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Strength Training Manual
The Agile Periodization Approach
Volume One
Mladen Jovanović
Published by:
Complementary Training
Belgrade, Serbia
2019
For information: www.complementarytraining.net
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Jovanović, M.
Strength Training Manual. The Agile Periodization Approach. Volume One
ISBN: 978-86-900803-1-1
978-86-900803-2-8 (Volume One)
Copyright © 2019 Mladen Jovanović
Cover design by Ricardo Marino
Cover image used under license from Shutterstock.com
E-Book design by Goran Smiljanić
All rights reserved. This book or any portion thereof may not be reproduced or used in
any manner whatsoever without the express written permission of the author except
for the use of brief quotations in a book review.
Published in Belgrade, Serbia
First E-Book Edition
Complementary Training
Website: www.complementarytraining.net
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Table of Contents
Preface to the Volume One . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Precision versus Significance. . . . . . . . . . . . . . . . . . . . . . . . . 10
Generalizations, Priors, and Bayesian updating. . . . . . . . . . . . . . . . 11
Large and Small Worlds• . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Different prediction errors and accompanying costs. . . . . . . . . . . . . . 13
Classification, Categorization and Fuzzy borders . . . . . . . . . . . . . . . 15
Place of Things vs Forum for Action . . . . . . . . . . . . . . . . . . . . .
16
Qualities, Ontology, Phenomenology, Complexity, Causality . . . . . . . . . 17
Philosophical stance(s) and influential persons. . . . . . . . . . . . . . . . 19
What is covered in this manual?. . . . . . . . . . . . . . . . . . . . . . .
19
2 Agile Periodization and Philosophy of Training . . . . . . . . . . . . . . . . . 21
Iterative Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Top-Down vs. Bottom-Up. . . . . . . . . . . . . . . . . . . . . . . . . . 23
Phases of strength training planning. . . . . . . . . . . . . . . . . . . . . 25
Qualities, Methods, and Objectives . . . . . . . . . . . . . . . . . . . . . . 26
Dan John's Four Training Quadrants. . . . . . . . . . . . . . . . . . . . .
31
Goals Setting and Decision Making (in Complexity and Uncertainty)•. . . . . 33
OKRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
37
Designing MVP . . . . . . . . . . . . . . . . . . . . . . . . . . . .
38
Is/Ought Gap and Hero’s Journey•. . . . . . . . . . . . . . . . . . . . . .
38
Evidence-based mumbo jumbo• . . . . . . . . . . . . . . . . . . . . . . . 41
Certainty, Risk, and Uncertainty•. . . . . . . . . . . . . . . . . . . . . . . 42
4
Optimal versus Robust . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
Positive and Negative knowledge. . . . . . . . . . . . . . . . . . . . . . . 46
Barbell Strategy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
47
Randomization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Latent vs. Observed. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50
Inter-Individual vs. Intra-Individual. . . . . . . . . . . . . . . . . . . . . 54
Substance vs. Form• . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Other complementary pairs . . . . . . . . . . . . . . . . . . . . . . . . . 59
Explore – Exploit . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Growing - Pruning. . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Develop – Express. . . . . . . . . . . . . . . . . . . . . . . . . . . 61
Maintain – Disrupt . . . . . . . . . . . . . . . . . . . . . . . . . .
61
Structure - Function. . . . . . . . . . . . . . . . . . . . . . . . . . 63
Weaknesses – Strengths. . . . . . . . . . . . . . . . . . . . . . . . 63
The Function of Muscles in the Human Body. . . . . . . . . . . . . . . . . 66
Grand Unified Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . .
70
Shu-Ha-Ri and Bruce Lee’s punch. . . . . . . . . . . . . . . . . . . . . . 71
Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
72
3 Exercises. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
General vs. Specific. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Grinding vs. Ballistic. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
Grinding movements . . . . . . . . . . . . . . . . . . . . . . . . .
78
Ballistic movements . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Control movements . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Simple vs. Complex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Fundamental movement patterns• . . . . . . . . . . . . . . . . . . . . . . 81
Grinding movement patterns . . . . . . . . . . . . . . . . . . . . .
