structure, an alternative approach to organising the set is to provide interrepetition (i.e., rest between individual repetitions) (Figure 13.1b) or intraset (i.e., rest between groups of repetitions within a single set) rest intervals
that last between 15 and 45 seconds (Figure 13.1c). Globally the inclusion
of periodic rest intervals, whilst maintaining the inter-set rest interval, has
been termed the cluster set within the scientific (Haff et al., 2003, 2008a,
2008b; Latella et al., 2019) and applied literature (Rader, 1958; Roll and
Omer, 1987; Siff and Verkhoshansky, 1999; Polliquin, 2001; Thibaudeau,
2006; Miller, 2011a). While the use of the cluster set has become a popular
research topic and has increasingly become a part of the programming
practices of strength and conditioning coaches, the roots of this training
structure can be traced back to the late 1950s when Perry Rader discussed
this topic in IronMan magazine (Rader, 1958). Furthermore, even though
the cluster set has a rich history in the training literature, many modern
researchers have classified any modification to the set structure or inclusion
of periodic rest into a series of repetitions as a cluster set (Marshall, 2011;
Marshall et al., 2012; Oliver et al., 2013; Tufano et al., 2017a). As a result,
there is debate amongst sport scientists and coaches about what a cluster set
entails, the scientific rationale for the use of a cluster set, and how to
actually employ this programming strategy into the training practices of
athletes. Therefore, the primary goals of this chapter are to elucidate these
topics and provide the strength and conditioning coach with useful
information that can inform how they utilise various set structures within
their resistance-training programmes.
SECTION 1
Defining the set
In order to understand the various set configurations that can be employed
as part of a resistance-training programme, it is essential that the strength
and conditioning coach understand the various terminology that can be used
to describe the set’s structure (Tufano et al., 2017a). There are four basic
categories of sets: (1) traditional; (2) cluster; (3) rest–pause; and (4) rest–
redistribution sets.
Traditional sets
The set is typically defined as a traditional set when the individual
repetitions contained within it are completed in a continuous manner
without any inter-repetition or intra-set rest intervals (Tufano et al., 2017a)
and there is a predetermined inter-set rest interval. The traditional set
configuration can be employed with a wide range of repetitions and interset rest intervals in order to modulate the training stimulus that the athlete is
exposed to and align with specific training targets. For example, <6
repetitions are traditionally used to target maximal strength, whilst >12
repetitions are typically aligned with strength endurance (Haff and Haff,
2012). Depending on the athlete’s level of development, different repetition
ranges can be aligned with different training targets (Table 13.1). For
example, repetition ranges of 8–12 are aligned with hypertrophy training for
novice athletes, whilst 6–12 repetitions are used to target this adaptation
with intermediate and advanced athletes (Haff and Haff, 2012). Ultimately
the traditional set is a time-tested and versatile way of programming
resistance training.
Table 13.1 Traditional training emphasis alignments with repetition ranges
Training emphasis
Traditional set repetition schemes
Training emphasis
Traditional
set
repetition schemesAdvanced
Novices
Intermediate
Muscular endurance
12–20
12–20
12–25
Hypertrophy
8–12
6–12
6–12
Muscular strength
≤6
≤6
≤6
Muscular power
Novices
n/a
Intermediate
3–6
Advanced
1–6
Adapted from Haff GG and Haff EE. Resistance training program design. In: M.H. Malek & J.W.
Coburn (eds.) NSCA’s Essentials of Personal Training. Champaign, IL: Human Kinetics, 2012,
pp. 359–401; Table 15.13, p. 380.
Cluster sets
The term “cluster set” has mistakenly become a popular “umbrella” term
for any set structure that differs from a traditional set (Tufano et al., 2017a).
In tracing the historic roots of the cluster set, the utilisation of interrepetition rest was originally referred to as the “rest–pause” method due to
the interspersing of a short rest interval, or a pause, between individual
repetitions within the set or what could be considered a period of defined
work (Rader, 1958). As time passed the rest–pause terminology morphed
into the current cluster set terminology when defining the manipulation of
the set structure in order to incorporate inter-repetition (Roll and Omer,
1987; Siff and Verkhoshansky, 1999; Haff et al., 2003) or intra-set rest
intervals (Haff et al., 2008a). While Tufano et al. (2017a) incorrectly
attribute the cluster set term to Haff et al. (2003), it is important to note that
Roll and Omer (1987) utilised the term in their paper published in 1987,
which was 16 years prior to the paper published by Haff et al. (2003). In
their paper, Roll and Omer (1987) defined the cluster set as performing
predetermined sets of 2–6 repetitions with 20–30 seconds’ rest between
each repetition in order to ensure that maximal intensity is achieved on each
repetition. Siff and Verkoshansky (1999) defined the cluster set as
performing one or more repetitions with a 10–20-second rest interval
between individual repetitions or groups of repetitions contained within the
set structure. They proposed the basic cluster set should be performed for a
total 4–6 repetitions with a 5 repetition maximum (RM) load, and that there
are two sub-categories of the cluster set: extensive and intensive cluster sets
(Siff and Verkhoshansky, 1999). While both sub-categories of cluster sets
were performed with 4–6 repetitions, the extensive cluster set was proposed
to use a 4–6RM load and a 10-second rest between each repetition or group
of repetitions, whereas the intensive cluster set was structured to use a load
between 75 and 90% of 1RM with a 20-second rest between each repetition
or group of repetitions (Siff and Verkhoshansky, 1999). When carefully
examining the work of Siff and Verkoshansky (1999) it is clear that their
definition of the cluster set is very similar to definitions presented by Roll
and Omer (1987) and Haff et al. (2003). While these authors’ definitions are
true to the historic roots of the cluster set concept (Rader, 1958), many
contemporary authors have mistakenly tried to make the cluster set
terminology into an “umbrella” term describing any manipulation of the set
structure (Jukic and Tufano, 2019; Merrigan et al., 2020a; Tufano et al.,
2020).
While the main alterations to the traditional set have historically been
based upon the insertion of inter-repetition or intra-set rest intervals (Haff et
al., 2008a), an additional way to modify the set was proposed by Haff et al.
(2008a, 2008b) where the loading pattern of each repetition or groups of
repetitions contained within the set is modified. Generally, five possible
variations to the loading pattern utilised in a set can be constructed:
standard, undulating, wave, ascending, and descending cluster set structures
(Figure 13.2) (Haff et al., 2008a, 2008b).
Example undulating, wave, ascending, and descending cluster sets.
Standard cluster sets: The standard cluster set is the most basic
modification of the traditional set structure (Haff et al., 2008a, 2008b).
With this type of cluster set the load is maintained across all repetitions
within the set and only the inter-repetition or intra-set rest interval is
modified (Figure 13.1b and 13.1c; Tufano et al., 2017a).
Undulating cluster set: The undulating structure is constructed so that
the resistance used across the set is increased in a pyramidal fashion
(Figure 13.2a; Haff et al., 2003). Depending upon the loading
parameters, the repetitions on the descending portion of the pyramid
will display a form of post-activation performance enhancement
(PAPE), as indicated by increases in the velocity of each repetition
(Haff et al., 2003).
Wave-loaded cluster set: Another loading strategy is to alternate
intensity from repetition to repetition (Figure 13.2b), or between
groups of repetitions, in order to create what is termed a wave-loaded
cluster set. Similarly to an undulating cluster set, a PAPE response is
stimulated by the higher loaded repetitions resulting in higher
velocities of movement occurring during repetitions where lower loads
are employed.
Ascending cluster set: The cluster set structure can be further modified
so that the load lifted increases across the set, resulting in the highest
intensity being lifted on the last repetition of each set (Figure 13.2c).
After the inter-set rest interval, it is hypothesised that higher velocities
of movement will occur during the first repetitions of subsequent sets
due to the PAPE-inducing effects of the higher-load repetitions.
Descending cluster set: The last loading structure that can be
programmed to modify the set structure is the descending cluster set
where the first repetition of the set is a maximal or near-maximal
attempt followed by subsequent repetitions with progressive reduction
in repetition loads (Figure 13.2d). It is hypothesised that the increased
velocity that occurs as the intensity decreases across the set is a result
of a PAPE response stimulated by the heaviest repetition(s) at the start
of the set.
While these five types of cluster sets have been used in many strength and
conditioning settings, much more research is needed to further our
understanding of how these loading structures acutely impact movement
velocity and translate into chronic training responses.
In addition to modifying the loading structure used with the cluster set,
the number of repetitions that are completed before inserting a rest interval
can be varied to change the training stimulus (Figure 13.3; Haff et al.,
2008a, 2008b; Tufano et al., 2017a). For example, three sets of 12
repetitions can be programmed with a 120-second inter-set rest interval and
30 seconds inter-repetition or intra-set rest which is used after every two
(Figure 13.3a; Tufano et al., 2016), three (Figure 13.3b), or four repetitions
(Figure 14.3c; Haff et al., 2008a).
Example cluster set repetition modifications.
By modulating the number of repetitions contained within the cluster set
the targeted training outcome can be altered. For example, for a given load
there will be a greater velocity decline for a cluster set containing four
repetitions in comparison to clusters of two repetitions (Tufano et al., 2016).
Therefore, using cluster sets with fewer repetitions in each cluster will
minimise velocity loss and will therefore be more appropriate for
developing neuromuscular power. Conversely, if maximising muscular
hypertrophy is the training target, then including more repetitions and
higher training loads within the cluster would result in a greater velocity
decline across each cluster (Pareja-Blanco et al., 2017) and allow for more
time under tension, and greater total work (Tufano et al., 2017b), which
may be more effective to stimulate hypertrophy. Interestingly, if the load is
aligned with the RM load for the number of repetitions contained within the
cluster, velocity loss is similar to that which can occur during high-volume
traditional sets (Tufano et al., 2017b). For example, similar velocity
declines occur when: (1) 12 repetitions are performed at 60% of 1RM; (2)
clusters of four repetitions are performed at 75% of 1RM with 30 seconds’
intra-set rest intervals; and (3) clusters of two repetitions performed at 80%
of 1RM with 30 seconds’ intra-set rest intervals (Tufano et al., 2017b).
Interestingly, the concentric time under tension is increased when smaller
cluster sets are performed with higher intensities when compared to
traditional sets. In this case it may be expected that the use of the cluster set
will provide a greater stimulus for either hypertrophy or strength, when
compared to a traditional set structure. Ultimately, through the manipulation
of the number of repetitions within the cluster set, the training stimulus can
be varied in a multitude of ways. This equips the strength and conditioning
coach with many options for introducing training variation and novelty
within an athlete’s training regime (Haff et al., 2008a).
Rest–pause method
The “rest–pause” terminology was originally used to define what is now
referred to as a cluster set, where inter-repetition rest is applied within a
pre-defined set (Rader, 1958). However, the modern application of the
“rest–pause” set has deviated significantly from this original model. As
such, the rest–pause terminology is used when periodic rest is employed to
extend the number of repetitions that can be performed within sets
performed to failure (Keogh et al., 1999; Marshall, 2011; Marshall et al.,
2012; Tufano et al., 2017a). For example, a rest–pause set could be
performed to muscular failure, typically with an 8–12RM load, followed by
20 seconds’ interval and another set to failure. A 20-second interval is
inserted after each set to failure until a targeted number of repetitions are
completed (Marshall, 2011; Marshall et al., 2012; Prestes et al., 2019).
While a high volume of training is associated with the modern incarnation
of the rest–pause method (Marshall et al., 2012; Prestes et al., 2019), it is
important to note that it is not possible to predetermine the number of
repetitions that are completed because this method employs a training-tofailure strategy (Tufano et al., 2017a). As such, it is difficult for the strength
and conditioning coach to control the volume of training that the athlete
performs.
The rest–pause set configuration strategy is often used when attempting
to increase muscular endurance or maximise hypertrophic gains. While
training-to-failure strategies have become popular, recent research has
highlighted that training to failure is not necessary to maximise
hypertrophic or maximal strength gains (Carroll et al., 2019a, 2019b). In
fact, strength and power gains are often muted with the use of training to
failure when compared to not training to failure (Izquierdo et al., 2006;
Carroll et al., 2019b), which may impact the effectiveness of this cluster set
configuration strategy when looking specifically to enhance muscle strength
and/or power.
Rest–redistribution
Recently several authors have proposed the concept of rest–redistribution as
an additional cluster set structure (Jukic and Tufano, 2019; Tufano et al.,
2020; Merrigan et al., 2020a; Jukic et al., 2020; Merrigan et al., 2020b).
With this set structure, the idea is to take the inter-set rest interval and
redistribute this rest to either provide inter-repetition or intra-set rest and
reduce the time burden associated with the use of cluster sets (Tufano et al.,
2020). While at first glance using the cluster set terminology to define this
practice seems logical, it is important to note that this set configuration is at
odds with the original incarnation of the cluster set (Rader, 1958; Roll and
Omer, 1987; Siff and Verkhoshansky, 1999), where the inter-set rest interval
applied is similar to what is used when using traditional sets. In reality, the
rest–redistribution model should not be considered a cluster set, but instead
should be referred to as a short inter-set rest interval strategy.
Recently researchers have determined that the rest–redistribution
strategy is not as effective at modulating fatigue-induced changes in
performance when compared to the implementation of more traditional
cluster set protocols (Jukic et al., 2020). It is important to remember that
one of the main drivers of the performance gains associated with the cluster
set is the additional inter-repetition or intra-set rest allowing for acute
performance enhancement (Jukic et al., 2020) via increased movement
velocities or allowing higher training loads to be utilised. It appears that
while the rest–redistribution strategy has its use as a programming strategy,
it does not produce the same outcomes as cluster sets. Due to the
aforementioned discrepancies between the rest–redistribution method and
cluster sets, it is not appropriate to classify rest–redistribution as a cluster
set.
SECTION 2
Scientific basis for the cluster set
When considering the use of the cluster set as part of the programming
process it is important to consider how these novel set structures differ from
traditional sets (Haff et al., 2008a, 2008b). The different physiological and
performance responses to the traditional and cluster set should assist in
informing how the strength and conditioning coach utilises these set
configurations as part of a performance-based strength-training programme.
Physiological, performance, and psychological responses to
traditional sets
When examining the traditional set configuration, it is well documented that
as the duration of the set is extended there is a concomitant reduction in
movement velocity (Gorostiaga et al., 2010; Tufano et al., 2016), power
output (Hardee et al., 2012b; Tufano et al., 2016), and technical proficiency
(Hardee et al., 2013). These reductions are likely reflective of a fatigue
response that occurs due to a combination of central (neural) and peripheral
(muscular) factors (Zajac et al., 2015; Enoka and Duchateau, 2016). While
fatigue was once thought to be necessary to maximise resistance traininginduced adaptations, there is now an ever-growing body of scientific
evidence that has strongly refuted the theory that momentary neuromuscular
failure (i.e., RM paradigms) is superior to not training to failure (Folland et
al., 2002; Izquierdo et al., 2006; Carroll et al., 2019a, 2019b).
When performing resistance training with a traditional set configuration
there can be reductions in maximal force-generating capacity, rate of force
development, and rate of relaxation within 5–9 maximal contractions
(Viitasalo and Komi, 1981). These reductions in performance capacities are
likely related to a reduced availability of phosphocreatine (PCr) and the rate
of adenosine triphosphate (ATP) resynthesis within the working muscles
(Bogdanis et al., 1995, 1996, 1998; Gorostiaga et al., 2012). Supporting this
contention, Sahlin and Ren (1989) report that maximal contractions result in
significant decreases in ATP and PCr concentrations. In addition to these
changes there are typically significant increases in creatine (Cr) and lactate
(La) (Gorostiaga et al., 2012) as well as reductions in muscle glycogen
(Haff et al., 2000), which are impacted by the number of repetitions
contained within the set as well as the load lifted (Robergs et al., 1991). For
example, when sets of five repetitions are performed on the leg press, there
is a ~26.8% reduction in the concentration of PCr, whilst there is a ~85%
reduction when sets of ten are performed (Gorostiaga et al., 2012). As PCr
decreases there is a concomitant increase in La accumulation as the
utilisation of glycogen increases across the series of sets typically contained
with a resistance-training programme. These changes are associated with
reductions in peak and mean power output across the series of repetitions,
with sets of ten repetitions displaying the greatest declines. Ultimately, the
changes in substrate availability across the set partially explain the
reductions in movement velocity and the expression of power that are
associated with traditional sets.
Theoretical and scientific basis for the cluster set
The modification of the set to include short inter-repetitions or intra-set rest
intervals has been hypothesised to improve the quality of performance of
each repetition contained within the set (Haff et al., 2003, 2008a, 2008b).
Theoretically, the use of a cluster set allows for: (1) a maintenance or
enhancement of training intensity; (2) the maintenance of velocity and force
production; and (3) the performance of a greater amount of total work
during the set (Haff et al., 2008a, 2008b; Tufano et al., 2017b). These
potential benefits are likely a result of the cluster set allowing for partial
recovery during the additional rest that is placed within the set structure.
It has been hypothesised that the inclusion of 15–30 seconds of interrepetition or intra-set rest may result in the partial replenishment of ATP
and PCr that offsets the typical reductions in these substrates seen with the
performance of multiple-repetition traditional sets (Haff et al., 2008a,
2008b). The replenishment of ATP occurs rapidly, with 70% of ATP
restored in as little as 30 seconds (Hultman et al., 1967), while the
resynthesis of PCr is slightly slower, with 50% restoration occurring within
30 seconds (Sahlin and Ren, 1989). The partial replenishment of ATP and
PCr associated with inter-repetition or intra-set rest likely results in
improvements in performance capacity. For example, Sahlin and Ren
(1989) reported that the addition of 15 seconds of rest resulted in one-half
of the decrease in force-generating capacity being restored, returning force
production to 79.7 ± 2.3% of maximal voluntary contraction (Sahlin and
Ren, 1989). Additionally, when 30 seconds of extra rest is employed, less
lactate is produced when compared to repetitions that are performed with a
traditional set structure (Goto et al., 2005). Collectively, these physiological
responses provide the theoretical framework for explaining the performance
benefits of cluster sets.
An additional benefit of all cluster sets is that they may allow for greater
loads to be lifted, which results in a greater time under tension and average
force production when compared to traditional sets (Tufano et al., 2017b).
Interestingly, when greater loads are lifted with the cluster set, the velocity
decline across the set is not different from what is seen with traditional sets
performed with lower loads. For example, Tufano et al. (2017b) report that
performing three sets of 12 repetitions with cluster sets of two with 80% of
1RM or cluster sets of four with 75% of 1RM, with 30 seconds of intra-set
rest, results in a similar decline in velocity across the three sets as seen
when performing traditional sets of 12 with 60% of 1RM. In fact, one of the
main benefits of the cluster set is that it allows for greater loads to be lifted
for more repetitions, which can enhance the hypertrophic and strength gains
associated with the training process. It is, however, important to consider
that when using higher loads with cluster sets the coach should consider the
impact that this will have on cumulative fatigue and delayed-onset muscle
soreness. As such it is recommended to consider progressively introducing
cluster sets to the athlete’s training programme.
Acute responses to cluster sets
As noted previously, there is a reduction in movement velocity (Tufano et
al., 2016) and power (Gorostiaga et al., 2012) across a traditional set, which
can be offset by placing inter-repetition or intra-set rest into the set (Tufano
et al., 2017a). This effect is most noted when this practice is employed with
lower-body or whole-body resistance-training exercises that are performed
with moderate to heavy loads which have the potential to generate
significant fatigue (Latella et al., 2019). For example, Haff et al. (2003)
report higher movement velocities when performing cluster sets of five
repetitions with 30 seconds of inter-repetition rest with clean pulls
performed with loads of 90–120% of the 1RM power clean, when
compared to traditional sets. Importantly, when the cluster set was utilised
with higher loads (i.e., 120% of 1RM power clean), the ability to maintain
movement velocity was demonstrated. These findings help strengthen the
argument that one of the main benefits of using cluster sets is to allow
athletes to lift greater loads and maintain a higher quality of movement
(Tufano et al., 2017b).
In a series of papers, Hardee et al. (2012a, 2012b, 2013) have provided
strong evidence for the positive acute impact of using cluster sets of six
repetitions with 20 and 40 seconds of inter-repetition rest with the power
clean performed at 80% of 1RM. Specifically, Hardee et al. (2012b) clearly
demonstrated that movement velocity during the power clean is better
maintained with longer inter-repetition rest intervals (i.e., 40 seconds) when
compared to shorter inter-repetition rest intervals (i.e., 20 seconds) or
traditional sets. In addition to maintaining movement velocity, the use of
cluster sets allowed for a better maintenance of movement quality (Hardee
et al., 2013), which can be negatively impacted by changes in motor control
that occur when fatigue accumulates (Halil et al., 2009). Importantly, even
though athletes were able to perform the power clean with higher velocities
and better technique during the two cluster set protocols, the athletes’ rating
of perceived exertion was significantly lower than seen when using the
traditional set (Hardee et al., 2012a). Collectively, the work of Hardee et al.
(2012a, 2012b, 2013) strengthens the argument that cluster sets allow for
enhanced acute performance responses which, if repeated consistently, may
lead to better-quality training and greater long-term training responses
(Hardee et al., 2012a, 2012b, 2013).
It is well documented that the load lifted during resistance-training
exercise exerts a significant effect on the physiological adaptations that
occur in response to a resistance-training programme (Fry, 2004). The
ability to consistently train with higher loads may allow for greater strength
gains as well as hypertrophic responses (Fry, 2004; Schoenfeld et al., 2016).
Based upon these data, it is clear that the cluster set provides a powerful
tool for acutely increasing the load that can be used for a given number of
repetitions, whilst maintaining the velocity and quality of the repetitions
performed (Tufano et al., 2017b). This is important because it clearly shows
that the cluster set allows the athlete to acutely train at higher intensities,
which is likely to lead to significantly greater longitudinal training effects.
Longitudinal responses to cluster sets
While a lot of research clearly demonstrates that there are positive acute
mechanical and physiological responses to cluster sets, there is far less
research examining the impact of the long-term effects of implementing
cluster sets within a resistance-training programme (Tufano et al., 2017a;
Latella et al., 2019). Due to relatively few longitudinal studies (Hansen et
al., 2011; Zarezadeh-Mehrizi et al., 2013; Arazi et al., 2018; Vargas-Molina
et al., 2020) that explore the implementation of cluster sets and the vastly
different strategies used to create the cluster set in these studies, it is
difficult to determine the actual impact of the cluster set on hypertrophy,
strength, or power output.
Recently, Vargas-Molina et al. (2020) compared the impact of traditional
and cluster sets that used 12 repetitions per set. Each cluster set was
organised into groups of three repetitions with 3RM loads and 20 seconds
of intra-set recovery with squats, deadlifts, and the leg press. The cluster set
was associated with greater increases in muscular strength and fat-free mass
in the lower body when compared to traditional sets. These findings support
the contentions of Tufano et al. (2017b, 2017c), who suggested that the use
of cluster sets with high-volume sets would allow for a greater mechanical
stimulus that could be translated into increases in muscular strength and
hypertrophic gains. Based upon this line of reasoning it seems plausible to
suggest that integrating cluster sets within a training programme that targets
strength endurance or hypertrophic outcomes may maximise performance
outcomes as well as hypertrophic responses.
In another longitudinal study, Arazi et al. (2018) examined the
integration of cluster sets within a periodised training programme. Across
an 8-week training study various standard cluster set structures were
performed with 10–30 seconds of inter-repetition rest with squats, bench
press, military press, jump squats, and bench press throws. When compared
to a group that performed the same training programme with traditional
sets, the use of cluster sets resulted in small but significant improvements in
vertical jump performance and similar gains in maximal strength. Similarly,
Zarezadeh-Mehrizi et al. (2013) implemented cluster sets that utilised 10–
30 seconds of inter-repetition rest or traditional sets with the same relative
intensities. After 10 weeks of training there were greater improvements in
vertical jump performance and similar strength gains when cluster sets were
utilised within the training programme. Collectively, these studies support
the contentions of Haff et al. (2008a, 2008b) that cluster sets are best used
when attempting to improve performance in ballistic activities, such as
jumping, while traditional sets may be better suited for stimulating strength
gains. While this is a logical suggestion, it is necessary to highlight that the
use of the same relative training load for both cluster and traditional sets
could partially explain the lack of difference in strength gains between set
conditions. However, if we consider that one of the main benefits of cluster
sets is that higher training loads can be utilised in training when compared
to traditional sets, it is likely that if programmed correctly (i.e., this benefit
is exploited), the cluster set has the potential to stimulate greater increases
in strength, in addition to the noted improvements in ballistic performance.
While it appears cluster sets, when programmed correctly, exert positive
benefits on hypertrophy, maximal strength, and explosive performance,
much more research is needed. It is suggested that future research must
consider the load applied to the cluster sets. To add, it is important that
researchers consider the ecological validity of how cluster sets are actually
programmed in applied resistance-training settings.
SECTION 3
Practical applications of cluster sets
There are numerous ways to utilise the cluster set in order to align with the
training goals established within the periodised training plan (Haff et al.,
2008a, 2008b). By manipulating the number of repetitions, inter-repetition
or intra-set rest intervals, and loading configurations contained within the
cluster set, the athlete can be exposed to a unique training stimulus which
can magnify the adaptive responses and performance gains achieved.
Programming cluster sets
When considering the use of cluster sets it is important to first establish the
training outcomes that are being targeted by the periodised training plan
(Haff et al., 2008a). Once the training programme outcomes are established,
the coach can begin the programming process.
The first step in the implementation of cluster sets is to determine which
exercises will be aligned with cluster set strategies (Figure 13.4).
Suggested exercise alignments for cluster sets.
Typically, cluster sets are utilised with ballistic exercises, such as the
weightlifting derivatives (i.e., clean/snatch pulls, power clean/snatch),
bench press throws, and jump squats (Haff et al., 2008b; Latella et al.,
2019). Additionally, cluster sets have been utilised with traditional strengthbased exercises such as the deadlift (Arazi et al., 2018), back squat (Tufano
et al., 2017b), and bench press. While all of these exercises could use
cluster set strategies it is important to note that not every exercise in a
training session needs to or should employ cluster sets. In fact, only 1–2
exercises per training session should be performed with cluster set
strategies, whilst the remaining exercises within the session should employ
traditional sets, in order to maximise the efficiency of the training session
(Table 13.2) (Haff et al., 2008a, 2008b).
Table 13.2 Example training session employing cluster sets
Exercise
Sets × Reps Intensity
(% RM)
Intensity InterSet type
(kg)
repetition rest
(s)
Mid-thigh
clean pull*
3
×
5
110%
132
0
Power clean
3
×
5/1
90%
108
20
Back squat
3
×
5
80%
144
0
Traditional
Bench press
3
×
5
75%
83
0
Traditional
Traditional
Standard
cluster
Note: 5/1 = total repetitions in set/repetitions in cluster. RM, repetition maximum. *Percentage of
maximum power clean. Power clean 1RM =120 kg; back squat 5RM = 180 kg; bench press
5RM = 110.
An example of this type of planning is presented in Table 13.2 where an
individual training session is presented in which a standard cluster set
structure is programmed for the power clean and traditional sets are planned
for the remaining exercises.
After determining which exercises will utilise cluster sets, the second
step in the programming process is to align the number of repetitions
contained within the set with the overall targeted training goals (Table
13.1). When making this decision, repetition ranges for the entire set are
typically structured based upon the ranges commonly used with traditional
sets (Haff et al., 2008a). For example, if the coach is designing a training
programme that targets hypertrophy, 6–12 repetitions per set are typically
programmed, while <6 repetitions are programmed when targeting maximal
strength or power development (Haff and Haff, 2012).
Once the number of repetitions is determined the third step in the
programming process is to determine which type of cluster set will be
programmed. This decision is made based upon aligning the cluster set with
the mesocycles targeted outcome, such as strength endurance, hypertrophy,
strength, or power outcomes (Figure 13.5).
Suggested training target/goal set type alignments.
When targeting strength/power endurance or hypertrophic training
outcomes, the coach can use rest–pause set structures if fatigue
management is not an issue. Alternatively, they can manage fatigue and
optimise the velocity of movement with the use of standard, ascending, or
descending cluster set training strategies. With each of these strategies there
will be an increase in the overall volume load of training. For example,
standard cluster sets, where training load is held constant and interrepetition or intra-set rest intervals are utilised in conjunction with
structured inter-set rest intervals, can be performed to target the desired
outcome. Conversely, undulating or wave-loaded cluster sets are more
typically utilised during mesocycles that target strength/power or power
development in order to capitalise on the PAPE effects of these cluster set
configurations (Haff et al., 2008a). Fundamentally, the coach should
consider what physiological and performance outcomes are being targeted
and then align a cluster set strategy with those goals.
Once the exercise, the number of repetitions contained within the set,
and the cluster set type are selected, the fourth step in the programming
process is to determine the number of sets and how the set is partitioned
(Figure 13.6).
Cluster sets: set and repetition examples.
For example, if a hypertrophy set of 12 repetitions is planned the coach
could design a cluster set that places rest after each individual repetition
(i.e., 12/1 = total repetitions/cluster repetitions) allowing for a greater
maintenance of velocity and technique across the set. Alternatively, the set
of 12 repetitions could be created as six pairs of two (i.e., 12/2), four
clusters of three repetitions (i.e., 12/3), three clusters of four repetitions
(i.e., 12/4) or two clusters of six repetitions (i.e., 12/6). By choosing the
number of repetitions contained within the cluster the coach can manipulate
the training stimulus and target different outcomes.
After the cluster set type is selected, the coach can then prescribe the
training load that will be utilised within the set. There are two basic
strategies for determining the load used to programme the standard cluster
set, with the first method employing the load that would typically be used
when performing a set of 12 repetitions. For example, if the coach planned
the intensity as 60% of 1RM, this load could be used with a standard cluster
set structure. However, this method of loading the cluster set would not
draw upon one of the main advantages of cluster sets, which is that higher
loads can be performed during the set. The second approach would be to
align the training load to the number of repetitions contained in each cluster,
where clusters containing fewer repetitions would use higher training loads
(Tufano et al., 2017b). For example, standard cluster sets of four repetitions
could be programmed to use 75% of 1RM, while cluster sets of two
repetitions might be programmed with 80% of 1RM. Ultimately there are
infinite ways to load the standard cluster set, but the coach should always
consider the relationship between the relative load and the number of
repetitions contained within the cluster.
When working with undulating, wave, ascending, and descending cluster
sets, different loading strategies need to be implemented. Traditionally the
coach will select a target intensity for the set and then, depending upon the
set structure, craft a loading paradigm (Table 13.3).
Table 13.3 Example loading patterns for cluster sets
Type of
cluster
Sets × Repetitions Intensity (%
1RM)
Clusters contained in
the set
(%/repetition)
Type of
cluster
Sets × Repetitions Intensity (%
1RM)
Clusters contained in
the set
(%/repetition)
Basic
1–5
×
5/1
85%
85/1 85/1 85/1 85/1 85/1
1–5
×
6/2
80%
80/2 80/2 80/2
1–5
×
5/1
80%
75/1 82/1 88/1 80/1 75/1
1–5
×
6/2
80%
77/2 86/2 77/2
1–5
×
5/1
80%
77/1 85/1 77/1 85/1 77/1
1–5
×
6/2
80%
77/2 86/2 77/2
1–5
×
5/1
80%
70/1 75/1 80/1 85/1 90/1
1–5
×
6/2
80%
75/2 80/2 85/2
1–5
×
5/1
80%
90/1 75/1 80/1 75/1 70/1
1–6
×
6/2
80%
85/2 80/2 75/2
Undulating
Wave
Ascending
Descending
Note: 5/1 = 5 total repetitions/cluster repetitions; 6/2 = 6 total repetitions/cluster repetitions.
For example, if the coach were to create an undulating cluster set that
contains five repetitions and wanted the average intensity across the set to
be 80% of 1RM, the repetitions contained in the cluster set would be 75%,
82%, 88%, 80%, and 75% of 1RM (Haff et al., 2003). Ultimately, when
working with wave, ascending, and descending cluster sets, a coach should
define the average load across the set and then align the individual cluster
intensities accordingly.
Once the loads used with the cluster set have been selected the coach can
then determine the amount of inter-repetition or intra-set rest that is
provided within each set (Figure 13.7).
Inter-repetition and intra-set rest interval alignments with training phase.
If strength/power endurance or hypertrophy is the targeted outcome,
shorter inter-repetition or intra-repetition rest between 5 and 15 seconds
should be selected. When shifting the training target toward maximal
strength the inter-repetition or intra-repetition rest interval contained in the
cluster would be lengthened to 15–30 seconds. The longest inter-repetition
or intra-repetition rest interval that would be used is 30–40 seconds.
Additionally, it is important to remember the shorter the inter-repetition or
intra-set rest interval, the greater the focus on endurance, and the longer the
interval, the greater the focus on power/strength development (Figure 13.7).
Additionally, the more repetitions contained within the cluster, the longer
the intra-set rest interval may be required.
Challenges to implementing cluster sets
While cluster sets are useful and beneficial training tools, they do have
practical limitations. The most noted limitation is the increased time needed
to complete exercises which employ the cluster set. For example, three
traditional sets of 12 repetitions are performed with 120 seconds of inter-set
rest, so total time dedicated to rest is 240 seconds. If each set of 12
repetitions is broken into five pairs of two repetitions, each separated by 30
seconds, and the same 120 seconds of inter-set rest is employed, the total
rest associated with three sets is now 690 seconds (Tufano et al., 2016). As
noted by Jukic and Tufano (ahead of press), increasing the rest associated
with a given exercise by this magnitude may not always be feasible from a
practical perspective if an athlete has limited total training time. While
Jukic and Tufano (ahead of press) are not incorrect about the extension of
rest time, it is important to note that not every exercise in a given training
session will utilise cluster sets and the coach can manipulate the interrepetition, intra-set, and inter-set rest intervals to allow for the more
efficient utilisation of the cluster set. One additional strategy that can be
used with team sport athletes is to perform what coach Erin Haff has termed
“partner cluster sets” (personal communication, 2018). With “partner
cluster sets” athletes can be paired based upon strength levels with one
another so that whilst one athlete is resting, another is performing the
repetitions contained within the cluster set (Figure 13.8).
Partner cluster sets.
To lengthen the inter-repetition or intra-set rest interval, the number of
athletes partnered could be increased to three, thus allowing each athlete to
lift in a rotation until the set is completed. Additionally, partnering athletes’
similar but not exact strength levels could also be used to lengthen the rest
interval. One of the additional benefits of the partner cluster set strategy is
that it enhances team dynamics as athletes need to learn how to work
together to complete the programmed sets, especially if loads have to be
altered between clusters such as during undulating, ascending, and
descending sets. Additionally, this strategy provides an important
opportunity for coaching to occur while athletes wait their turn in the lifting
rotation.
Periodisation and cluster sets
The utilisation of the cluster set within a periodised training programme has
not been widely investigated within the scientific literature. When
examining the classic applied coaching literature, cluster sets have been
employed during the specific preparation and pre-competition phase (i.e.,
pre-season) (Roll and Omer, 1987). For example, Roll and Omer (1987)
suggest using standard cluster sets during the strength/power phase of a
resistance-training programme that is associated with the pre-competition
periods within an annual training plan for an American College Football
team. Similarly, Miller (2011b) recommends using cluster sets during the
specific preparation and pre-competition phases of the annual training plan
of weightlifters.
While it is logical to align cluster sets within the specific and precompetition phases, which often contain strength and power-training blocks
of resistance training, various types of cluster set can be aligned with
targeted training outcomes which are associated with various phases of the
annual training plan (Figure 13.9; Haff et al., 2008a, 2008b).
Set alignments with phases of a periodised training plan.
For example, standard, ascending, and descending cluster set
configurations can be used within the preparation period of the annual
training plan, whilst standard, undulating, ascending, or wave-loaded
cluster sets can be utilised during the competition period. Ultimately, the
alignment of the cluster set with the various periods and phases of an annual
training plan should be based upon the resistance-training targets (i.e.,
strength endurance, hypertrophy, strength and power).
Summary
The cluster set is not a new concept, but a classic strategy for modifying the
set structure to alter the training stimulus and to provide the athlete with a
novel training stimulus. The cluster set can be created in numerous ways,
through modifying the loading, recovery, and organisational strategies used
to create the set. Through manipulating the cluster set type and the recovery
duration, the degree of recovery between the repetitions or groups of
repetitions contained in the set can be impacted. Cluster sets can be
employed to target strength endurance, hypertrophy, strength, and power
development. While cluster sets are extremely useful, they should not be
used with every exercise in a training session and should be confined to one
to two main exercises (i.e., squatting, deadlift, weightlifting derivatives,
etc.) per sessions. In team sport situations it may be warranted to create
partner cluster sets where groups of athletes perform repetitions in an
alternating manner in order to allow for a more efficient use of training time
and, more importantly, the development of team dynamics and chemistry.
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Part III
Coaching your athlete
14 Movement screening: a systematic
approach to assessing movement
quality
Louis Howe and Chris Bishop
DOI: 10.4324/9781003044734-18
SECTION 1
Introduction
Movement screening is the process of analysing an athlete’s technical performance
across a movement task. Alongside testing measures of athletic qualities, movement
screening allows strength and conditioning (S&C) coaches to determine an athlete’s
competency for executing fundamental movement patterns during an initial assessment.
Consequently, movement screening supports decision making during the gap analysis –
a process whereby a coach compares the athlete’s current performance levels against
established benchmarks or standards. In this context, movement screening provides
S&C coaches with an appreciation for whether an athlete is prepared to progress (via
increased mass, movement velocity or coordinative challenge) a relevant movement
pattern, to further develop physical skills and capacities that enhance sport
performance. In turn, S&C coaches are able to make better-informed decisions at an
individual level regarding appropriate exercise prescription. This supports S&C
coaches to individualise their approach to athletic development, whilst simultaneously
improving athlete safety in the weight room.
Although movement screening has limited ability to predict injury incidence (Bahr,
2016; Moran et al., 2017), it can be used to identify athletes at greater injury risk
(Hewett et al., 2005; Padua et al., 2015; Hewett, 2016). In this context, athletes who
demonstrate specific movement traits during a movement screen would be identified as
being at greater injury risk. For example, an athlete who performs a landing task with
excessive dynamic knee valgus is at greater risk of developing anterior cruciate
ligament injury (Hewett et al., 2005). This would be defined as a movement fault, a
coordination strategy that does not align with a pre-defined performance criterion for
the task. Although this finding does not guarantee the occurrence of an anterior cruciate
ligament injury (Leppänen et al., 2017), it does suggest the athlete is at greater risk
(Myer et al., 2007), particularly if other risk factors associated with this injury are
present (e.g. sport, gender, previous injury).
Another benefit to formally including a movement screen within a testing battery is
to provide a baseline indication for an athlete’s movement quality prior to initiating an
S&C programme. This will help the S&C coach document improvement following an
intervention – whether through appropriate coaching or training. This will be important
in instances where an athlete lacks competency across several movement patterns
leading to technique being prioritised for a length of time, as may be the case when a
physical capacity deficit (i.e. insufficient ability to access a physical quality such as
strength or mobility) is the cause of the failed movement screen. For example, if an
athlete’s ability to perform full range-of-motion shoulder elevation is poor due to
limited thoracic spine mobility, overhead lifting performance will be compromised
(Kebaetse et al., 1999). A training programme to improve thoracic extension mobility
in some instances will take time to achieve appreciable improvements, resulting in
superior overhead lifting technique. The results from the initial screen will support the
coach in rationalising the importance of a mobility programme to the athlete, which in
turn may enhance the athlete’s motivation to perform the mobility programme
regularly. Furthermore, improvements recorded in the subsequent movement screen
following engagement with the mobility programme will demonstrate to the athlete and
other relevant parties (i.e. technical coach) that the programme resulted in enhanced
movement quality. This process reinforces to the athlete the benefits of S&C training,
supporting future “buy-in”.
The aim of this chapter is to provide the S&C coach with a systematic approach to
performing movement screens based on the needs of the athlete and the coach. Key
considerations for designing and performing movement screens will be discussed to
ensure movement quality is accurately measured. To support the interpretation of the
findings, an investigation process will be presented to establish the primary cause of a
movement fault, helping S&C coaches problem-solve and individualise their approach
to improving movement quality. Finally, in this chapter we present an example for how
movement screening can be performed in the practical setting.
Selecting movements to screen
Specificity for exercise selection is an accepted principle for the transfer of training
(Brearley and Bishop, 2019), yet it is rarely discussed in the context of movement
screening. Earlier, we proposed that a primary objective of movement screening is to
establish an athlete’s competency to perform specific movements, determining their
level of preparedness for loading the pattern. As such, patterns that mimic exercises
that the S&C coach plans to programme should be prioritised when selecting
movements for screening. This ensures each screen establishes what it is supposed to
(i.e. movement quality during exercise) and possesses high construct validity (Thomas
et al., 2005). Movements that do not replicate the primary exercises likely to be
prescribed to develop athletic performance should not be prioritised for screening
unless the intended use is for identifying injury risk. For example, although
performance of the active straight-leg raise requires an athlete to disassociate hip
flexion from spinal motion, its relevance to the performance of a closed-chain hip hinge
pattern used to develop posterior-chain strength is limited when compared to the
Romanian deadlift screen. Although there are similarities between these tasks, the
active straight-leg raise provides no information for how an athlete: (1) maintains
balance during the movement; (2) actively develops spinal stiffness in an upright
posture; (3) coordinates hip and knee flexion while minimising ankle motion during
standing; (4) actively lengthens the hamstring musculature using an eccentric muscle
action; and (5) manipulates the location of load so as to minimise spinal forces. As
screening a single movement can be time consuming (>3 minutes) and various
movement patterns are commonly used in training (e.g. jumping, hopping, squatting,
lunging, hinging, pushing, pulling and rotating), coaches are left with little time to
qualify movement quality during less relevant tasks. Therefore, it is suggested that
practitioners filter their choice of movement screens to ensure findings directly inform
training decisions while guaranteeing a time-efficient approach.
Specificity is especially relevant when screening movements that are performed at
relatively low velocities. In such instances, coaches must recognise that the information
gained during low-velocity movement screens provides only a partial representation for
how activities with similar coordination features occur at high velocities (Frost et al.,
2015a). For example, peak knee abduction angle measured during a bodyweight squat
shows only a non-significant moderate association (r = 0.46) with the same measure
during a double-leg landing (Donohue et al., 2015). Although several reasons may
underpin differences in competency between low- and high-velocity activities, the
demands of the task will be the main cause for discrepancies observed. For many
athletes, bodyweight squatting presents as a mobility challenge, with considerable
demands for hip, knee and ankle motion (Hemmerich et al., 2006). Alternatively,
landings require relatively less mobility at the hip and knee joint, but greater eccentric
strength and rate of force development to rapidly attenuate landing forces (Montgomery
et al., 2012) and preparatory strategies to coordinate the movement prior to ground
contact (Hashemi et al., 2010). As a consequence of the conflicting requirements of
each task, athletes who possess mobility restrictions will likely demonstrate suboptimal squat mechanics but may still be able to demonstrate appropriate landing
technique (Dill et al., 2014). Conversely, athletes with low eccentric strength in the
lower extremity are likely to demonstrate poor landing strategies (Lephart et al., 2002;
de Marche Baldon, 2011), but may still be able to demonstrate a bodyweight squat. As
poor control of the trunk (Zazulak et al., 2007; Dingenen et al., 2014) and lower
extremity (Hewett et al., 2005) in the frontal plane during landings increases the risk for
knee ligament injuries, screening competency during landing tasks and not through
squatting movements becomes even more relevant. This is not to suggest that landing
technique must be screened as part of the initial assessment on the first day of coaching
a novice athlete. Depending on the circumstances, S&C coaches may choose to
organise screening comparable to how training is periodised, so that high-velocity
activities (e.g. jump-landing) are screened once a level of competence has been
achieved in low-velocity movements (e.g. squat).
As previously discussed, movement screening can also be used as a tool to
determine an athlete’s injury risk. For this to be accomplished, movements should be
selected that share mechanical similarities to the mechanism of the injury. For example,
patellofemoral pain syndrome commonly occurs in sports that involve the performance
of a high volume of jump-landings (Weiss and Whatman, 2015). As a consequence,
double-leg landing technique can indicate which individuals are at greater risk of
developing patellofemoral pain syndrome, with sagittal plane knee angle at initial
ground contact (Boling et al., 2019) and peak flexion (Boling et al., 2009), along with
frontal-plane projection angle (Holden et al., 2017), all shown to be modifiable risk
factors. It is therefore suggested that when selecting movement screens S&C coaches
consider the injuries that an athlete may be at greater risk of developing through sport
participation (Howe, Waldron and Read, 2017). For injuries that demonstrate an
incidence and severity rate requiring prevention strategies to be employed, the presence
of modifiable risk factors should be assessed during relevant movement screens if
applicable so as to inform the training process.
An additional consideration for selecting movements to screen is the demands of the
sport and the S&C coaches’ approach to developing relevant physical capacities. For
example, numerous sports place minimal demand for upper-extremity strength qualities
and, consequently, screening upper-limb movement may not be a priority. However,
although some athletes may require minimal training for certain regions of the body,
coaches may decide to screen movement quality in the area due to the methods
employed to improve strength qualities. For instance, a coach seeking to develop
explosive strength for a track and field athlete may choose to use variations of
weightlifting exercises and medicine ball throws. As many of these lifts require athletes
to load the upper extremity overhead, screening the thoracic and cervical spine,
scapulothoracic articulation and glenohumeral joint function would be highly relevant
(Howe and Blagrove, 2015; Howe and Read, 2015). Therefore, the sport and the
approach employed to develop athletic performance by the S&C coach should also
influence decision making when selecting movements to screen.
As time for movement screening is finite, S&C coaches will likely need to be
judicious when selecting movements. This may mean that when deciding on screens to
investigate movement quality, coaches group movements where possible. For example,
as shoulder elevation capability underpins overhead pulling and pushing exercises,
using the bilateral shoulder elevation screen provides an appreciation of an athlete’s
ability to optimally orientate the hand overhead (Howe and Blagrove, 2015). Although
this approach may sacrifice a degree of specificity, it does preserve time and ensure
efficiency is maximised. Other examples for maximising time efficiency during the
screening process would be to complete movement screens during performance testing.
For example, if the S&C coach would like to screen landing mechanics, video analysis
could be used during jump testing to allow coaches to collect multiple forms of
information during one test. Therefore, S&C coaches are encouraged to be creative in
promoting efficiency when designing movement screens. This must be achieved while
assuring a level of reliability to support the interpretation of the results produced
through movement screening (discussed later in the chapter).
Finally, S&C coaches should also consider the constraints imposed during each
movement screen. A common error during movement screening is to have the athlete
perform the movement using a technique or start position that fails to accurately
replicate the demands of an exercise performed in the weight room. An example of this
is having athletes perform an overhead squat screen with the feet facing forward in the
sagittal plane (Cook et al., 2014). This constraint does not align with the technical
model associated with the overhead squat exercise (Yule, 2007), and will capture a high
number of false positives when attempting to determine an individual’s ability to squat
with the feet orientated in a self-selected position (McMillian et al., 2016). This occurs
as squatting with the feet forward prevents the athlete from accessing the same amount
of hip abduction as when some toe-out is allowed. Having the feet facing forwards
maximises the length of the femur in the anterior–posterior direction and biases the
movement to demand high levels of ankle dorsiflexion range of motion to maintain an
upright trunk position (Demers et al., 2018). If toeing out is included in the squat
variation being screened, the femur is orientated more towards the frontal plane
(relative to the feet-forward position) during the descent via hip abduction. The result is
the length of the femur in the anterior–posterior direction decreases, reducing the
demand for the ankle to dorsiflex. Although screening the squat with the feet facing
forward may be useful for identifying individuals with restricted ankle mobility (Rabin
and Kozol, 2017), it is not appropriate for determining an athlete’s ability to squat
(McMillian et al., 2016) or whether the individual has adequate ankle mobility to
perform the squat as an exercise. Therefore, coaches must ensure, when possible, the
movements selected for screening are executed in a similar manner to how the exercise
will be performed during training. This in turn will provide greater accuracy when
determining an athlete’s readiness for loading the movement pattern.
Table 14.1 provides an example menu of movements that may be considered for
screening, along with the equipment required, set-up and instructions that should be
provided to the participant. Nine screens are included that cover the majority of
movement patterns (i.e. jump, hop, squat, hinge, lunge, push and pull) commonly
programmed to support the development of physical qualities. However, for efficiency
purposes, coaches may choose to only screen movements they anticipate will act as the
foundation of the S&C programme. To complement this process, a case study will
demonstrate how coaches may design a movement screen to fit athletes and their needs.
Table 14.1 Example movement screens, including standardisation procedures
Screen
Equipment
Set-up
Instructions
Countermovement
jump
None
Stand upright with
the feet facing
forwards and hip
width apart.
Hands on hips
“Jump as high as possible by dropping to a selfselected depth and then immediately
exploding up. Upon landing, maintain
balance, while keeping the hands on your
hips throughout. Please perform three
repetitions.”
75% forward hop
Tape measure
Tape
Two strips of tape are “Hop forward, landing on the same leg with
placed on the
your big toe just behind the target marker.
ground parallel to
Upon landing, maintain balance for 2
each other at a
seconds. Throughout, keep the hands on the
distance of 75% of
hips. Please perform three repetitions with
maximal hop
the same leg. Once finished, complete three
distance.
repetitions with the other leg.”
Stand upright on one
leg with the
greater toe behind
the first marker
(taped line).
Hands on hips
Squat
None
Stand upright with
“Keeping the feet flat on the ground, squat
the feet shoulder
down as low as you can. Hold the bottom
width apart and
position for 1 second, and then return to the
turned out
start. Please perform three continuous
approximately 11
repetitions at a controlled pace.”
and 1 on a clock
face.
Fingers are
interlinked and the
hands are placed
behind the head
with the elbows
pointing to the
side.
Neutral head position
with the eyes
looking directly
forwards
Screen
Equipment
Set-up
Instructions
Single-leg squat
None
Stand upright on one “Keeping the foot flat on the ground, squat
leg with the foot
down with one leg as low as you can with the
facing forwards.
arms remaining parallel to the ground. Be
The non-stance leg is
sure to keep the non-stance knee flexed
positioned so the
throughout. Hold the bottom position for 1
knee is flexed to
second, and then return to the start. Please
90° with the hip in
perform three continuous repetitions at a
a relatively neutral
controlled pace with the same leg. Once
position.
finished, complete three repetitions with the
Shoulders flexed to
other leg.”
90° with the
elbows extended
(arms parallel to
the ground).
Neutral head position
with the eyes
looking directly
forwards
Forward lunge
None
Lunge distance is
“Step forward so the big toe lands just behind
normalised to leg
the target marker. Upon contact with the
length, calculated
ground, drop into a lunge, stopping just
as the distance
before the back knee contacts the ground.
between the
Please perform three continuous repetitions
anterior superior
at a controlled pace with the same leg. Once
iliac spine of the
finished, complete three repetitions with the
pelvis and the
other leg.”
medial malleolus
of the tibia
(measured in
supine lying).
Tape is placed on the
floor to mark the
lunge distance (leg
length) between
the greater toe of
the trail leg and
the greater toe of
the lead leg.
Stand upright with
the feet hip width
apart and facing
directly forwards.
Hands on hips.
Neutral head position
with the eyes
looking directly
forwards
Screen
Equipment
Set-up
Instructions
Romanian deadlift
Lightweight
Stand upright with
“Maintaining your spinal alignment, lower the
dowel
the feet hip-width
bar down the front of your thighs as far as
approximately
apart and facing
you can whilst only slightly bending the
30 mm in
approximately
knees. Hold the bottom position for 1 second,
diameter
forwards.
and then return to the start. Please perform
Hold the dowel with
three continuous repetitions at a controlled
an overhand grip
pace.”
and the hands just
outside of shoulder
width.
Neutral head position
with the eyes
looking directly
forwards
Bilateral shoulder
elevation
None
Stand upright with
“Standing tall, lift the arms out to the side until
the feet hip-width
they are directly above your head, pointing
apart.
upwards. Keep the elbows extended
Arms are by the side
throughout the movement and at the top of
with the elbows
the movement, the palms should face each
extended and
other. Please perform three continuous
palms facing the
repetitions at a controlled pace.”
side of the thighs.
Neutral head position
with the eyes
looking directly
forward
Screen
Equipment
Set-up
Inverted row
Barbell, power
The barbell is
rack and
positioned in the
approximately
power rack at a
45-cm box
height so that
when the athlete
lays supine on the
floor, only their
fingertips can
touch the bar.
Lying supine, the
athlete places their
heels on the box
with the feet
together and
facing straight up.
The box should be
positioned far
enough from the
bar so that the
chest can contact
the bar with the
body straight.
The athlete grips the
bar with the hands
pronated, just
outside of shoulder
width.
Neutral head position
with the eyes
looking directly
forwards (relative
to the body)
Instructions
“Lift the pelvis so that from the heel to the
head, you are a straight line – this is the start
position. While maintaining the alignment of
your body, pull yourself up to the bar until
you feel the bar touch your chest. Hold this
position for 1 second before descending until
the elbows are fully extended. Please perform
three continuous repetitions at a controlled
pace.”
Screen
Equipment
Set-up
Instructions
Push-up
None
The athlete lies prone “Perform the push-up by pushing the body
on the ground with
away from the ground until your elbows are
the hands directly
fully extended. Hold the top position for 1
under the
second before returning to the start position.
shoulders just
Throughout the movement maintain a
outside of shoulder
straight line from the heels to the head.
width.
Please perform three continuous repetitions
The feet should be
at a controlled pace.”
together with the
knees extended
and the toes
extended so the
balls of the feet
contact the ground.
Neutral head position
with the eyes
looking directly
forwards (relative
to the body)
SECTION 2
Designing performance criteria to aid the assessment of movement
screens
Commercially available movement screens commonly employ a grading system that
results in a composite score from a range of screens being calculated to represent an
individual’s movement quality (Bennett et al., 2017). However, composite scores
provide little value in establishing competency for specific movement patterns (Scibek
et al., 2020) and injury risk (Moran et al., 2017). As an alternative approach, the S&C
coach should direct their attention to the performance of each test. Additionally, as
opposed to scoring movement using a numerical scoring system with levels (i.e. 0–3), it
is suggested a pass–fail criterion is used to report performance during screening along
with a list of movement faults identified. In this case, a pass would signify that the
athlete performed the movement screen using a coordination strategy that satisfied the
associated performance criteria. A fail would indicate that discrepancies existed in the
performance of the movement screen relative to the performance criteria, or that the
athlete experienced pain during the movement. As movement screening is a tool to
determine whether an athlete does or does not possess the technique necessary to
develop physical qualities using that movement, it is suggested there is no need for a
grade beyond pass or fail.
The performance criteria represent the technical features that the athlete is expected
to display during each movement, guiding the S&C coach as to how the movement
should be executed. It is imperative that each component included in the performance
criteria is essential for the optimal performance of the movement. Failure to meet the
movement standards set by the performance criteria should indicate the athlete
demonstrates a strategy that will limit performance or increase injury risk if the
movement were to be loaded. Table 14.2 provides an example performance criterion
with a brief rationale provided for each component.
Table 14.2 Performance criteria for each example screen, including a brief underpinning rationale
Screen
View
Performance
criteria
Rationale
Screen
View
Countermovement
jump (landing
phase)
Anterior
Performance
criteria
1. Feet land
between hip
Rationale
Excessive toe-in or -out during landings increases
anterior cruciate ligament injury risk (Ishida et al.,
2015)
and shoulder
width apart,
facing
forward with
minimal toein or -out
2. Foot contact
is
symmetrical
3. Knees remain
over the toes
Between-limb time discrepancies in ground contact
cause asymmetry in peak vertical ground reaction
forces (GRF) (Britto et al., 2015) and are suggested
as a risk factor for both acute (Hewett et al., 2010)
and overuse injuries (Bressel and Cronin, 2005)
High knee abduction angle during landings increases
anterior cruciate ligament injury risk (Hewett et al.,
2005)
throughout
the landing
4. Pelvis
remains level
Lateral trunk lean increases peak vertical GRF and peak
knee valgus angle for the ipsilateral limb (Hinshaw
et al., 2019)
and no trunk
lean is present
Side
5. Forefoot
touches down
Landing with a plantar flexed ankle reduces peak
vertical GRF (Rowley and Richards, 2015)
prior to heel
contact
Increased knee joint flexion results in reduced peak
vertical GRF during landings (Zhang et al., 2000)
approximately
and is associated with reduced injury risk (Boling et
60–90°
al., 2009; Leppänen et al., 2017)
6. Knee flexes
following
ground
contact
7. The trunk
leans forward
>30°
A forward trunk lean is associated with increased hip
flexion (Blackburn and Padua, 2008) and results in
reduced peak vertical GRF (Blackburn and Padua,
2009)
Screen
View
Performance
criteria
8. Spine remains
in a neutral
Rationale
Neutral spine alignment increases tolerance to
compressive forces (Gunning et al., 2001)
position
75% forward hop
(landing phase)
Anterior
1. Foot lands
facing
Excessive toe-in or out during landings increases
anterior cruciate ligament injury risk (Ishida et al.,
2015)
forwards with
minimal toein or -out
2. The knee
remains over
High knee abduction angle increases anterior cruciate
ligament injury risk (Hewett et al., 2005)
the toes
throughout
the landing
3. Pelvis
remains level
Lateral trunk lean increases peak vertical GRFs and
peak knee valgus angle for the ipsilateral limb
(Hinshaw et al., 2019)
and no trunk
lean is present
Side
Increased knee joint flexion results in reduced peak
vertical GRF during landings (Zhang et al., 2000)
approximately
and is associated with reduced injury risk (Boling et
60–90°
al., 2009; Leppänen et al., 2017)
4. Knee flexes
following
ground
contact
5. The trunk
leans forward
A forward trunk lean is associated with increased hip
flexion (Blackburn and Padua, 2008) resulting in less
loading on the knee joint (Dingenen et al., 2015)
>30°
6. Spine remains
in a neutral
Neutral spine alignment increases tolerance to
compressive forces (Gunning et al., 2001)
position
7. No obvious
trunk rotation
occurs
Poor trunk control during landings is associated with
greater loading at the knee joint during landings
(Critchley et al., 2019)
Screen
View
Squat
Anterior
Performance
criteria
1. No change in
foot position
Rationale
Excessive toe-out increases medial-lateral knee joint
displacement during squatting (Lorenzetti et al.,
2018)
or alignment
2. Knees remain
over the toes
throughout
the descent
Medial knee joint displacement may be associated with
hip adduction and internal rotation (Slater & Hart,
2016), which can be a provocative position for
femoroacetabular impingement (Lamontagne et al.,
2009)
and ascent
3. Pelvis and
shoulders
Lateral trunk lean during squatting may cause
asymmetry in force production
remain level
throughout
Side
4. Hip crease
descends
Represents a minimal standard of range of motion for
the movement
below the top
of the knee
5. Spine remains
in a neutral
Neutral spine alignment increases tolerance to
compressive forces (Gunning et al., 2001) and
reduces shear forces (Potvin et al., 1991)
position
Posterior
6. Pelvis
remains
centred over
the base of
support
Single-leg squat
Anterior
1. No change in
foot position
Lateral hip shift during closed-chain lower-extremity
exercise causes asymmetry in force production
(Lally et al., 2017) and may suggest an avoidance
strategy (Trulsson et al., 2015). In some instances,
this movement presents as an opportunity to improve
squat performance by increasing the leg contribution
of the (relatively) unloaded limb
Excessive toe-in or out during single-leg exercises
increases injury risk to passive structures located
around the knee joint (Sakurai et al., 2020)
or alignment
2. Knees remain
over the toes
throughout
the descent
and ascent
Maintaining this position reduces knee abduction
moments (Herrington et al., 2017). Medial knee
displacement may be associated with hip adduction
and internal rotation (Slater & Hart, 2016), which
can be a provocative position for femoroacetabular
impingement (Lamontagne et al., 2009)
Screen
View
Performance
criteria
3. Pelvis
remains level
Rationale
Ipsilateral lateral trunk lean during single-leg squatting
increases peak knee abduction angles (Nakagawa et
al., 2012)
and no trunk
lean is present
Side
4. Knee flexes to Represents a minimal standard of range of motion for
the movement
≥ 90°
5. Spine remains
in a neutral
Neutral spine alignment increases tolerance to
compressive forces (Gunning et al., 2001) and
reduces shear forces (Potvin et al., 1991)
position
6. No obvious
trunk rotation
Trunk rotation is associated with poor lumbo-pelvic
stabilisation during variations of single-leg squatting
(Perrott et al., 2010)
occurs
Forward lunge
Anterior
1. Both lead and
trail foot face
forwards
throughout
2. Lead knee
remains over
Excessive toe-in or out during single-leg exercises
increases injury risk to passive structures located
around the knee joint (Sakurai et al., 2019). Coaches
should be aware that slight toe-in on the lead leg may
be advantageous for increasing balance secondary to
a greater base of support
Maintaining this position during lunging reduces
loading on passive structures located around the knee
joint (Thijs et al., 2007)
the toes
throughout
3. Pelvis
remains level
Adequate lumbo-pelvic stabilisation is required to
maintain this position (Whatman et al., 2012)
and no trunk
lean is present
Side
4. Lead foot
remains in
full contact
with the
ground
following
initial ground
contact
Heel lifting off the ground increases risk of falling due
to reduced base of support
Screen
View
Performance
criteria
5. Spine remains
in a neutral
Rationale
Neutral spine alignment increases tolerance to
compressive forces (Gunning et al., 2001) and
reduces shear forces (Potvin et al., 1991)
position
6. Knee flexion
for the lead
Represents equal contribution of the trail and lead leg
to producing force
and trail leg is
approximately
90°
Romanian deadlift
Anterior
1. Bar descends
lower than the
Represents a minimal standard of range of motion for
the movement
patella
2. Bar remains
Indicates symmetry in the coordination strategy used
level
throughout
Side
3. Slight knee
flexion occurs
Signifies a hip flexion strategy is dominant in lowering
the load
during the
descent
4. Tibia remains
Minimises ankle dorsiflexion contribution
vertical
throughout
5. Spine remains
in a neutral
Neutral spine alignment increases tolerance to
compressive forces (Gunning et al., 2001) and
reduces shear forces (Potvin et al., 1991)
position
Posterior
6. Pelvis
remains
centred over
the base of
support
Lateral hip shift during closed-chain lower-extremity
exercise causes asymmetry in force production
(Lally et al., 2017)
Screen
View
Bilateral shoulder
elevation
Anterior
Performance
criteria
1. Upper arm
reaches a
Rationale
Represents a minimal standard of range of motion for
the movement
vertical
alignment
relative to the
ground
2. Elbows
remain
Elbow flexion is a compensatory strategy used to
achieve the goal of orientating the hands over the
head (Howe and Blagrove, 2015)
extended
Side
3. Arms remain
in the frontal
Deviations out of the frontal plane represent a
compensatory strategy during the test (Howe and
Blagrove, 2015)
plane
4. Head does not Poor cervical spine alignment negatively impacts
upper-extremity function (Thigpen et al., 2010)
change
position
5. Spine remains
in a neutral
alignment
Posterior
6. No obvious
signs of
Excessive thoracic spine flexion impairs
scapulothoracic function (Crosbie et al., 2010) and
reduces scapular plane abduction strength (Kebaetse
et al., 1999)
Demonstrates optimal synergy between the
scapulothoracic muscles (Ludewig and Reynolds,
2009)
shrugging
Inverted row
Side
1. The chest
touches the
Represents a minimal standard of range of motion for
the movement
bar
2. The scapulas
fully protract
and retract
during the
descent and
ascent,
respectively,
in a controlled
fashion
Full scapular retraction and protraction indicate
adequate muscular control of the trapezius and
rhomboid musculature (Ekstrom et al., 2003)
Screen
View
Performance
criteria
Rationale
3. The scapula is Demonstrates optimal synergy between the
scapulothoracic muscles (Ludewig et al., 2004)
not fully
elevated or
depressed
4. Throughout
the
Demonstrates adequate lumbo-pelvic control during a
pulling movement
movement,
the body
forms a
straight line
from the heel
to the head
5. Spine remains
in a neutral
Neutral spine alignment increases tolerance to
compressive forces (Gunning et al., 2001)
alignment
Push-up
Side
1. Elbows fully
extend at the
Represents a minimal standard of range of motion for
the movement
top of the
ascent
2. The scapulas
fully protract
Full scapular retraction and protraction indicates
adequate muscular control of the serratus anterior
muscle (Ludewig et al., 2004)
and retract
during the
ascent and
descent,
respectively,
in a controlled
fashion
3. The scapula is Demonstrates optimal synergy between the
scapulothoracic muscles (Ludewig et al., 2004)
not fully
elevated or
depressed
Screen
View
Performance
criteria
4. Throughout
the
Rationale
Demonstrates adequate lumbo-pelvic control during a
pushing movement
movement,
the body
forms a
straight line
from the heel
to the head
5. Spine remains
in a neutral
Neutral spine alignment increases tolerance to
compressive forces (Gunning et al., 2001)
alignment
When selecting components of a movement that should be included in a
performance criterion, the S&C coach should account for individual variability in the
coordination of the movement. For example, variance in anthropometric dimensions
will influence the relative contribution of the hip, knee and ankle joints to lowering the
centre of mass during squatting (McKean and Burkett, 2012). Visually, this can be
observed through varying trunk angles relative to the tibia (shin) angle. A common
recommendation for performing a squat movement is to use a technique that maintains
a torso angle that is parallel to the tibia (Bishop and Turner, 2017). However, strict
adherence to this criterion fails to account for the natural variance that exists between
individuals of different statures. Athletes who possess a long torso relative to their
femurs will likely squat with a more vertical trunk angle. Conversely, athletes with a
shorter torso relative to their femurs will likely adopt greater forward lean during the
squat to maintain balance. As a result, S&C coaches may choose to ignore this feature
of the movement and focus on other characteristics of the squat movement that are
required for proficiency in the movement (e.g. maintaining a neutral spine).
Alternatively, if the S&C coach believes this feature of the movement will inform their
practice, movements that demand this characteristic (e.g. overhead or front squat)
should be selected for screening to identify if the athlete has the skill and capacities to
demonstrate this coordination strategy. Importantly, the S&C coach must distinguish
between movement faults that result in diminished performance or increased injury
risk, and variances in performance that do not compromise either.
Performing movement screening
A common argument against the use of movement screening is that formally
performing screens is unnecessary. Instead, observing the way each athlete moves
during training sessions will suffice. Although there is merit in this approach, this
presents several problems that must at least be considered when attempting to reliably
screen an athlete’s movement competency. This section will provide the S&C coach
with important considerations for how to perform a movement screen.
The primary issue with using training sessions as a movement screen would be a
lack of standardisation in the testing procedures (including both screening and
assessments), resulting in greater error due to confounding variables diminishing the
reliability of the data collected. Reliability is defined as the consistency of a test to
provide an outcome measure (Atkinson and Nevill, 1998) and must be established to
support the interpretation of the findings. As all testing procedures contain varying
levels of associated error, the S&C coach must identify whether changes in results have
occurred due to differences in the athlete’s movement competency following training or
represent variability in the outcome measure associated with error (Atkinson and
Nevill, 1998). To improve reliability when performing movement screens, the S&C
coach should ensure the factors presented in Table 14.3 are considered.
Table 14.3 Key considerations to improve reliability when screening movement quality
Factor
Consideration
Testing
equipment
The same testing equipment is used for each testing session and the equipment is set up
appropriately and calibrated, as required
Clothing and
footwear
Athletes should wear similar clothing and footwear between testing sessions. Preferably,
athletes should wear the same footwear they expect to regularly train in and clothing that
allows for unrestricted movement and anatomical landmarks to be observed
Facilities and
flooring
Facilities and flooring should be consistent across testing sessions
Circadian
variation
Time of day and the day relative to the training week should be controlled between test
sessions. This will limit the influence of circadian variation and fluctuations in training load
across the week, respectively
Warm-up
If used, the same warm-up protocol should be performed to prevent variability secondary to
differences in the level of acute preparedness
Instructions and
Athletes should be instructed on how to perform the task using a standardised script that
demonstrations
includes only relevant information. A demonstration should also be provided to ensure the
athlete has a clear understanding for how the task should be performed
Factor
Consideration
Familiarisation
Athletes should be allowed time to practise the screen to ensure changes in results are not
caused by greater familiarity with the task secondary to a learning effect. Sets of three
repetitions should initially be performed by the athlete to allow for them to be familiarised
with the movements. This should be repeated until the athlete reports they are comfortable
with the movement and the coach is confident there is enough consistency between
repetitions to ensure reliable results are recorded. Coaches may need to use this time to
reinforce elements of the instructions
Data collection
method
For each screen, a camera should be set up so that the optical axis of the camera is
perpendicular to the plane of motion being recorded, while ensuring the entire movement is
captured. For screens that require footage in both the sagittal and frontal plane, coaches can
either use two cameras to record footage simultaneously or if only a single camera is
available, the athlete should perform clusters of repetitions at different angles to the camera
to allow for footage to be recorded in various planes
Performing movement screens in real time has been shown to produce reliable
results (Onate et al., 2012). However, investigations establishing the criterion validity
for real-time screening demonstrates low accuracy, with the level of agreement being
shown to be poor between the evaluation of movement competency in real time and
objective measurements recorded using gold-standard methods for measuring
movement (i.e. three-dimensional (3D) motion capture analysis) (Whiteside et al.,
2016). It has been suggested that disparities in scores between real-time and 3D motion
capture are caused by the need for assessors to grade several components of the
performance criteria simultaneously in real time during a single repetition (Whiteside et
al., 2016). As a result, it is recommended that the S&C coach use video analysis when
performing movement screening to improve accuracy. If logistics requires coaches to
screen in real time, it is recommended that, for each repetition, only one component of
the performance criteria be assessed. This will result in the number of components
included in the performance criteria determining how many repetitions to perform for
each screen (Gould et al., 2017). As a result, coaches will avoid the error associated
with screening movement using a performance criterion that includes several
components across only three repetitions in real time.
Identifying the causes of movement faults
Following the performance of a movement screen, S&C coaches must have a process to
interpret the information gathered so as to inform practice. Figure 14.1 illustrates a
model that can be used by S&C coaches to establish the cause(s) of movement fault(s)
that may present during a movement screen. When an athlete performs a movement
screen optimally relative to the performance criteria, the athlete has passed the screen
(stage 1). In this instance, the S&C coach can be confident that the athlete has an
adequate level of skill and capacities to perform the movement. In this context, skill
represents the athlete’s ability to coordinate their body optimally to perform the
movement screen using a strategy that matches each component of the performance
criteria, while capacities signifies the athlete’s access to a certain physical quality (e.g.
strength, mobility, balance, endurance, etc.). As a result of the passed screen, the
movement can be programmed to drive adaptations in athletic qualities.
Model to establish the cause(s) of movement fault(s).
Similar to the medical model used for screening health-related factors (e.g. blood
pressure), when an individual fails a movement screen, further investigation through
additional assessment is required to identify the cause(s) of the movement fault(s). This
requires the S&C coach to adopt a systematic approach to determining the source of the
movement fault (Howe and Cushion, 2017). The investigation process for establishing
the cause of a failed movement screen should be regarded as crucial for developing
movement quality in the pattern screened. Time to train is finite for all athletes and
excessive time spent performing corrective exercises will reduce time available to
develop physical qualities that will result in enhanced sport performance. This is
particularly problematic if S&C coaches apply a scattergun approach to improving
movement quality without further investigation, whereby assumed skill, proprioception,
balance, strength and mobility issues are addressed through mass prescription of
corrective exercises. However, if the cause of the movement fault is identified,
corrective strategies can be employed that are effective and time-efficient.
Stages 2–4 of the investigation process presented in Figure 14.1 are designed to
determine whether the cause of the movement fault is either a skill or capacity issue. To
illustrate the practical application of this concept, consider the following example. Two
athletes perform the squat screen with excessive forward lean that results in a loss of
neutral spine prior to the hip crease descending below the top of the knee joint. Both
athletes are made aware of this movement fault and asked to practise squatting without
making contact with a wall that is behind them one foot length away from their heels.
In this example, the wall acts as a constraint by preventing excessive forward trunk lean
and limiting how far the pelvis can deviate posteriorly. Following a short period of
practice, one athlete is now able to perform the squat so the hip crease descends below
the top of the knee, while preserving a neutral spine. In this instance, the movement
fault was caused by a lack of skill. The second athlete is unable to solve the movement
problem and, as such, falls forward or limits their range of motion to preserve balance
during each attempt. For this athlete, the working hypothesis is the athlete possesses a
capacity issue that is limiting their ability to adapt their coordinative strategy and
further investigation is required. It should be noted that the distinction provided here is
limited, as skills and capacities share an interdependent relationship during the
performance of any movement. However, in the context of movement screening and
developing corrective strategies, this concept serves the S&C coach in establishing the
cause(s) of a movement fault that an athlete demonstrates.
When an athlete fails a movement screen, they have either demonstrated movement
faults in the coordination strategy used or reported pain during the movement. For the
latter, immediate referral to a medical practitioner is required. When movement faults
are demonstrated during the initial screen with no pain present, the S&C coach should
progress the athlete to stage 2 of the investigation process illustrated in Figure 14.1. At
this point, the S&C coach will begin to identify whether a skill issue is the primary
cause of the movement fault. A skill deficit would represent the athlete’s failure to
coordinate the movement using a strategy the S&C coach regards as optimal. Although
coaches could move directly to testing capacities (stage 4 of this process), coaching the
athlete on how to perform the movement is the next logical step. This suggestion is
based on evidence showing that significant improvements in movement quality occur in
short time periods following a basic explanation of the performance criteria (Frost et al.
2015b; Bryson et al., 2018). However, coaching involves more than just providing
athletes with a verbal description of a technical model. Verbal feedback, visual
demonstrations and techniques that stimulate kinaesthetic awareness can all be
strategically applied to facilitate self-correction (Cushion et al., 2017). In the authors’
experience, in many cases this process takes 1–2 minutes for most weight-room-based
movements and presents as a time-efficient strategy for identifying the cause of the
movement fault following the initial screen.
Stage 2 has the additional benefit of helping to establish how “coach-able” an athlete
is, as well as their preferred learning style that will serve as a useful tool for future
interactions with the athlete. Furthermore, coaches can observe what cues resonate for
each athlete in supporting them to appreciate the goal of the task. For athletes
possessing the necessary capacities to perform the movement optimally, stage 2 will
likely result in the athlete passing the original movement screen. In this instance, the
investigation should be ceased and the primary cause of the movement fault has been
identified as a skill deficit. The pattern is ready for loading, although additional time
spent developing movement skill may be required. It is beyond the scope of this chapter
to discuss the science that underpins the variety of approaches available to the S&C
coach to improve movement quality through coaching. The interested reader is referred
to Cushion et al. (2017).
If the movement faults remain, or additional movement faults become apparent as
the athlete compensates for the constraints imposed through coaching, the athlete
should be progressed to stage 3 of the investigation process. This requires the S&C
coach to subtly manipulate the task in order to identify how the athlete can successfully
complete the movement. This serves two primary purposes:
1. Provide clues as to the capacity deficits that may be present, whilst ensuring
efficiency in the investigation process by ruling out capacity deficits and rendering
certain assessments unnecessary.
2. Determine variations in the technique that the athlete can adopt to perform the
movement using a strategy that allows the athlete to pass the screen by performing
the movement as outlined by the performance criteria. This information may also
help the coach identify exercises that the athlete is best suited for.
Table 14.4 provides example task manipulations that can be applied to the commonly
used overhead squat screen. It should be emphasised that stage 3 should only be
employed where the S&C coach sees value in manipulating a task to improve
effectiveness during the investigation process.
Table 14.4 Example task manipulations for an overhead squat screen that can be applied at stage 3 of the
investigation process
Task
manipulation
Rationale
Interpretation
Task
manipulation
Rationale
Interpretation
Elevate the heel
using a 10°
wedge
Reduces the demand for hip
flexion (Charlton et al.,
2017) and ankle dorsiflexion
range of motion (Legg et al.,
2017)
This manipulation informs the strength and conditioning
(S&C) coach what the squat would look like if
additional ankle dorsiflexion range of motion were
available. If the athlete performs the squat with no
movement faults with the addition of the heel wedge,
limited hip flexion or ankle dorsiflexion range of
motion may be the cause of the movement fault. In
this instance, restricted knee flexion range of motion
can be ruled out
Elevate the
forefoot using a
10° wedge
Increases the demands for hip
flexion and ankle
dorsiflexion range of motion
(Macrum et al., 2012)
This manipulation informs the S&C coach whether the
athlete has additional hip flexion they can access
during the squat. If the movement fault increases in
magnitude, limited ankle dorsiflexion range of
motion may be the cause of the movement fault.
Additionally, if hip flexion range of motion increases
during this movement, it is unlikely hip mobility is a
limiting factor as the athlete is able to access greater
range of motion at the joint. If squat depth decreases
significantly, the S&C coach is unable to rule out
limited hip mobility
Counterbalanced
squat
By squatting holding a weight
in front of the body
(approximately 10% of body
mass), the athlete’s centre of
mass can move behind their
base of support. This
decreases the need for ankle
dorsiflexion range of motion,
while allowing the athlete to
display full knee flexion
range of motion (Lynn and
Noffal, 2012)
This manipulation informs the S&C coach whether the
athlete possesses adequate knee and hip flexion range
of motion to perform the squat. If the athlete can fully
flex the knee (hamstrings contact the gastrocnemius)
while maintaining a relatively upright trunk and
neutral spine, the athlete possesses adequate knee and
hip flexion range of motion. In this instance, ankle
dorsiflexion range of motion may be the culprit
Wide-stance squat
Squatting with a wide stance
increases hip abduction
range of motion (Lorenzetti
et al., 2018). This results in a
decreased demand for ankle
dorsiflexion range of motion
(Demers et al., 2018) by
reducing the length of the
femur in an anterior–
posterior direction (Cleather,
2012)
This manipulation informs the S&C coach whether the
athlete can effectively access their hip abduction
range of motion during the squat. If the movement
fault decreases in magnitude, limited ankle
dorsiflexion range of motion is a potential cause.
Alternatively, limited capacity to flex the hip without
additional hip abduction may be a source of the
movement fault
Throughout the investigation process, the S&C coach should form a working
hypothesis as to the primary cause of the movement fault. At stage 4, isolated
assessments will be performed to test specific capacities that challenge the working
hypothesis. The isolated assessments of interest will depend on the movement being
screened and how the athlete performed during the preceding stages. Importantly, the
results from these assessments should provide the S&C coach with objective data that
can be compared to normative data to support the hypothesis that a capacity deficit is
present. For example, during squatting, the hip abducts approximately 30° during the
descent phase (Hemmerich et al., 2006; Swinton et al., 2012). Assessing hip abduction
range of motion using the supine hip abduction test would provide objective data that
can be compared directly to the movement to determine whether a capacity deficit
exists (Howe and Waldron, 2019). Additionally, as long as the S&C coach has
determined the error (e.g. typical error) associated with their testing procedures for each
assessment (Howe and Waldron, 2019), changes in the capacity following training can
be documented and used to determine true change and the effectiveness of a corrective
programme. Table 14.5 provides a brief description of isolated assessments that can be
employed to determine deficits in mobility along with the associated movement screen.
Normative values are relative to the demands of the corresponding movement pattern to
guide the interpretation as part of the investigatory process. However, these values
should be interpreted with strong caution due to differences in anthropometric profiles
and variability in the coordinative strategies used to perform each movement.
Table 14.5 Isolated assessments for mobility testing
Test
Start
position
Movement
Measurement
Normative Relevant
values or movement
pass
screen
criteria
Test
Start
position
Movement
Supine
active
shoulder
flexion
test
The athlete lies The athlete is
supine, with
cued to
the knees
maximally
flexed to 90°
flex the
and the feet
shoulder by
flat against
bringing the
the ground.
thumbs
The athlete
towards the
is cued to
ground above
posteriorly
the head.
rotate the
Elbows must
pelvis and
remain
the head
extended and
should be
the lumbar
positioned so
spine
that the face
maintained in
is looking
a flexed
towards the
position
ceiling. The
shoulder is
flexed to
90°, with the
elbows
extended, the
palms facing
each other,
and thumbs
extended
Measurement
Normative Relevant
values or movement
pass
screen
criteria
Prior to testing, the
smartphone is
zeroed against a
vertical
reference (e.g.
wall). The
smartphone is
placed along the
upper-arm
(triceps brachii),
just below the
medial
epicondyle
Thumb
Bilateral shoulder
touches the
elevation
ground
with the
elbows
extended
Test
Start
position
Movement
Measurement
Normative Relevant
values or movement
pass
screen
criteria
Supine
active
shoulder
rotation
test
(internal
and
external)
The athlete lies
supine on a
plinth, with
the knees
flexed to 90°
and the feet
flat against
the table.
The shoulder
is abducted
to 90°
(upper-arm
rests on the
plinth), with
the elbow
flexed to 90°
and palm
facing
towards the
feet
For
glenohumeral
external
rotation, the
athlete is
cued to bring
the back of
the hand
towards the
floor as far as
possible. For
glenohumeral
internal
rotation, the
athlete is
cued to bring
the palm
towards the
floor as far as
possible
Prior to testing, the External
smartphone is
rotation: >
zeroed against a
90°
vertical
Internal
reference (e.g.
rotation: >
wall). For
40°
external rotation,
the smartphone
is placed on the
anterior surface
of the forearm
(flexor side) just
below the ulnar
styloid process.
For internal
rotation, the
smartphone is
placed on the
posterior surface
of the forearm
(extensor side)
just below the
ulnar styloid
process
Bilateral shoulder
elevation
Test
Start
position
Movement
Measurement
Normative Relevant
values or movement
pass
screen
criteria
Thoracic
spine
extension
test
The athlete
leans with
their back
against a
bare wall.
The feet
should be
positioned
one-foot
length away
from the
wall, with
the knees
slightly
flexed. The
athlete is
cued to
posteriorly
rotate the
pelvis to
flatten the
spine against
the wall. The
head should
be touching
the wall and
the mouth
should be
closed
Maintaining
contact
between the
head and the
wall, the
athlete is
cued to draw
the chin
towards the
chest as far as
possible
The distance
between the
tragus (small
pointed
eminence
covering the
auditory meatus
(ear canal)) and
the wall is
measured to the
nearest 0.5 cm
The corner of
the eye
should be
in line or
below the
auditory
meatus
Bilateral shoulder
elevation.
Romanian deadlift
Test
Start
position
Movement
Lumbar
locked
rotation
test
The athlete
The athlete is
kneels with
cued to rotate
the ankles
as far as
plantar
possible in
flexed. The
the direction
athlete sits
to the side
on their
with the arm
heels, whilst
off the floor,
supporting
whilst
their uppermaintaining a
body mass
neutral
with their
alignment of
elbows and
the cervical
forearms
spine and the
placed on the
supporting
ground so
forearm on
the shoulders
the floor
are flexed to
90°. The
athlete flexes
the
ipsilateral
elbow
maximally
while
bringing the
forearm off
the ground
Measurement
Normative Relevant
values or movement
pass
screen
criteria
Prior to testing, the
smartphone is
zeroed against a
vertical
reference (e.g.
wall). The
smartphone is
placed on the
spine at the level
of C7–T1 at the
level of the
neckline on a
traditional crew
neck t-shirt
> 45°
Bilateral shoulder
elevation
Test
Start
position
Movement
Measurement
Normative Relevant
values or movement
pass
screen
criteria
Supine
active hip
flexion
test
The athlete lies The athlete is
Prior to testing, the > 10°
supine on the
cued to
smartphone is
ground, with
maximally
zeroed against a
both knees
bring the
vertical
extended and
knee of the
reference (e.g.
the arms by
test limb
wall). In the start
the athlete’s
towards the
position, a
side
ipsilateral
horizontal line is
shoulder,
marked on the
while bending
athlete’s thigh, 5
the knee
cm above the
base of the
patella. The
smartphone is
placed proximal
to the marked
line at the point
of maximal hip
flexion
Squat.
Single-leg squat.
Forward lunge (lead
leg).
Countermovement
jump.
75% forward hop
Test
Start
position
Movement
Modified
Thomas
test
The athlete lies While
supine on a
maintaining
plinth so that
hip alignment
when the
for both
hips are
limbs, the
extended, the
athlete is
back of the
instructed to
thighs are
flex the knee
supported by
on the test
the table, but
limb as far as
the knee
possible
does not
contact the
table. Both
hips begin in
a flexed
position,
flattening the
lumbar
spine. The
athlete is
instructed to
lower the
test limb
down into
hip
extension,
with the
knee
extended
until the
back of the
thigh
contacts the
table
Measurement
Normative Relevant
values or movement
pass
screen
criteria
Prior to testing, the < 30°
smartphone is
zeroed against a
vertical
reference (e.g.
wall). The
smartphone is
placed on the
anterior border
of the tibia distal
to the tibial
tuberosity at the
point of maximal
knee flexion
Forward lunge (trail
leg)
Test
Start
position
Movement
Measurement
Normative Relevant
values or movement
pass
screen
criteria
Supine hip
abduction
test
Athlete lies in a The athlete
Prior to testing, the > 40°
supine
maximally
smartphone is
position with
abducts at the
zeroed against a
the legs
hip (moves
vertical
extended.
the knee
reference (e.g.
The test leg
away from
wall). At the
is flexed at
the midline of
point of maximal
the hip and
the pelvis)
hip abduction,
knee to 90°
while the
place the phone
coach
on the medial
stabilises the
surface at
pelvis,
approximately
preventing
mid-thigh
rotation from
occurring
Squat
Active hip
rotation
test
(internal
and
external)
The athlete sits The athlete is
Prior to testing, the External
on the edge
instructed to
smartphone is
rotation: >
of a plinth,
maximally
zeroed against a
40°
with the
rotate the foot
vertical
Internal
knees flexed
away from
reference (e.g.
rotation: >
at 90° and
(hip internal
wall) and a
30°
the lower
rotation) or
horizontal line is
legs freely
towards (hip
made 10 cm
hanging off
external
above the
the table. For
rotation) the
inferior tip of the
both internal
midline of
lateral malleolus.
and external
their body,
For both tests,
rotation, the
while
the smartphone
non-test leg
maintaining a
is placed directly
is placed
90° flexed
proximal to the
over the
position at the
marked line
lateral edge
knee
of the plinth
by abducting
the hip
Squat.
Single-leg squat
Test
Start
position
Movement
Active knee
extension
test
The athlete lies The athlete is
supine on the
cued to
ground, with
maximally
both legs
extend the
extended and
knee, whilst
flat on the
maintaining
ground and
hip alignment
the arms by
the athlete’s
side. The test
limb is then
flexed at the
hip and knee
to 90° and
foot
positioned in
a neutral
alignment
Modified
weightbearing
lunge test
The athlete
The athlete is
Prior to testing, the > 40°
starts in a
instructed to
smartphone is
half-kneeling
reach the
zeroed against a
position,
knee forward
vertical
with the
as far as
reference (e.g.
pelvis facing
possible,
wall). At the
forwards and
while keeping
point of maximal
the trunk
the knee over
ankle
relatively
the foot, the
dorsiflexion just
upright
heel down
prior to heel lift,
(some
against the
the smartphone
forward lean
ground and
should be placed
is allowed).
the pelvis
on the anterior
The test foot
facing
border of the
is positioned
forward
tibia distal to the
half a foot
tibial tuberosity
length ahead
of the knee
of the nontest leg, with
the knee
aligned
directly over
the foot on
the test limb
Practical applications: a case study
Measurement
Prior to testing, the
smartphone is
zeroed against a
vertical
reference (e.g.
wall). At the
point of maximal
knee extension,
the smartphone
is placed on the
anterior border
of the tibia distal
to the tibial
tuberosity
Normative Relevant
values or movement
pass
screen
< 20°
Romanian deadlift
criteria
Squat.
Single-leg squat.
Countermovement
jump.
75% forward hop
This section will now provide a “real-world” example for how the approach discussed
in this chapter can be applied. A 19-year-old international female distance runner, with
no previous experience of S&C training, presented for an initial testing session prior to
commencing a structured S&C programme ahead of the competitive season. Physical
capacity and tissue tolerance testing were performed alongside movement screening
(stage 1 only) in a single testing session, while physiological testing and gait analysis
were completed elsewhere by other members of the interdisciplinary team. Findings
from the movement screen, along with the investigatory process previously discussed in
this chapter, are presented in Table 14.6.
Table 14.6 Movement screen findings and associated investigatory process for an international distance runner
Order Movement
screen
Stage 1
(screen
movement)
Stage 2
(coach)
1
Squat
Pass
2
Forward lunge
Fail: Knee
Athlete passed the
valgus
screen with practice
(patella
following:
inside of
1. Verbal
greater toe)
feedback and
demonstrated
cueing
on the lead
leg following
2. Additional
ground
demonstrations
contact on
both sides
3
Romanian deadlift
Fail: Excessive
knee flexion
and neutral
spine
alignment
are not
maintained
prior to the
bar reaching
the patella
Athlete passed the
screen with practice
following:
1. Verbal
feedback and
cueing
2. Additional
demonstrations
3. Practice with
changes in
environmental
constraints
4
Bilateral shoulder
elevation
Pass
Stage 3
Stage 4
(task
(isolated
manipulation) assessments)
Order Movement
screen
Stage 1
(screen
movement)
Stage 2
(coach)
Stage 3
Stage 4
(task
(isolated
manipulation) assessments)
5
Countermovement
jump (landing
phase)
Pass
6
75% forward hop
(landing phase)
Fail: Knee
Athlete was unable to Single-leg squat:
valgus
pass the screen with
Excessive spine
(patella
practice following:
flexion during
inside of
the descent and
1. Verbal
greater toe)
knee flexion did
feedback and
and limited
not reach 90°.
cueing
knee flexion
Counterbalanced
are
single-leg squat
2. Additional
demonstrated
(5 kg): Athlete
demonstrations
following
was able to
ground
maintain a
3. Video
contact on
neutral spine
feedback on
both sides
alignment and
her
achieve >90°
knee flexion
performance
Modified
weightbearing lunge
test:
Right = 44°
Left = 42°
Movement screening was performed in a fresh state, prior to physical capacity and
tissue tolerance assessment, with the exception of landing movements. In this instance,
double-leg landing competency was screened using the same test for assessment of
explosive strength (i.e. countermovement jump). Similarly, movement quality during
single-leg landings was screened following the performance of a maximal hop test used
to determine between-limbs symmetry in strength. Movement screens were primarily
selected based on their distinct mechanical similarities to the range of exercises that
would likely be prescribed as part of the S&C programme, with the exception of the
bilateral shoulder elevation screen. This movement was chosen to assess competency
for achieving an overhead position in preparation of ballistic (i.e. weightlifting and
medicine ball throws) and supplementary (i.e. trunk and upper-body exercises) training
modalities.
All screens were recorded for video analysis, with a single camera (sampling rate 60
frames per second) set-up using the procedures outlined in Howe et al. (2020). To allow
for accurate comparison against the performance criteria, the athlete was required to
complete clusters of three repetitions at the necessary angles relative to the camera. A
demonstration and standardised instructions (Table 14.1) were provided prior to
familiarisation to ensure the athlete understood the task demands. No warm-up was
used for the squat, forward lunge, Romanian deadlift or bilateral shoulder elevation
screens. A standardised warm-up was performed prior to the countermovement jump
and 75% forward hop screen.
As reported in Table 14.6, the athlete failed three of the six movement screens,
demonstrating movement faults for the forward lunge, Romanian deadlift and 75%
forward hop screen. During the subsequent training session, the athlete was coached
(stage 2) for each movement. This began with allowing the athlete to practise the
movement following additional demonstrations and verbal feedback with an emphasis
on highlighting her specific movement fault(s). For the 75% forward hop screen,
showing the athlete video footage of her performance was also adopted as a coaching
strategy. While the athlete was able to pass the forward lunge screen immediately
following a demonstration and feedback on performance, the Romanian deadlift
required the manipulation of environmental constraints to develop hip–spine
disassociation. This was achieved initially by having the athlete perform the movement
with both tibias directly in front of a training bench to prevent a “knee-dominant”
strategy being accessed, whilst directing the athlete towards a “hip-dominant” pattern.
Following additional practice, a dowel was held along the athlete’s spine to provide
kinaesthetic feedback for spinal alignment and help the athlete maintain a neutral spine
position. This strategy resulted in the athlete passing the Romanian deadlift screen. As
the forward lunge and Romanian deadlift screen were passed following coaching, a
lack of skill was the primary culprit for the failed screens and no further investigation
was required. To reinforce the corrections for these patterns, frontal-plane control of the
lower extremity and hip–spine disassociation were emphasised in the design of the
dynamic warm-up for subsequent S&C sessions.
Following a short period coaching the 75% forward hop screen, significant
improvements in technique were not observed. As the movement faults were not
corrected following practice, a contributing factor may be muscle strength. Weakness in
the leg extensor muscles has been shown to be associated with stiffer landing strategies
(Fisher et al., 2016). Additionally, when less knee flexion is present during landings,
peak knee valgus angles may increase (Pollard et al., 2010). Physical capacity testing
performed during the initial testing session had already revealed low levels of leg
extensor strength during tests such as one repetition maximum (1RM) single-leg leg
press (right = 0.89 kg/body mass; left = 0.85 kg/body mass) and countermovement
jump (22 cm) when compared to normative data (Blagrove, 2015). Therefore, based on
the findings of this investigatory process, it was hypothesised that diminished leg
extensor strength was a primary driver for the movement fault. However, the
contribution of mobility restrictions could not be excluded at this point.
Further investigation was performed with the single-leg squat to establish whether
the athlete had the capacity to access the required knee flexion during a less dynamic
variant (stage 3). As the athlete also demonstrated sub-optimal technique for this
movement, failing to flex the hip, knee and ankle joints whilst maintaining a neutral
spine position, a mobility restriction was considered alongside insufficient strength
levels. To direct the isolated assessments, a counterbalanced single-leg squat was
performed to determine whether hip and knee flexion range of motion was sufficient.
Using approximately 10% of the athlete’s body mass, the athlete was now able to squat
beyond the acceptable depth (i.e. > 90°) whilst maintaining a neutral spine and
controlling knee alignment in the frontal plane. As adequate hip and knee flexion range
of motion was displayed during the counterbalanced single-leg squat, restricted ankle
dorsiflexion range of motion relative to the movement demands was hypothesised.
However, as counterbalanced squats reduce loading at the knee joint (Lynn and Noffal,
2012), muscle weakness could not be ruled out.
Studies have shown that restrictions in ankle dorsiflexion range of motion negatively
affect landing mechanics by reducing sagittal-plane knee joint displacement (Dowling
et al., 2018; Howe et al., 2019) and increasing knee valgus (Malloy et al., 2015). To
challenge the working hypothesis and assess ankle dorsiflexion range of motion, the
modified weight-bearing lunge test was administered as an isolated assessment (Table
14.5). As the athlete demonstrated sufficient ankle dorsiflexion range of motion relative
to the requirements of the movement (e.g. approximately 35°; Horan et al., 2014), ankle
joint hypomobility was not believed to be the primary cause of the failed 75% forward
hop screen.
This process provided the following information:
1. The athlete had sufficient physical capacities to perform the squat, forward lunge,
Romanian deadlift and countermovement jump exercises to an acceptable level.
2. Overhead lifting exercises would not be limited by mobility restrictions.
3. Sufficient mobility was present to perform lower-extremity strength exercises.
4. To improve single-leg landing mechanics, leg extensor strength would need to be
prioritised.
Conclusion
Movement screening should be administered prior to designing a training programme
so as to: (1) identify an athlete’s movement competency during patterns that will be
loaded during the training of the athlete; and (2) determine injury risk. This should be
performed formally, allowing coaches to document the training process with accurate
data, evidencing the success and failures of the programme. In order to support the
accurate collection of data, procedures should be standardised to ensure the methods
used to screen a movement are reliable. This includes the use of a clearly defined and
well-rationalised performance criterion to support the identification of movement
faults.
When movement faults are displayed during a screen, S&C coaches should
systematically investigate the pattern to establish the potential causes of the error. This
chapter presented a four-stage model that supports coaches in recognising the source of
the movement fault, by determining the contribution movement skill and physical
capacities have on the performance of the screen. This process begins by coaching the
athlete on the movement. When an athlete passes the screen following coaching, a lack
of skill is the cause of the fault. However, when movement faults persist, a deficit in a
physical capacity is potentially the driver. In this instance, manipulating the task can
allow the cause to be accurately highlighted, indicating what isolated assessments
should be administered. This process allows S&C coaches to individualise their
corrective strategies in an efficient and effective manner.
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15 Technical demands of strength
training
Timothy J. Suchomel and Paul Comfort
DOI: 10.4324/9781003044734-19
SECTION 1
Exercise technique
The technique used during a given exercise may largely alter the resultant
training stimulus. Aside from an athlete’s anthropometrics and training age,
an exercise may be modified through changes in the range of motion
(ROM) performed or the grip or stance. The following paragraphs will
discuss each of the outlined topics and how they may affect the adaptations
elicited from training.
Range of motion
The ROM performed during an exercise describes the displacement of an
athlete’s body mass and/or the external load being lifted. When prescribing
exercises for athletes, practitioners must focus not only on the ability of the
athlete to perform the exercise, but teaching them to perform each exercise
through a ROM that permits the safe/correct execution of the exercise that
will ultimately elicit the desired training adaptations. There is little debate
that performing an exercise with proper technique is more important than
the weight that may be lifted; however, some athletes may sacrifice the
ROM performed in order to “claim” that they lifted a heavier load. While
this practice may only occur during “max-out” sessions, it should not be
encouraged due to the training implications that may result from chronic
use (e.g., training-to-failure mindset, developing poor technical habits, etc.).
Instead, practitioners should promote the execution of exercises through the
full ROM an athlete is able to perform, considering existing constraints
such as the athlete’s safety, flexibility, anthropometrics, and previous
injuries that may hinder performance. By promoting such a practice, it is
more likely that athletes will develop good training habits and positive
training adaptations (e.g., increased strength and power, decreased injury
risk, and improved/maintained ROM at the involved joints).
Squatting variations (e.g., back squat, front squat, goblet squat, etc.) are
some of the most commonly prescribed exercises within resistance-training
programs. Regardless of the variation, the method in which it is performed
is often the subject of discussion when it comes to the desired ROM
performed by athletes. Based on a practitioner’s coaching philosophy, he or
she may desire that the athletes perform full squats, parallel squats, halfsquats, quarter-squats, or any combination of those previously listed.
Certain squat depths may be considered by some to be “more positionspecific” or “safer”; however, the desired adaptations being sought may
dictate the ROM performed. For example, previous research has indicated
that training with deep squats produced greater increases in quadriceps
muscle cross-sectional area, lower-extremity lean body mass, isometric
knee extension strength, and jump height compared to shallow squats
(Bloomquist et al., 2013). In addition, Hartmann et al. (2012) indicated that
training with deep front and back squats elicited greater vertical jump
adaptations compared to quarter-squats. However, the results of additional
research have indicated that training with quarter-squats produced greater
sprint speed adaptations compared to full squats (Rhea et al., 2016).
Interestingly, Bazyler et al. (2014) indicated that a combination of both full
ROM squats and partial squats may produce greater maximal strength and
rapid force production characteristics than performing only full ROM
squats.
It is important to note that the ROM performed during an exercise may
dictate the activation of specific musculature, the training adaptations
elicited, or the specificity to a sport movement. Previous researchers have
indicated that greater gluteus maximus activation occurs during deeper
squats, but found no differences between partial, parallel, or deep squats in
vastus medialis, vastus lateralis, or biceps femoris activation (Caterisano et
al., 2002). Similarly, Gorsuch et al. (2013) displayed that greater activation
of the rectus femoris and erector spinae muscles was produced during
parallel squats compared to partial squats, but noted no differences in biceps
femoris or lateral gastrocnemius activation between squat variations. The
results of additional research also support these findings for the rectus
femoris (Pereira et al., 2010). Moreover, Bryanton et al. (2012) suggested
that greater relative muscular effort was produced at greater squat depths
for both hip and knee extensors. Table 15.1 summarizes the effects squat
depth has on load, muscle activation, joint loading, and transference to
dynamic movements.
Table 15.1 Potential training effects of partial and deep squat variations
While practitioners may have their opinions on what ROM should be
performed, the decision to increase or decrease the ROM performed may be
justified if the athlete is returning from injury or within specific training
periods where larger or smaller volume loads may be needed to elicit
specific training adaptations. Kotani and Hori (2017) have recommended
that athletes should perform deep squats during the majority of the training
year. However, the authors also mentioned that shallow squats may be
implemented to emphasize power output and rate of force development
(RFD) if the preparation period exceeds 10 weeks. A further description of
this approach will be discussed in Section 2 below.
Grip and stance variation
The grip or stance used during a given exercise may modify the training
stimulus by changing the muscle activation patterns of the muscles being
trained. For example, a wider grip during a bench press may increase the
amount of activation of the sternoclavicular portion of the pectoralis major
while decreasing the activation of the triceps brachii and anterior deltoid
(Barnett et al., 1995; Lehman, 2005); however, such a grip may increase the
risk of shoulder injuries. Similarly, a wider squat stance may increase the
activation of the adductor muscles (McCaw and Melrose, 1999), while a
wider deadlift stance may increase vastus medialis, vastus lateralis, and
tibialis anterior activation (Escamilla et al., 2002). Whether referring to a
bench press, squat, or deadlift variation, different activation patterns may
alter the extent to which the musculature is activated, which may ultimately
affect potential architectural or neuromuscular adaptations. This idea has
been explored in greater detail in other literature, for the bench press (Green
and Comfort, 2007) and pull-up/lateral pull-down (Leslie and Comfort,
2013) exercises.
Another grip consideration that has been previously discussed is the use
of the “hook grip” (Favre and Peterson, 2012). The hook grip is frequently
used during traditional weightlifting movements (e.g. snatch, clean and
jerk) and their derivatives (e.g. clean pull from the floor, hang power
snatch, mid-thigh pull, etc.). The idea behind the hook grip is that by
wrapping additional fingers around the thumb, athletes may prevent their
grip from being a limiting factor when it comes to the weight that can be
lifted for single and multiple repetitions. The findings of recent literature
suggest that one repetition maximum (1RM) power clean, peak velocity,
power, force, and catch height may all be improved by using the hook grip
(Oranchuk et al., 2019).
Mechanical demands of exercises
Force–velocity characteristics
The nature of each exercise partially determines the force–velocity
characteristics that an athlete trains. For example, the back squat serves as a
force-dominant exercise in which the primary goal is to develop muscular
strength. In contrast, the jump squat is a velocity-dominant exercise that
may be used to develop high-velocity characteristics. Cormie et al. (2010a)
showed that relatively weak men may improve their athletic performance
by training with either a strength or ballistic training emphasis. However,
the authors also noted specific adaptations based on the type of training
used (e.g., greater relative back squat strength adaptations with strength
emphasis training and greater sprint speed adaptations with ballistic
emphasis). While it is important to emphasize high-force movements or
high-velocity movements during certain periods of the training year, the use
of combined loading has previously been recommended where athletes train
and develop both the force and velocity sides of their force–velocity profile,
albeit with an emphasis on one aspect (Haff and Nimphius, 2012). Training
in such a manner may ultimately lead to favorable adaptations in RFD and
power (Cormie et al., 2007). A recent review discussed how this method of
training can be implemented using a sequenced progression of weightlifting
derivatives (Suchomel et al., 2017) (Also see Chapter 16.) Assessments
which may indicate whether force production or movement velocity should
be emphasized are explored in Chapters 10 and 11.
Stretch-shortening cycle
The inclusion/exclusion of the stretch-shortening cycle (SSC) within a
movement may impact the training stimulus an athlete receives. The SSC
may allow for the activation of the stretch reflex, optimization of length–
tension muscle factors, optimization of muscle activation, and the
concentric muscle action beginning at a higher force output (Komi, 1986,
2000; Aagaard et al., 2000; Cormie et al., 2010b). By using the SSC, an
athlete may produce greater magnitudes and rates of force production,
potentially allowing for heavier loads to be lifted and a given load being
lifted at a higher velocity. In contrast, movements that exclude the SSC may
require unique neuromuscular demands. For example, an exercise
performed using a static start position may require a greater RFD compared
to a movement that includes the SSC because an athlete must overcome the
inertia of the training load from a dead-stop position compared to having
developed a given magnitude of force previously. Such observations have
been reported for weightlifting derivatives (Comfort et al., 2011a, 2011b).
The inclusion/exclusion of the SSC may place varying demands on athletes
(Meechan et al., 2020a, 2020b), with an increased eccentric demand when
utilizing the SSC, due to the braking phase that is required and thus,
practitioners should consider each athlete’s sport/event when programming
exercises to allow for maximum transfer of training.
Load placement
The placement of load during different exercise variations (e.g., front squat
vs. back squat) may modify the activation of specific musculature. One
study indicated that the front squat produced greater vastus lateralis
activation during the ascending phase and entire movement, while the back
squat produced greater semitendinosus activation during the ascending
phase (Yavuz et al., 2015). In contrast, two other studies reported no
differences in muscle activation between the front squat and back squat
(Gullett et al., 2009; Yavuz et al., 2015; Contreras et al., 2016a). Additional
research demonstrated that greater peak force, velocity, and power were
achieved using a hexagonal bar deadlift compared to a traditional deadlift
(Swinton et al., 2011).
While the previous example includes exercises that are typically used for
strength development, similar results have been shown with ballistic
jumping movements. The acute kinetic and kinematic differences between
the jump squat and hexagonal bar jump indicate that greater force, RFD,
and jump heights are achieved during the hexagonal bar jump, across
several different loads (Swinton et al., 2012). In both studies, Swinton et al.
(2011, 2012) noted that the differences displayed may have been due to
more favorable moment arms based on the load being closer to the lifter’s
center of mass, ultimately allowing for more efficient vertical force
production. A more recent study expanded upon previous literature and
compared both the jump squat and hexagonal bar jump with the jump shrug
exercise (Suchomel et al., 2019). Suchomel et al. (2019) supported the
findings that the hexagonal bar jump produced a greater training stimulus
compared to the jump squat, but also concluded that the jump shrug
produced superior kinetic magnitudes compared to the jump squat as well.
Furthermore, although no differences existed between the hexagonal bar
jump and jump shrug, it was concluded that the exercises may best serve
the athlete as strength-speed (moderate-high-load power) and speedstrength (low-moderate-load power) movements, respectively.
Force production vectors
Muscular strength has been defined as the ability to produce force against
an external resistance; however, when it comes to exercise selection, the
direction in which the force is produced may alter an athlete’s training
outcomes. Previous research has examined the effects of training with
exercises that emphasize more vertical force vectors compared to horizontal
(Contreras et al., 2016b) or unilateral–multidirectional (Gonzalo-Skok et
al., 2017). Contreras et al. (2016b) indicated that adolescent rugby and
rowing athletes who trained with either the front squat or barbell hip thrust
for 6 weeks demonstrated greater improvements in the vertical jump and
horizontal jump and 10- and 20-m sprint times, respectively. Similarly,
Gonzalo-Skok et al. (2017) indicated that amateur/semi-professional teamsport athletes who trained with squats produced greater improvements in
unilateral and bilateral vertical jumps and 25-m sprints compared to those
who trained with unilateral–multidirectional versapulley. In addition, those
who trained using the versapulley demonstrated greater improvements in
lateral and horizontal jumps and change-of-direction tasks. It should be
noted, however, that the results of Jarvis et al. (2019) contradict the
previous findings as the authors concluded that training with barbell hip
thrusts did not enhance 10-, 20-, 30-, or 40-m sprint times. Similar findings
were displayed by Fitzpatrick et al. (2019), who showed that despite
improvements in 3RM hip thrust, there were no differences in the
magnitude of improvement between vertical and horizontal jumping. The
authors of the latter study suggested that the force-vector theory may be
flawed based on mechanical inconsistencies. Instead, the authors suggested
using dynamic correspondence as the method of exercise selection. Thus, it
is important that practitioners understand the orientation of the athlete when
they are generating force (Figure 15.1). Considering the above results,
practitioners may also note that the application of force during various
exercises may produce specific adaptations. DeWeese et al. (2016)
discussed this idea regarding resistance training practices for developing
sprint speed.
Ground reaction forces (orange arrow) and local coordinate frames (blue
arrows) during a sprint acceleration.
Ballistic and non-ballistic exercises
The nature of the exercise(s) performed may result in a different training
stimulus experienced by the athlete based on the intent of the movement. As
noted in Chapter 2, this may include modifications in the force–velocity
characteristics of the exercise. The results of previous work by Lake et al.
(2012) and Suchomel et al. (2018), as well as Newton et al. (1996), have
highlighted the differences between lower- and upper-body exercises
performed in a ballistic manner (i.e., acceleration throughout the entire
movement) and exercises performed quickly (i.e., intentionally fast with a
negative acceleration at the end of the movement), respectively. Taken
together, the results of these studies indicate that exercises performed in a
ballistic manner produced greater force, velocity, power, and muscle
activation compared to the same exercises performed quickly.
Practitioners may choose from a variety of ballistic exercises that may
provide an effective training stimulus. Regarding the development of lowerbody explosive strength, the exercises that first come to mind may be the
weightlifting movements and their derivatives due to their ability to
improve force–velocity characteristics to a greater extent compared to other
training methods (Tricoli et al., 2005; Channell and Barfield, 2008;
Arabatzi and Kellis, 2012; Otto III et al., 2012; Chaouachi et al., 2014;Teo
et al., 2016). This is likely due to movement specificity, but also the ability
to accelerate a moderate-heavy load in a jumping movement with ballistic
intent. Greater detail on how practitioners can use weightlifting movements
to enhance sport performance will be covered in Chapter 16. While
weightlifting movements provide an effective ballistic training stimulus, it
should be noted that exercises like the jump squat (Cormie et al., 2010a),
hexagonal bar jump (Swinton et al., 2012; Suchomel et al., 2019), kettlebell
swing (Lake and Lauder, 2012), and ballistic squat can also provide an
effective training stimulus for the improvement of lower-body explosive
strength.
Practitioners may be more limited with their exercise selection regarding
ballistic upper-body exercises. Typical upper-body ballistic exercises may
include the bench press throw, plyometric push-up, and medicine ball
throw. Newton et al. (1996) indicated that a ballistic bench press throw may
produce greater force, power, and muscle activation compared to a bench
press performed quickly. The extent of these differences can be explained
by the velocity of the movement throughout its completion. The results of
the previous study indicated that the ballistic bench press throw was
accelerated throughout the entire movement whereas the traditional bench
press resulted in deceleration at the end of the movement (~45% of the
ROM). Taking these results into account, the traditional bench press may
serve as more of a foundational exercise to develop strength, while the
bench press throw may be used to develop RFD and power characteristics
(Soriano et al., 2017). Similarly, Vossen et al. (2000) indicated that
plyometric push-ups result in greater improvements in strength and power
compared to traditional push-ups.
The ability of ballistic exercises to improve a strength/power training
stimulus is well documented. An additional benefit of ballistic exercises
may be their ability to be used as a potentiation stimulus, as noted by
Maloney et al. (2014). Previous researchers indicated that ballistic
concentric-only half-squats produced a larger and faster potentiation effect
compared to those performed in a non-ballistic manner (Suchomel et al.,
2016c, 2016d). This may be due to the ability of ballistic exercises to recruit
high-threshold motor units (van Cutsem et al., 1998), which display greater
potentiation compared to smaller, lower-threshold motor units (Hamada et
al., 2000).
Rest intervals
Inter-set rest intervals
It has previously been suggested that rest intervals as short as 30 seconds
(Sheppard and Triplett, 2016) or 1 minute (Kraemer et al., 2002) may be
used to stimulate adaptations in muscle hypertrophy. While a greater
metabolic demand may be present following high-volume exercise sets
(Gorostiaga et al., 2010, 2012), an athlete’s ability to recover during a short
rest interval is limited and thus, their capacity to tolerate the same loads or
heavier loads becomes diminished as the number of sets increases (Buresh
et al., 2009; de Salles et al., 2009). This is likely due to decreased adenosine
triphosphate (ATP), phosphocreatine (PCr), and glycogen concentrations as
well as increases in hydrogen concentrations due to repetitive high-volume
sets (Gorostiaga et al., 2010, 2012).
Despite previous recommendations, additional research findings indicate
that longer rest intervals (1.5–3 minutes) may produce superior muscle
hypertrophy and strength adaptations compared to shorter inter-set rest
intervals (0.5–1 minute) (Robinson et al., 1995; Schoenfeld et al., 2016;
Longo et al., 2020). This may be due to several factors (e.g., neural,
metabolic, etc.); however, one must consider not only the quantity of work,
but the quality of work. For example, researchers indicated that subjects
were unable to complete four sets of ten repetitions during the back squat
with 70% 1RM and 2 minutes of inter-set rest (Oliver et al., 2016). In
response to the failed sets, the authors noted that they decreased the load
performed within the remaining sets, which likely decreased the overload
placed on the athlete. Longer inter-set rest periods may allow for athletes to
replenish their ATP stores and lessen the metabolic fatigue experienced to a
greater extent prior to a subsequent set compared to shorter rest periods.
Ultimately, this may lead to a higher quality and volume of work performed
through the continued use of the prescribed loads, and possible increased
loads, during all sets, potentially leading to greater physiological
adaptations (e.g., work capacity and muscle cross-sectional area) (Longo et
al., 2020).
Collectively, it appears that while shorter rest intervals have the potential
to produce a hypertrophic response, peak adaptations in trained individuals
may be limited due to the loads/volume that may be maintained over
multiple exercise sets. Moreover, if the ultimate goal is to increase the
muscular power of the athlete, training with shorter rest intervals may result
in an endurance effect, which may interfere with long-term hypertrophy
adaptations (Baar, 2006; Hawley, 2009). It should be noted that if
practitioners are concerned with the increase in the overall training time
associated with longer inter-set rest intervals, they may consider short rest
intervals within a set to split up and maintain the work performed. Such an
approach to training, termed cluster set training (Haff et al., 2008), will be
briefly discussed below and covered in greater detail in Chapter 13.
Much of the existing evidence suggests that longer rest intervals may
produce superior adaptations in muscular strength and power. Robinson et
al. (1995) indicated that longer rest intervals (1.5–3.0 minutes) produced
greater strength and power adaptations during a high-volume program.
Additional researchers have indicated that longer rest intervals (2.5–5.0
minutes) resulted in a greater volume of work performed during a workout
(Willardson and Burkett, 2005, 2008), greater ability to train with heavier
loads (Willardson and Burkett, 2006), and greater strength increases
(Robinson et al., 1995; Pincivero et al., 1997; de Salles et al., 2010)
compared to shorter rest intervals (0.5–2.0 minutes). While another study
indicated that no statistical differences in strength gains were found
between 2- and 4-minute rest intervals (Willardson and Burkett, 2008),
those who trained using longer rest intervals produced a larger practical
effect compared to those who trained with shorter rest intervals (i.e.,
Cohen’s d = 2.96, very large vs. d = 1.96, large) (Hopkins, 2014). The
discussed research is in line with previous rest interval recommendations
for improving muscular strength and power (i.e., 2–5 minutes) (Kraemer et
al., 2002; de Salles et al., 2009; Sheppard and Triplett, 2016). It should be
noted that the range in rest interval length may exist due to the training age
(Willardson and Burkett, 2008), fiber-type composition of the athletes, and
the loads implemented in training. Rest interval recommendations are
summarized in Table 15.2.
Table 15.2 Rest interval length to achieve specific training goals
Training goal
Rest interval length
Hypertrophy
1.5–3 minutes
Strength
2–5 minutes
Power
2–5 minutes
Note: Rest interval length may vary based on the type of exercise, load, repetition scheme, and
training status of the athlete.
Intra-set/inter-repetition rest intervals
A growing body of literature has been published regarding inter-repetition
rest within a set of exercise. Specifically, researchers have examined the
effect that cluster sets (Haff et al., 2008) have on kinetic, kinematic, and
technique characteristics during various repetition schemes. A cluster set
may be defined as a traditional exercise set that is split into smaller sets of
repetitions (i.e., clusters) that are separated by rest intervals. One of the first
studies examining cluster sets investigated the effect of various set
configurations (i.e., traditional, undulating, and cluster) on clean pull
performance (Haff et al., 2003). The results indicated that a cluster set
configuration may result in greater barbell velocity and displacement and
power-generating capacity across an entire set. A similar series of studies
examined the effect of rest interval length between repetitions within
several sets on various power clean performance variables (Hardee et al.,
2012a, 2012b, 2013). Collectively, the results indicated that cluster set
configurations using 20–40 seconds of rest between repetitions allowed
subjects to maintain power output and technique and lower their perceived
exertion.
Researchers have also examined the effect of cluster set configurations
on higher repetition sets that focus on muscle hypertrophy. In a series of
studies, researchers reported that high repetition sets with inter-repetition
rest resulted in greater increases in strength and power, while producing
similar increases in lean body mass (Oliver et al., 2013), greater total
volume load and power, similar anabolic hormonal response, decreased
metabolic stress (Oliver et al., 2015), and maintenance of force, velocity,
and power (Oliver et al., 2016) compared to traditional sets. It is important
that practitioners note the amount of total training time required if certain
rest intervals are implemented within cluster set configurations. For
example, researchers noted that performing six two-repetition clusters for a
set of 12 total repetitions may take longer than performing three fourrepetition clusters (Tufano et al., 2016). Smaller clusters require a longer
training time due to the increased amount of rest taken within a set. From a
practical standpoint, using antagonistic supersets (e.g., bench press and
bent-over row) may be an efficient method of performing cluster sets,
where the second exercises of the superset are performed during the rest
period for the previous exercise. It should be noted that a paucity of
research exists on antagonistic supersets. Considering that some sport
governing bodies set strict guidelines on the amount of time for team
activities, it is important for practitioners interested in using cluster sets to
choose cluster set configurations that are both time-efficient and effective at
managing fatigue. For a more thorough discussion on the theoretical and
practical applications of cluster sets, readers are directed to Chapter 13.
Cluster set rest interval recommendations are summarized in Table 15.3.
Table 15.3 Cluster set rest interval length to achieve specific training goals
Training goal
Rest interval length
Hypertrophy
5–15 seconds
Strength
20–25 seconds
Power
30–40 seconds
Adapted from Tufano et al. (2017).
Potentiation complex rest intervals
While the previously discussed rest intervals may be specific to traditional
resistance-training exercises, unique rest intervals may exist when
implementing potentiation complexes. A number of factors may affect the
magnitude of potentiation expressed (Tillin and Bishop, 2009; Suchomel et
al., 2016a). However, a portion of the existing potentiation literature has
focused on examining the effect that various rest intervals have on the
magnitude of potentiation expressed. Following a potentiating stimulus,
both a state of fatigue and potentiation exist (Rassier and Macintosh, 2000;
Sale, 2002; Fowles and Green, 2003; Hodgson et al., 2005). The interplay
between fatigue and potentiation may be acutely modeled on the fitness–
fatigue paradigm (Zatsiorsky, 1995), where the subsequent performance is
the result of the interaction between fatigue and the fitness after-effects that
are the result of an exercise stimulus. While meta-analyses indicated that
rest intervals ranging between 3–7 minutes, 7–10 minutes (Wilson et al.,
2013), and 8–12 minutes (Gouvêa et al., 2013) produced positive moderate
practical effects, additional literature indicated that the type, intensity, and
duration of the exercise may determine whether fatigue or potentiation is
dominant over the other (Masiulis et al., 2007). Thus, it should come as no
surprise that certain protocols may produce positive moderate practical
effects as early as 2 minutes post-stimulus (Suchomel et al., 2016c) or as
late as 15 or 20 minutes post-stimulus (Gilbert and Lees, 2005). Therefore,
practitioners should consider that each individual potentiation complex
possesses unique characteristics and may therefore have its own “optimal”
rest interval.
Another factor that may affect the rest interval during various
potentiation complexes is the relative strength of the individuals completing
the protocol. The results of previous literature have indicated that strong
relationships exist between an individual’s relative strength and the
magnitude of potentiation expressed (Seitz et al., 2014; Suchomel et al.,
2016b, 2016d). This idea is supported by the notion that stronger
individuals may be able to tolerate a more fatiguing protocol given their
frequent exposure to high-intensity loading during training (Stone et al.,
2008). Moreover, researchers have noted that stronger individuals potentiate
earlier and to a greater extent compared to weaker individuals (Jo et al.,
2010; Seitz et al., 2014; Suchomel et al., 2016d). Thus, when designing
potentiation complexes for athletes, practitioners should ensure that they
take the athlete’s relative strength into account. It should be noted that
researchers have recently attempted to distinguish the differences between
post-activation potentiation (PAP) and post-activation performance
enhancement (PAPE) (Blazevich and Babault, 2019); however, further
research is needed to determine if these characteristics are truly distinct
from one another.
SECTION 2
Practical applications
Modifications for appropriate exercise performance
Appropriate modifications/alternatives may need to be made in order for an
athlete to safely perform a specific exercise or receive a given training
stimulus. Whether it may be inexperience with an exercise or a lack of
quality coaching, some athletes have difficulty performing certain exercises.
Thus, it is important to provide athletes with consistent coaching
modifications to help them learn and/or improve their technique in order to
perform exercises correctly.
Previous recommendations were made to maximize leg muscle
activation and minimize the risk of injury during the back squat (Comfort et
al., 2018). Briefly, an athlete’s feet should be wider than shoulder-width
apart with a natural foot position (Ninos et al., 1997; McCaw and Melrose,
1999), unrestricted movement of the knees while the heels maintain contact
with the floor (Fry et al., 2003), a forward or upward gaze (Donnelly et al.,
2006), and full ROM (115–125° of knee flexion) (Ninos et al., 1997;
Caterisano et al., 2002), as long as the athlete is able to maintain a lordotic
curve/neutral spine. Some athletes may have difficulty reaching the desired
squat depth due to several potential issues (e.g., inexperience, stance, lack
of flexibility, balance, etc.). Some common methods to implement that may
help athletes achieve the desired squat depth may be to modify their stance
width and/or rotating their toes out (i.e., hip external rotation). These
modifications will open up the hip joints and allow for greater displacement
of the athlete’s body. While the above provides one example, additional
technique recommendations have been made for the bench press (Green and
Comfort, 2007) and pull-up/lateral pull-down (Leslie and Comfort, 2013)
exercises.
Footwear
While some athletes may be able to effectively squat to the desired depth by
adjusting their stance width or turning their toes out, a pre-existing
anatomical limitation or lack of flexibility within the ankle may still prevent
an athlete from performing a good squat. An additional consideration may
be to slightly elevate the heels of athletes in order to lessen the effect that
this limitation has on their squat performance. This may be accomplished
by placing small weights under an athlete’s heels or by purchasing
weightlifting shoes. The results of previous research have indicated that
weightlifting shoes may allow for a greater squat depth, an upright torso,
and greater stability to be achieved (Hughes and Prescott, 2015; Legg et al.,
2017). Further work has suggested that weightlifting shoes may reduce the
forward trunk lean of individuals, reducing potential shear stress in the
spine, and also increase knee extensor muscle activation compared to
running shoes (Sato et al., 2012). While the addition of weightlifting shoes
will not inherently fix poor squat technique, the resulting acute changes in
technique may lead to chronic improvements in strength and potential
reductions in injuries.
Weightlifting movements
The weightlifting movements (i.e., snatch and clean and jerk) and their
derivatives are popular exercises within resistance-training programs.
However, they are often described as technically complex movements that
are difficult to teach and for athletes to learn. Practitioners may find that
some of their athletes may have difficulty learning an aspect of a full
weightlifting movement (e.g., performing the first pull to the knee,
transitioning to the second pull starting position, properly executing the
catch phase, etc.). While this may deter some practitioners from prescribing
weightlifting movements within their athletes’ training programs, it should
be noted that a number of derivatives exist that serve as effective substitutes
(Suchomel et al., 2017). Scenarios that a practitioner may face when it
comes to choosing an alternative weightlifting movement are displayed in
Figures 15.2 and 15.3.
Scenario requiring weightlifting alternatives for the snatch: (a) range of
motion must be reduced and the bar raised for the start of the lift; (b) if
planning to use a catching variation in subsequent phases a catching variation
at 80–95% 1RM may be advantageous to reinforce technique; (c) if the
athlete cannot catch (e.g. due to injury or limited range of motion) and/or
higher loads (≥100% 1RM power snatch) are desired pulling derivatives may
be advantageous.
Scenario requiring weightlifting alternatives for the hang power clean.
Unilateral training alternatives
Although the back squat exercise is a popular choice for lower-extremity
strength development, it is not without its limitations. As mentioned above,
it is possible that the back squat may result in a greater forward lean
compared to the front squat. Moreover, this may result in greater shear
forces in the spine experienced by athletes. While proper technique
modifications with the potential assistance of weightlifting shoes may
mediate these issues, practitioners should also note that unilateral exercises,
such as the rear-foot elevated split squat, may serve as effective exercise
alternatives. While some research findings have indicated that unilateral
training results in similar improvements in strength and power adaptations
(McCurdy et al., 2005) as well as sprint speed and agility (Speirs et al.,
2016), additional research has shown similar improvements in sprint
performance between unilateral and bilateral training, but greater
improvements in change-of-direction performance following bilateral
training (Appleby et al., 2020). Further research findings indicate that a
modified split squat resulted in greater gluteus medius, hamstring, and
quadriceps activation compared to a bilateral squat (McCurdy et al., 2010).
These authors also noted that the modified split squat also maintained a
more upright torso, which may potentially decrease shear force stress in an
athlete’s lower back. This notion is supported by large effect size
differences in left and right erector spinae activation between the rear-foot
elevated split squat and back squat exercise (Bellon et al., 2013).
Collectively, the evidence indicates that unilateral exercises may be suitable
alternatives for practitioners to prescribe (Appleby et al., 2019), especially
if an athlete is hampered by lower-back pain. However, it should be noted
that unilateral exercises may be best implemented as assistance exercises to
bilateral movements (Ramirez-Campillo et al., 2018). This conclusion is
based on the physiological stimulus that bilateral exercises can provide
(Appleby et al., 2020), but also the decreased stability that is characteristic
of unilateral exercises.
Cueing and feedback
Sport and strength and conditioning coaches traditionally have their own
methods of cueing and providing feedback to athletes. While this is done to
get athletes to perform an exercise or task in a certain manner, practitioners
should note that how they provide cues and feedback may have a profound
effect on the training stimulus that athletes receive.
Cueing
Previous work by Wulf (2007) indicates that cues and feedback that are
external (i.e., athlete focuses on movement effect) are much more effective
than those that are internal (i.e., athlete focuses on his or her body
movements) when it comes to how motor skills are performed, learned, and
retained. In a recent review, the authors discussed instructions and cues for
improving sprint performance echoed these sentiments, suggesting that
cueing should provide an external focus for the athlete (Benz et al., 2016).
The authors suggested that coaches should consider providing external
and/or neutral cues at 100% frequency while keeping the quantity of
instructions low. A similar strategy may be applied when cueing athletes in
the weight room. For example, if an athlete is performing an overhead press
and the training emphasis is speed-strength, an appropriate external cue
may be: “Make the bar rattle at the top,” compared to an internal cue of:
“Contract your arms faster to push the weight.” From the athlete’s
perspective, the external cue gives them the goal based on a sound that
would indicate that they moved the weight quickly. As athletes become
more experienced, smaller cueing phrases may be used. At this point, an
athlete and their coach understand what a specific cue means for them
compared to another athlete. A common cue used in the weight room that
can be applied to many scenarios is: “Stay tight!” As previously mentioned,
this cue may be sufficient for a more experienced athlete; however, it may
also mean something different to two different athletes. It is recommended
that practitioners apply an external focus strategy when it comes to cueing
exercises, keeping in mind that the amount of information provided should
be concise and specific to each athlete. Coaching instruction and cueing are
discussed further in Chapter 20.
Feedback
Like coaching cues, research findings support the use of providing external
feedback to athletes as opposed to internal feedback. Coaches can provide
feedback in a variety of ways, including audio (e.g., verbal discussions),
visual (e.g., video analysis and/or demonstrations), and quantitative (e.g.,
data display). Previous research has demonstrated that augmented feedback
(included coaching and two-dimensional video analysis) resulted in greater
kinetic and kinematic adaptations during the power snatch exercise
compared to a control group (Winchester et al., 2009). While this method
was effective, another study examined the use of the method of
amplification of error (MAE) and how it affected snatch performance
compared to traditional coaching feedback (Milanese et al., 2017). Briefly,
MAE allows athletes to learn to correct their movements by understanding
how to perform the movement incorrectly. The authors indicated that the
MAE group produced greater kinematic improvements of snatch technique
compared to direct instruction only. Finally, a practical example of
quantitative feedback may be through the use of velocity-based training
(Mann et al., 2015). In order to achieve a specific velocity during training,
the athlete may need to be provided with immediate velocity feedback.
Using current technologies, an athlete may see the velocity they produced
and adjust the weight accordingly in order to meet the goal of that training
session.
The amount of feedback given to an athlete may be based on their
training age. However, practitioners should be cautious as to how much
feedback is provided at any given time. Athletes may not be able to receive
multiple pieces of information and perform an exercise effectively,
especially if feedback is provided after every repetition. In order to
effectively provide feedback to an athlete, practitioners should choose one
point of emphasis that an athlete can work on during subsequent training
sets. Practitioners should focus on the most important aspect that is
hindering appropriate exercise performance before fine-tuning technique
with smaller corrections. This is especially true if an athlete is putting
themselves at risk for injury.
Range-of-motion specificity example
While practitioners may have their opinions on what ROM should be
performed (full or partial), the decision to increase or decrease the ROM
may be justified if the athlete is returning from injury or training within
specific training periods when larger or smaller volume loads may be
needed to elicit specific training adaptations. The most obvious instance
would include an athlete’s return from an injury. In this situation,
practitioners may not be as focused on improvements that will transfer to
the athlete’s sport/event, but instead may be focused on having the athlete
regain the competency of an exercise using a reduced ROM. Some of this
training may be dictated by the sports medicine staff; however, strength and
conditioning practitioners should be aware and involved in some capacity
as well. Ultimately, once an athlete again achieves the desired ROM during
a given exercise, strength and conditioning practitioners may take over and
transition the athlete into a return to fitness phase.
While the above scenario certainly occurs, it should be noted that it may
be practical to reduce the ROM of a given exercise during certain times of
the training year in order to maintain certain abilities or reach peak
adaptations. For example, it may be preferable during certain times of year
to perform half-squats or quarter-squats in order to dissipate any
accumulated fatigue and peak for a certain event. If a practitioner is
working with a sprinter, reducing the ROM of the work sets may be
advantageous from multiple aspects. For example, it may be practical to
progress a sprinter from performing full squats and adding in half-squats
and quarter-squats during certain phases of training (Bazyler et al., 2014).
Using a progression may not only reduce an athlete’s neuromuscular fatigue
due to less eccentric work performed, but partial squats may also increase
the mechanical specificity of their training for maximum velocity. This
notion is supported by recent research that indicated that training with
quarter-squats resulted in greater improvements in 40-yard sprint time and
vertical jump height compared to training with full and half-squats (Rhea et
al., 2016). However, it should be noted that additional literature has
suggested that the complete removal of full-ROM squats in trained
individuals may result in a plateau and possible reductions in 1RM strength
(Harris et al., 2000; Painter et al., 2012). Thus, practitioners should consider
prescribing a combination of both full and partial ROM squats in order to
improve/maintain overall and angle-specific strength.
Summary
While there are several factors that a practitioner must consider when
prescribing resistance-training exercises to their athletes, each individual
factor should not be overlooked. Exercise technique considerations such as
the ROM performed and the grip/stance used may alter the training stimulus
for athletes. In addition, practitioners must consider mechanical demands of
each exercise, including their force–velocity characteristics, the
inclusion/exclusion of the SSC, load placement, direction in which the force
is produced, and ballistic/non-ballistic nature. Finally, the rest intervals
used, whether they are inter-set, intra-set, or within potentiation complexes,
should be specific to the characteristics that are being developed within
each phase of training.
From a practical standpoint, practitioners should implement appropriate
modifications to exercises in order to provide an effective training stimulus
for their athletes. In addition, consistent external coaching cues combined
with specific feedback will improve the learning and retention of
challenging tasks. Finally, practitioners should note that a decreased ROM
combined with a sufficient load may provide an effective training stimulus
that is more specific to positions achieved during different phases of sport
training.
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16
Weightlifting for sports
performance
Timothy J. Suchomel and Paul Comfort
DOI: 10.4324/9781003044734-20
SECTION 2
The effectiveness of weightlifting movements
The term ‘weightlifting’ refers to the sport in which competitors perform
the snatch and the clean and jerk, attempting to lift the maximum amount of
weight. Weightlifting in this sense is different from the general term
‘resistance training’, which refers to all other forms of training in which an
individual is moving against a resistive load. However, weightlifting
movements (i.e. snatch, clean and jerk) and their derivatives may also be
used within resistance-training programmes in order to train the strength
and power characteristics of athletes who are not competing in the sport of
weightlifting.
While both weightlifting and other forms of resistance training may
improve an athlete’s lower-body strength and power, research suggests that
weightlifting movements and their derivatives may provide superior
training effects compared to other methods (Hoffman et al., 2004; Tricoli et
al., 2005; Channell and Barfield, 2008; Arabatzi and Kellis, 2012; Otto III
et al., 2012; Chaouachi et al., 2014; Teo et al., 2016). These findings are
attributed to two primary reasons: movement specificity and the overload
that the athlete can be subjected to.
Movement specificity
The most common movement in sports is the coordinated extension of the
hip, knee and ankle joints (plantar flexion), termed ‘triple extension’.
Jumping, sprinting and change-of-direction tasks require the completion of
the triple extension movement. A similar coordinated triple extension
movement takes place during the second pull phase of weightlifting
movements (see the section ‘Weightlifting technique’, below), which allows
these movements to transfer to sports performance. Due to the similarities
between the triple extension of sports movements and the second pull of
weightlifting movements, it should come as no surprise that better
performance of weightlifting movements is related to better performance
during sprinting and jumping (Carlock et al., 2004; Hori et al., 2008).
Overload
Weightlifting exercises are coordinated movements in which an athlete
moves a moderate-heavy load with ballistic intent. While other resistancetraining methods may be used to train lower-body strength and power (e.g.
free weights, plyometrics, kettlebells, etc.), these methods are typically not
performed in the same manner as weightlifting movements. For example,
training with the back squat may produce high forces but with less velocity,
whereas plyometric exercise may produce high velocities but with less
force. This is supported by previous literature that has demonstrated that the
power outputs of the snatch, clean and jerk were superior to core exercises
(primary compound exercises) such as the squat and deadlift (Garhammer,
1980, 1991). Additional literature indicated that standard resistance-training
exercises (e.g. bench press, squat, etc.) result in reduced force production
(i.e. deceleration) during as much as 45% of the range of motion.
Weightlifting technique
During the snatch in a weightlifting competition, the lifter must lift the
barbell from the floor to an overhead position, receiving the weight with the
arms fully extended, in one continuous motion. The clean is characterised
by lifting the barbell from the floor to a resting position across the front of
the lifter’s shoulders. As a continuation of the clean, the jerk is completed
by lifting the barbell from the shoulders to an overhead position, receiving
the weight with the arms fully extended. The technique of each lift is
described below.
Snatch/clean first pull
The first pull refers to the initial movement of the barbell from the floor to a
position just above the knee. The starting position of each athlete will be
based on their anthropometric characteristics such as their height, body
mass and somatotype as well as their range of motion and flexibility.
Athletes should position themselves so that they are centred on the bar with
their feet flat and positioned about hip-width apart and the barbell
positioned over the middle of their feet. The recommended grip to use with
weightlifting movements is the hook grip as this increases grip strength
(Figure 16.1). Whether performing a clean or snatch variation, the hands
may be positioned more closely together or further apart, respectively.
While the appropriate distance between the hands will vary based on an
individual’s anthropometrics, an easy method to determine this distance
involves placing the individual in a position where the second pull of the
snatch or clean starts (i.e. mid-thigh/power position) (Figure 16.2). From
here, the hands may be narrowed or spread further apart to ensure the
proper second pull position. The elbows should be pointed outward to
prevent excess elbow flexion that may hinder the transfer of force to the
barbell. The barbell should almost be in contact with the athlete’s lower leg,
their knees should be in line with their feet and their hips should be slightly
higher than their knees. The position of the upper body should include
extended arms, shoulders in front of the bar, an elevated chest, shoulder
blades pulled back and a slightly arched (natural curve) or flat back. Finally,
the athlete’s head should be neutral with the eyes looking forward (Figure
16.3).
Hook grip – (a) thumb wraps under the bar with (b) the fingers wrapped
around the thumb and bar.
Clean (top) and snatch (bottom) grip spacing.
Starting position for (left) the snatch and (right) clean.
After reaching the correct starting position, athletes should inhale to
increase their intra-abdominal pressure and remove any slack that may still
exist within their arms. The athlete should then begin the lift by pushing
into the ground through the centre of their feet while elevating their hips
and shoulders at the same rate and maintaining the angle of their back,
shoulders over the barbell, and fully extended arms. While elevating the
barbell, the knees move backward while the lower legs reach a near-vertical
position, resulting in a shift of the centre of pressure from the mid-foot to
the heels (Figure 16.4).
The end of the first pull for (left) the snatch and (right) clean.
Snatch/clean transition
The transition phase refers to the movement of the barbell from a position
just above the knee to the mid-thigh ‘power’ position in preparation for the
second pull. An effective transition phase requires the athlete to re-bend the
knees to a position in front of the barbell as it moves from the knee to the
mid-thigh, shifting the centre of pressure from the heels to the mid-foot.
The athlete’s hips should move over the ankles, resulting in a vertical torso,
extended arms and knees bent to approximately 125–145° (Figure 16.5).
Mid-thigh position side view for (left) the snatch and (right) clean.
Snatch/clean second pull
Upon reaching the mid-thigh position, athletes perform the second pull
movement by pushing into the ground and rapidly extending their hips,
knees and ankles (plantar flexion) and shrugging their shoulders (Figure
16.6). This movement causes the barbell to rise vertically and results in the
greatest force, rate of force development (RFD), velocity and power
(Enoka, 1979; Garhammer, 1980, 1982). Athletes should keep their arms
extended for as long as possible during the second pull to ensure maximum
force transfer to the barbell. However, the athlete’s arms will bend due to
the upward momentum of the barbell and the failure to elevate the torso any
higher. It should be noted that while the second pull results in the
completion of certain weightlifting derivatives (see the section
‘Weightlifting derivatives’, below), others require the athlete to catch or
receive the weight.
Second pull of (left) the snatch and (right) clean.
Snatch/clean catch
Following the second pull, a snatch variation requires the athlete to rotate
the hands and elbows around the barbell, moving from a vertical position
above the barbell into a position below the barbell. Simultaneously, the
athlete will flex the hips, knees and ankles (dorsiflexion), drop and pull
themselves into an overhead squat position while their feet may move
slightly outward to a more stable position. The athlete should receive the
barbell in an overhead squat position with their elbows locked out whilst at
the same time their feet land flat on the ground in the desired squat depth
while maintaining an upright torso and normal lumbar curve (Figure 16.7).
Catch position of the snatch (left) and clean (right). (Modified from DeWeese
et al., 2014.)
A clean variation requires the athlete to rotate the elbows around the
barbell from a position above the barbell into a horizontal position in front
of the barbell. The athlete will flex their hips, knees and ankles
(dorsiflexion), drop and pull themselves into a front squat position while
their feet may move slightly outward to a more stable position. The athlete
should receive the barbell in a front squat position on the front of their
shoulders with their elbows pointed forward, their upper arm nearly parallel
with the ground and a relaxed grip, while at the same time their feet land
flat on the ground in the desired squat depth while maintaining an upright
torso and normal lumbar curve (Figure 16.7). Figure 16.8 displays a power
clean and power snatch catch variation.
Power snatch (left) and power clean (right) catch positions.
Snatch/clean recovery
After becoming stable in the desired squat depth for snatch and clean
variations, the recovery phase requires the athlete to return to a standing
position maintaining the overhead or front squat position (Figure 16.9). The
athlete should maintain an upright torso while extending the hips and knees
to return to a standing position.
Recovery position for the snatch (left) and clean (right).
Jerk starting position
As a continuation of the clean exercise, or from a rack or training blocks,
the athlete should start in standing position with the feet approximately
shoulder-width apart, an upright torso and the barbell racked across the
front of their shoulders with their upper arms nearly parallel to the floor.
The athlete’s eyes should be forward and their chin tucked (Figure 16.10).
An alternative variation would allow the athletes to start with the barbell
resting on their upper back, similar to a back squat.
Starting position for a jerk variation.
Jerk dip
Before the athlete begins the lift, the athlete should take a deep breath in
order to elevate the rib cage, brace the other trunk musculature and create
intra-abdominal pressure. Following the breath, the athlete will
simultaneously flex their hip and knee joints and descend to a quarter-squat
position where the knees are flexed to approximately 125–145° (Figure
16.11). While slightly shifting backwards during the dip, the athlete’s
weight should be distributed between their mid-foot and heels. As the
athlete descends, they should keep their elbows elevated to prevent the
barbell from moving away from their centre of mass. This common error
may result in the athlete pushing the barbell more forward rather than
vertically during the drive phase. In addition, it is important to maintain the
centre of pressure through the mid-foot to heel. The dip phase should be
completed rapidly without pausing in the bottom position in order to receive
the greatest stretch-shortening cycle benefits (i.e. greater use of stored
elastic energy and less force dissipation).
Completion of the dip phase of the jerk.
Jerk drive
Upon reaching the bottom of the dip phase, the athlete should immediately,
without pausing, rapidly extend the hip, knee and ankle joints in order to
drive the barbell up vertically (Figure 16.12). The triple extension
movement should cause the barbell to elevate off the athlete’s shoulders and
pass in front of their face. It is important to remind the athlete to tuck their
chin during the drive phase in order to prevent possible injury. As the
barbell continues to elevate, the athlete should grasp it with an overhand
grip. Simultaneously, the athlete’s feet are beginning to split either forward
and backward (split jerk) or laterally (power jerk). The athlete’s torso
should remain upright and rigid in preparation for receiving the load
overhead.
The drive phase of the jerk.
Jerk receiving positions
Depending on the variation used, split jerk or power jerk, the athlete’s feet
will continue to split forward and backward or laterally. Coaches should
note that the splitting of the feet should not be a jumping motion, but rather
a continuation of the drive phase. During the split jerk (Figure 16.13), the
athlete should ‘jab’ the front foot forward so that it is flat on the ground
with the pressure on the heel. The athlete’s front knee should flex and
remain in line with their toes. Simultaneously, the athlete’s back foot moves
backward and is planted on the ball of their foot with their heel off the
ground. The back leg should be slightly bent to allow for the absorption of
force as the load is received overhead. As the athlete splits their legs, they
should also continue the drive phase by pushing the barbell vertically and
receiving it overhead with their elbows in a locked position. The barbell
should be received with a braced torso in a position where the barbell is
directly above the back of the head (Figure 16.13). The split distance of the
athlete’s legs will be individualised based on anthropometrics, flexibility
and strength.
Split jerk receiving position.
A power jerk variation follows a similar sequence of movements through
the drive phase. Instead of splitting the feet forward and backward, the
athlete moves their feet slightly laterally and flexes their hips and knees into
a quarter-squat position. At this point, the athlete continues to drive the
barbell upward before receiving in the previously described overhead
position (Figure 16.14).
Power jerk receiving position.
Jerk recovery
In order to recover from a split jerk position, the athlete should first step
backwards with their front foot until it is close to the body and then step
forward with the back foot until the legs are together all while maintaining
an upright posture and the barbell held overhead with locked arms (Figure
16.15). The movements of the legs should be completed in this order to
allow for the centre of mass to be moved backwards against a braced back
leg rather than creating forward momentum by moving towards the front
leg.
Once in a stable receiving position during the power jerk, the athlete
should extend their hips and knees while maintaining an upright torso and
holding the barbell overhead with locked arms to return to a standing
position (Figure 16.15).
Jerk recovery.
Weightlifting derivatives
As mentioned above, the primary weightlifting movements are the snatch,
clean and jerk. However, it should be noted that there are several partial lifts
(i.e. weightlifting derivatives) that exclude part of the full snatch, clean or
jerk movements. Despite removing an aspect of the lift, weightlifting
derivatives may also be effectively implemented into resistance-training
programmes for athletes. It should be noted that weightlifting derivatives
may be further sub-divided into weightlifting catching and pulling
derivatives.
Weightlifting catching derivatives
Weightlifting catching derivatives are defined as weightlifting movements
that involve the catch phase of the snatch or clean, but omit a portion of the
traditional snatch or clean movement (e.g. full squat catch, lifting the
barbell off the floor, etc.). In addition to producing high-power outputs
during the triple extension movement, it is generally believed that
weightlifting catching derivatives will train an athlete to decelerate an
external load, which is an important characteristic for athletes in sports such
as rugby, American football and wrestling. Previous research has indicated
that weightlifting catching derivatives may be used as a training tool to
improve landing characteristics, as loading during the catch was
comparable to that observed during a drop jump landing (Moolyk et al.,
2013).
As with any exercise, the athlete’s technique is vital to receive the
optimal training stimulus while minimising the risk of injury. This is
especially true when it comes to weightlifting movements and their
derivatives as they are highly complex regarding technique. Several studies
have examined factors that may influence the proper completion of the
snatch and clean and jerk exercises. Researchers have examined the effect
that loading has on snatch and clean and jerk technique (Häkkinen et al.,
1984), snatch technique of weightlifters at different levels (Kauhanen et al.,
1984; Harbili and Alptekin, 2014), technique changes following feedback
(Winchester et al., 2009) and the technique differences between successful
and unsuccessful snatch attempts (Stone et al., 1998; Gourgoulis et al.,
2009) and power clean repetitions (Kipp and Meinerz, 2017). The findings
from this literature are beneficial in that they may help improve coaching
cues and the focus on critical aspects of each lift.
The most common snatch and clean derivatives prescribed are the power
clean/snatch and hang power clean/snatch. Thus, to aid practitioners and
their programming decisions, researchers have examined these exercises by
attempting to find the load that produces the greatest magnitude of power
(i.e. the optimal load). This research has indicated that loads ranging from
70% to 80% one repetition maximum (1RM) may provide the optimal
training load for the power clean (Comfort et al., 2012a) and hang power
clean (Kawamori et al., 2005; Kilduff et al., 2007). Interestingly, a paucity
of research has examined the optimal training load for snatch catching
derivatives. However, the information presented within the literature
surrounding the optimal training loads of weightlifting catching derivatives
is important for practitioners when it comes to prescribing loads during
various training phases. Furthermore, it is important that practitioners
understand that the optimal load may be specific to the device used to
measure power output (e.g. force plate, linear position transducer, etc.)
(Hori et al., 2005; Cormie et al., 2007; McBride et al., 2011; Lake et al.,
2012). Practitioners should also determine which magnitude of power is
specific to the athlete’s sport/event. For example, power applied to the
barbell is essential for weightlifters, whereas power applied to the system is
arguably more important in terms of assessing the development of lowerbody power. A review has discussed optimal loading ranges for lower-body
exercises and concluded that a range of loads should be prescribed when
training for maximal power output (Soriano et al., 2015). This notion is
supported by additional literature (Newton and Kraemer, 1994; Newton et
al., 2002; Haff and Nimphius, 2012).
A third aspect of the extant literature focuses on different cluster set
configurations when it comes to implementing weightlifting catching
derivatives. The results of these studies indicate that the use of cluster sets
offset the increase in perceived effort (Hardee et al., 2012a), allowed for
technique to be maintained (Hardee et al., 2013) and also allowed power
output to be maintained throughout the set (Hardee et al., 2012b). From a
practical standpoint, it appears that 20–40 seconds of inter-repetition rest
may allow the athlete to experience a better training stimulus when training
with the clean derivatives. See Chapter 13 for a detailed discussion of the
use of cluster sets.
Weightlifting pulling derivatives
Weightlifting pulling derivatives, as the name suggests, are weightlifting
derivatives that remove the catch phase and finish with the completion of
the second pull (Figure 16.6). Examples of weightlifting pulling derivatives
discussed within the literature include the clean/snatch mid-thigh pull, pull
from the knee, hang pull, pull from the floor, countermovement shrug, hang
high pull and jump shrug (Suchomel et al., 2017a). Some of the benefits of
the above derivatives include decreased exercise complexity regarding
technique, a potential decreased learning and teaching time for the
movements, a potential reduction of impact on specific joints and a greater
ability to overload the triple extension movement (Suchomel et al., 2015b).
Due to the number of benefits that may enhance the abilities of athletes,
research has examined weightlifting pulling derivatives in several
capacities, including comparisons with weightlifting catching derivatives,
loading effects and different set configurations.
Cross-sectional comparisons with weightlifting catching derivatives
have shown that weightlifting pulling derivatives may produce a
comparable (Comfort et al., 2011a, 2011b) or superior (Suchomel et al.,
2014b; Suchomel and Sole, 2017a, 2017b; Kipp et al., 2018; Kipp et al.,
2019a, 2019b; Takei et al., 2020) training stimulus compared to
weightlifting catching derivatives with regard to peak force, velocity,
power, RFD and impulse. Further research indicated that the load
acceptance demands (work, mean force, duration) of weightlifting pulling
derivatives are similar or greater compared to weightlifting catching
derivatives (Comfort et al., 2017; Suchomel et al., 2017b, 2018a, 2020b).
While the above studies display the cross-sectional differences between
weightlifting catching and pulling derivatives, research that displays
longitudinal strength-power adaptations may be more beneficial. Comfort et
al. (2018) examined the differences of training for 8 weeks with either
weightlifting catching or pulling derivatives that were load-matched. Their
findings showed no differences in 1RM power clean, isometric mid-thigh
pull force production characteristics or countermovement jump
performance between groups, indicating that either catching or pulling
derivatives may be used to improve strength-power adaptations.
Interestingly, two recent studies (Suchomel et al., 2020a, 2020b) expanded
on the study by Comfort et al. (2018) and added a third group that trained
using weightlifting pulling derivatives that included phase-specific loading
to provide a force (loads >100% 1RM) or velocity (loads <50% 1RM)
overload stimulus. The findings from the recent studies showed that training
with weightlifting pulling derivatives that include a force and velocity
overload stimulus may produce greater dynamic and isometric strength,
sprint and change-of-direction adaptations (Suchomel et al., 2020a), as well
as greater squat jump and countermovement jump propulsive force
adaptations (Suchomel et al., 2020b). The results of the latter two training
studies suggest that the ability to expand the loading spectrum using
weightlifting pulling derivatives may allow for more favourable strengthpower adaptations.
Similar to weightlifting catching derivatives, much of the research that
focuses on weightlifting pulling derivatives has examined the effect that the
external load has on various kinetic and kinematic variables. Through
examining different loads, sport scientists and practitioners can determine
which loads provide the optimal training stimulus for athletes within the
context of each exercise. Furthermore, these findings may then be applied
within resistance-training programmes. For example, the goals of maximal
strength and absolute strength-training blocks are to enhance the maximal
force production capacity of the athlete and to begin the initial stages of
enhancing their RFD characteristics against heavy external loads. Thus,
weightlifting pulling derivatives that allow for the use of heavier training
loads may aid in the development of the desired characteristics. Researchers
have shown that the mid-thigh pull (Comfort et al., 2012b, 2015; Meechan
et al., 2020b), countermovement shrug (Meechan et al., 2020b), pull from
the knee/hang pull (Meechan et al., 2020a) and pull from the floor (Haff et
al., 2003) may use loads in excess of an athlete’s 1RM power clean because
these derivatives do not require athletes to drop under the barbell and catch
the load. Specifically, practitioners may prescribe loads up to approximately
120–140% of their 1RM power clean, as long as proper technique is
maintained. Based on these findings, it is clear that weightlifting pulling
derivatives may enhance an athlete’s force production characteristics. In
fact, previous research indicated that implementing weightlifting pulling
derivatives such as the mid-thigh pull, countermovement shrug and pull
from the floor produced greater peak force production adaptations
compared to only implementing weightlifting catching derivatives
(Suchomel et al., 2020a).
Another example would be selecting exercises that maximise power
production during speed-strength-training blocks. While high-force
production is emphasised during maximal strength and absolute strengthtraining blocks, the goals of a speed-strength-training block are to peak the
RFD and power characteristics of athletes prior to competition. Thus,
weightlifting pulling derivatives that are the most ballistic in nature may be
useful exercises that may aid in the development of these characteristics.
Previous research has examined the effect that load has on the jump shrug
(Suchomel et al., 2013) and hang high pull (Suchomel et al., 2015a). The
results of these loading studies indicated that the lightest loads examined
(i.e. 30 and 45% of 1RM hang power clean) produced the greatest
magnitudes of velocity and power. It should be noted that athletes may not
always perform a 1RM catching derivative and may thus require another
method to prescribe loads for weightlifting pulling derivatives. A recent
study indicated that loads from 20–40% body mass or 10–20% of a back
squat 1RM may be used to optimise power output for the jump shrug
(Suchomel et al., 2019). However, practitioners should use caution when
prescribing loads based on body mass or from a 1RM squat because relative
strength may alter the performance of weightlifting movements. In contrast
to exercises such as the mid-thigh pull and pull from the floor, it is clear
that the jump shrug and hang high pull may fall on the opposite end of the
loading spectrum, but may still be useful during certain phases of training
(Suchomel et al., 2017a). It should be noted that unpublished data support
the notion that exercise-specific loading with weightlifting pulling
derivatives may also produce greater rapid force production (e.g. force at
50–200 ms) adaptations compared to submaximally loaded weightlifting
catching and pulling derivatives.
A third area of research on weightlifting pulling derivatives is research
that examines different set configurations. For example, the aforementioned
studies may provide the practitioner with the choice of exercise and the
potential loads that coincide as an effective training stimulus; however, the
performance of each repetition may be modified based on the set structure.
Previous research has examined different set configurations (traditional,
undulating and cluster) when performing the clean pull from the floor (Haff
et al., 2003). The results of this study indicated that the use of a cluster set
may result in greater barbell velocity and displacement during the clean pull
from the floor compared to a traditional set. More recent research examined
the effect of rest redistribution sets that modified the traditional set structure
by taking the total amount of rest between sets and distributing it between
smaller sets of the clean pull from the floor (Jukic and Tufano, 2019, 2020).
The results from this research indicated that rest redistribution sets allowed
for the maintenance of movement velocity and power (Jukic and Tufano,
2019) as well as lower perceived and mechanical fatigue (Jukic and Tufano,
2020). Further detail on different set configurations is discussed in Chapter
13.
SECTION 2
Practical applications
Developing an athlete’s force–velocity profile
As described in Chapter 2, one of the primary goals of a strength and
conditioning practitioner is to develop the force–velocity profile of their
athletes in order to enhance important force production characteristics such
as impulse, RFD and power. Haff and Nimphius (2012) indicated that the
most effective way to develop an athlete’s force–velocity profile is through
the use of training methods that will develop both the force and velocity
ends of the spectrum. While this process can be completed using different
set and repetition schemes, warm-up and warm-down sets, and various
intensities during core exercises (squat, bench press, etc.), a sequenced
progression of weightlifting derivatives may also develop the entire force–
velocity profile of an athlete (Suchomel et al., 2017a). Figure 16.16 displays
the theoretical force–velocity relationship specific to weightlifting
derivatives.
Force–velocity curve for weightlifting exercises. 1RM, one repetition
maximum; HPC, hang power clean; PC, power clean.
The previously discussed literature supports the notion that weightlifting
derivatives such as the mid-thigh pull, countermovement shrug, pull from
the knee, hang pull and pull from the floor may all be used to develop highforce production characteristics due to the decreased displacement of the
load during each movement. On the opposite end of the force–velocity
curve are weightlifting derivatives that are characterised by higher
velocities. The jump shrug, hang high pull, mid-thigh clean/snatch and
countermovement (hang) clean/snatch are weightlifting derivatives that are
highly ballistic and are typically programmed with low-moderate loads
(<60% 1RM). While the placement of derivatives within Figure 16.16 is
supported by evidence, it should be noted that the load prescribed may
influence the position of each exercise on the force–velocity curve. For
example, while the mid-thigh pull enables athletes to use the heaviest loads
(i.e. 140% of 1RM power clean), power production and velocity were
maximised with the lightest load (i.e. 40% of 1RM power clean) (Comfort
et al., 2012b, 2015). However, recent research from Meechan et al. (2020b)
indicated that the addition of a countermovement (e.g. countermovement
shrug) may allow peak power to occur across a spectrum of loads (i.e. 80–
120% of 1RM power clean) based on the trade-off between force and
movement velocity with a change in load.
As discussed in Chapter 7, previous literature suggests that a sequenced
progression of training phases promotes the optimal development of an
athlete’s force–velocity profile (Stone et al., 1982; Minetti, 2002; Zamparo
et al., 2002). Briefly, increases in work capacity and muscle cross-sectional
area produced during a strength-endurance (hypertrophy) phase enhance an
athlete’s ability to increase their muscular strength. From here, increases in
muscular strength will then enhance an athlete’s potential to improve their
RFD and power characteristics. A similar approach can be taken when
prescribing weightlifting derivatives because certain lifts place greater
emphasis on either force or velocity. Thus, specific weightlifting catching
and pulling derivatives may be prescribed during resistance-training phases
in order to meet the goals of each phase and develop the force–velocity
profile of the athlete. The following will discuss the implementation of
weightlifting derivatives into various resistance training phases to promote
the optimal development of an athlete’s force–velocity profile.
Strength-endurance
The strength-endurance phase is characterised by a high volume of
repetitions (usually 8–12) in exercises that use moderately heavy loads (60–
70% 1RM). The purpose of this phase is to increase the athlete’s work
capacity, stimulate increases in muscle cross-sectional area and refine
exercise technique for subsequent training phases. Regarding the use of
weightlifting derivatives within this phase, it is suggested that practitioners
implement the clean/snatch pull from the floor, pull to the knee and clean
grip shoulder shrug for several reasons. First, the suggested derivatives
serve as foundation exercises that enable the progression to more complex
weightlifting movements. The inability to perform these exercises may lead
to improper exercise technique of more complex derivatives, potentially
impacting the training stimulus. Second, the clean/snatch pull from the floor
enables athletes to overload the triple extension movement without
experiencing the additional stress and complexity of performing the catch
phase every repetition as fatigue develops. While the catch phase of certain
weightlifting derivatives may enable the athlete to develop additional
performance characteristics as mentioned above, the high volume
experienced during the strength-endurance phase may lead to a
deterioration in form due to acute fatigue. Moreover, a decline in technique
may alter catch phase mechanics and increase the likelihood of injury or
compression stress. Finally, the suggested derivatives enable the
development of important lower- and upper-body musculature that will be
used to enhance the force–velocity profile during later training phases in
tandem with exercises such as squatting, pressing and pulling movements.
Recent training studies have displayed how to effectively implement pulling
derivatives within a higher-volume training phase (Suchomel et al., 2020a,
2020b).
It should be noted that the athletic population may dictate which
weightlifting movements are prescribed in a strength-endurance-training
block. For example, the clean/snatch pull from the floor may only be
implemented with an athletic population whose technique is more
consistent and resilient to fatigue. Practitioners may also consider
prescribing cluster sets of either two or five repetitions for the clean/snatch
pull from the floor due to the high volume within the strength-endurance
phase. As discussed in Chapter 13, the use of cluster sets or rest
redistribution sets may enable the athlete to maintain technique, force
production and power output throughout each set (Jukic and Tufano, 2019,
2020) leading to high-quality work, enhanced work capacity and force
production adaptations with a high volume of repetitions. Moreover, the
inter-repetition rest interval may allow the coach to provide additional
feedback to the athlete.
Maximal strength
A maximal-strength phase is used to increase an athlete’s force production
capacity using sets of 4–6 repetitions and moderately heavy to heavy loads
(i.e. 80–90% 1RM, although potentially slightly higher with pulling
derivatives). During this phase, practitioners should shift their focus to
exercises that emphasise force production and enable the use of heavier
loads. A limitation to weightlifting catching derivatives is that practitioners
cannot prescribe loads greater than the athlete’s 1RM. This, however, is not
the case for weightlifting pulling derivatives as exercises such as the
clean/snatch pull from the floor, pull from the knee and mid-thigh pull
allow for loads greater than the athlete’s 1RM to be used due to the
elimination of the catch phase and decreased displacement of the load. The
use of these exercises combined with heavier loads will emphasise force
production and train the high-force portion of the force–velocity curve.
Absolute strength
Similar to the maximal-strength phase, the goals of the absolute-strength
phase are to enhance the athlete’s low-repetition (e.g. 1–3) force production
(both magnitude and rate) characteristics using near-maximal loads (90–
95% 1RM or potentially as high as 120–140% 1RM with pulling
derivatives). While the same exercises from the maximal-strength phase
may be prescribed to retain the athlete’s capacity for high-force production,
additional derivatives that include a strength-speed component should be
introduced to begin the enhancement of RFD. These exercises might
include the hang power clean/snatch (Suchomel et al., 2014a), power
clean/snatch, mid-thigh clean/snatch (Comfort et al., 2011a, 2011b) and the
full clean/snatch. The combination of high-force movements and
introducing high-velocity movements will ultimately contribute to the
athlete’s ability to further develop impulse, RFD and power characteristics.
Strength-speed
The primary goals of the strength-speed phase are to further increase RFD
and power, while also maintaining or potentially increasing the athlete’s
strength. Because previous literature has indicated that RFD and power are
two of the most important characteristics regarding an athlete’s performance
(Morrissey et al., 1995; Stone et al., 2002), it is important to prepare the
athlete to maximise these adaptations using the previously discussed
training phases. Based on the phasic progression of resistance-training
phases, increases in muscular strength (Suchomel et al., 2016b, 2018b) and
RFD (Taber et al., 2016) from the previous training phases should, in
theory, enhance the athlete’s ability to augment their power characteristics.
Regarding the programming of weightlifting derivatives during the
strength-speed phase, RFD and power characteristics may be enhanced
using a combination of heavy and light loads. However, the emphasis
within this phase is to move relatively heavy loads quickly in order to
enhance RFD characteristics. Thus, the mid-thigh clean/snatch,
countermovement clean/snatch and power clean/snatch from the knee
(Suchomel et al., 2016a) may be used to develop the high-velocity portion
of the force–velocity curve, while the power clean, clean/snatch pulls from
the floor, knee and mid-thigh may develop the high-force end of the force–
velocity curve.
Speed-strength
The goals of the speed-strength phase are to produce peak adaptations in
RFD and power prior to competition. In order to peak these abilities, a wide
variety of weightlifting derivatives may be prescribed. Many of the
previously described derivatives may be prescribed; however, the speed at
which the movement is performed, and therefore the load, must be
considered. For this reason, the jump shrug and hang high pull may be
highlighted during the speed-strength phase due to their ballistic nature. A
combined approach of prescribing heavy- and light-loaded derivatives
should be implemented to optimise RFD and power adaptations. Thus,
practitioners may prescribe a combination of the clean/snatch mid-thigh
pull or pull from the floor and the jump shrug and hang high pull to focus
on training each end of the force–velocity curve. Varying neurological
demands will be placed on the athlete as the above combination will
simulate overcoming the inertia of an external load from a static start (e.g.
mid-thigh pull) and using the stretch-shortening cycle (e.g. jump shrug),
allowing them to optimise impulse, RFD and power characteristics.
Another aspect to consider during the speed-strength phase is the load
implemented with each exercise. Previous literature has suggested that
training at or near the loads that maximise power may produce favourable
strength-power adaptations (Kawamori and Haff, 2004). As discussed
above, loads of approximately 70–80% 1RM may provide the optimal
training load for the power clean and hang power clean, while lighter loads
(i.e. 30–45% 1RM of hang power clean) may serve as an optimal training
stimulus for the jump shrug and hang high pull. Additional literature has
indicated that loads of approximately 90% of an athlete’s 1RM power clean
(Haff et al., 2003) or full clean/snatch (Ermakov, 1980) may optimise the
training stimulus for the clean/snatch pull from the floor, while loads of
100% and 120% 1RM power clean may maximise power during the pull
from the knee/hang clean pull (Meechan et al., 2020a) and
countermovement shrug (Meechan et al., 2020b), respectively.
Speed development
A sequenced progression of programming weightlifting derivatives may aid
in the development of an athlete’s speed characteristics (DeWeese et al.,
2016). Using the methods described above, specific weightlifting
derivatives may be programmed during specific strength-training phases
that coincide with speed development phases (Figure 16.17). The following
will discuss the rationale of prescribing a sequenced progression of
weightlifting derivatives to enhance an athlete’s sprint speed.
Sequenced progressions of speed and strength-power development with the
weightlifting derivatives that may be used within each phase. CM,
countermovement. (Modified from DeWeese et al., 2014.)
General preparation phase
As displayed in Figure 16.17, the general preparation phase is focused on
improving the accelerative abilities of an athlete. Coaches may choose to
program resisted runs (i.e. incline sprints and towing) at this point to
develop high propulsive forces into the ground, while in the weight room a
strength-endurance phase serves to develop the athlete’s work capacity and
cross-sectional area in order to enhance their muscular strength and power
in later training phases (Stone et al., 1982). As mentioned above,
practitioners may program the clean/snatch pull to knee, pull from the floor
and shoulder shrug. Each of these movements can be used to strengthen the
athlete’s musculature at specific angles that relate to their posture during
various acceleration phases. For example, the first pull requires athletes to
start from a knee angle of approximately 90° and extend the knees to about
120°, which are angles that coincide with a sprinter’s knee angles in the
starting blocks.
Special preparation phase
Upon entering the special preparation phase of training, the training
emphasis builds upon the enhanced acceleration characteristics from the
previous phase to build top speed characteristics. Coaches may program
running drills such as acceleration holds, low-load resisted runs and longer
segment accelerations during this phase before introducing maximumvelocity sprinting drills (e.g. fly-in sprints and in-and-outs). Concurrently in
the weight room, the focus of training shifts to improving the athlete’s
strength characteristics. The clean/snatch pull from the floor, pull from the
knee and mid-thigh pull exercises serve to develop vertical force production
through the ranges of motion experienced during the acceleration and
transition to upright running phases. Moreover, these movements overload
the athlete in a position that is relative to top speed mechanics (i.e. 125–
145° knee angle, upright torso and shortened range of motion) (DeWeese et
al., 2015). In addition, exercises like the hang power clean/snatch, power
clean/snatch, mid-thigh clean/snatch and the full clean and snatch may be
programmed during this phase to introduce a strength-speed component that
will aid in the development of the athlete’s RFD characteristics.
Early-mid competition phase
Leading into the start of the season, coaches will typically prescribe drills
that will retain an athlete’s accelerative and top speed abilities through short
sprint work as well as training sessions specific to the sprint distances of the
athlete’s sport/event. Within the weight room, an early emphasis should be
placed on strength-speed. Thus, weightlifting derivatives that focus on
moving heavier loads quickly should be programmed. The suggested
exercises within this phase include the mid-thigh pull, countermovement
shrug and the power clean/snatch. The mid-thigh pull and
countermovement shrug in this case will maintain high-force production
characteristics as practitioners may program up to 140% 1RM, while the
power clean/snatch enables athletes to utilise the stretch-shortening cycle
that occurs during the double-knee bend, as described above. The latter will
allow athletes to generate large vertical forces in an upright position that
may counteract those experienced during the stance phase of sprinting.
Finally, the emphasis may shift to incorporating speed-strength exercises
which move lighter loads quickly. Such exercises may include the
countermovement clean/snatch, mid-thigh clean/snatch, hang high pull and
jump shrug.
Late competition/taper phase
Upon reaching the latter stages of competition, the emphasis in weight
room training aims to emphasise speed-strength characteristics while
retaining strength-speed characteristics. Practitioners may elect to
implement a variety of ballistic movements such as potentiation complexes,
light-weighted jump squats, plyometrics, etc. However, regarding
weightlifting derivatives, the countermovement clean/snatch, mid-thigh
clean/snatch, hang high pull and jump shrug should be implemented during
this phase of training. In addition, practitioners may consider implementing
the mid-thigh pull to continue to retain strength-speed qualities. In fact, the
mid-thigh pull could be programmed prior to one of the previously
mentioned exercises in order to potentiate the power output of the latter
exercise.
Summary
Weightlifting movements and their derivatives are effective training tools
that may be used to enhance an athlete’s lower-body ‘explosiveness’ and
load acceptance/braking characteristics. Weightlifting catching and pulling
derivatives both provide useful training stimuli and may be programmed to
meet the specific goals of various resistance-training phases. A sequenced
progression of weightlifting catching and pulling derivatives may be used to
optimally develop the force–velocity profile and speed of an athlete.
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