83
Ballistic movement patterns. . . . . . . . . . . . . . . . . . . . . . 85
Combining movement patterns with the Time-Complexity quadrants. 86
Exercise Priority/Emphasis/Importance . . . . . . . . . . . . . . . . . . . 87
Session Position. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
Use of the Slots and Combinatorics. . . . . . . . . . . . . . . . . . . . . . 90
The use of Functional Units in Team Sessions. . . . . . . . . . . . . . . . 92
1RM relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
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Upper Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
Lower Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
Combined. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
What should you do next? . . . . . . . . . . . . . . . . . . . . . . . . . . 100
4 Prescription . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
Three components of Intensity (Load, Intent, Exertion) •. . . . . . . . . . 103
Load-Max Reps Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
Load-Exertion Table. . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
Not all training maximums are created equal. . . . . . . . . . . . . . . . . 111
Purpose of 1RM or EDM . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
How to estimate 1RM or EDM? . . . . . . . . . . . . . . . . . . . . . . . . 115
True 1RM test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Reps to (technical) failure . . . . . . . . . . . . . . . . . . . . . . . 117
Velocity based estimates. . . . . . . . . . . . . . . . . . . . . . . . 118
Estimation through iteration. . . . . . . . . . . . . . . . . . . . . . 121
Total System Load vs. External Load?. . . . . . . . . . . . . . . . . . . . 125
Comparing individuals . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
Simple ratio (relative strength) . . . . . . . . . . . . . . . . . . . . 134
Allometric scaling . . . . . . . . . . . . . . . . . . . . . . . . . . 135
Percent-based approach to prescribing training loads• . . . . . . . . . . . 137
Prescribing using open sets. . . . . . . . . . . . . . . . . . . . . . 138
Prescribing using %1RM approach
(percent-based bread and butter method) . . . . . . . . . . . . . . . 139
Prescribing using subjective indicators of exertion levels (RPE, RIR). . 140
Prescribing using Velocity Based Training (VBT) . . . . . . . . . . . . 141
Other prescription methods . . . . . . . . . . . . . . . . . . . . . . 142
Modifications of the percent-based approach . . . . . . . . . . . . . 142
Rep Zones. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
Load Zones. . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
Subjective Indicators. . . . . . . . . . . . . . . . . . . . . . . 145
Velocity Based Training. . . . . . . . . . . . . . . . . . . . . . 146
Time and Reps Constraints . . . . . . . . . . . . . . . . . . . . 147
Prediction and monitoring . . . . . . . . . . . . . . . . . . . . . . . . . 148
Ballistic Movements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
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What is 1RM with ballistic movements . . . . . . . . . . . . . . . . . . . . 159
What is failure with ballistic movements (and how many reps to do)•. . . . 162
Appendix: Exercise List. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
About. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
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STRENGTH TRAINING MANUAL Volume One
Preface to the Volume One
When I started writing the Strength Training Manual, I wanted it to be a simple
and short book with heuristics and reference tables. As I began to write, I soon realized
that the readers will have hard time understanding how to actually apply those heuristics
and tables, as well as understand the whys behind them. Additionally, writing is not a
simple act of dumping material on paper for me, but rather an act of exploration and
discovery. Therefore, as I wrote, new things emerged and I wanted to play with them,
attack them from multiple perspectives to see how robust they are. In the end, this made
the Strength Training Manual much larger and much slower to write than I originally
intended.
The reasons why the Strength Training Manual e-book comes in volumes are
as follows. First, I can split it in chunks, which, for those who embark on any writing
adventure, is much more manageable. Second, I wanted this to be available to the
readers as soon as possible, so that I can collect the feedback and improve the text for the
potential paperback/hardback edition. Third, reading 600-page e-book is much harder
than reading 200-something e-book. Fourth, the profit. E-book version of the Strength
Training Manual published in volumes is available for free for the Complementary
Training members, which makes it an additional benefit of the membership. In a
nutshell, publishing in volumes seemed like a good idea and a solution. Only time will
tell if I was right or wrong.
In this Volume One, first four chapters are published, plus the exercise table from
the Appendix. This Volume is heavier on the philosophy and the Agile Periodization
behind my strength training planning, although chapters 3 and 4 are much more
practical and provide multiple useful tables and heuristics.
As always, I am looking forward to your critiques and feedback. Please do not
hesitate to contact me if you have any questions or spot any kind of bullshit.
Mladen Jovanović
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MLADEN JOVANOVIĆ
1 Introduction
As a strength and conditioning coach, I have always collected and referenced
numerous tables, heuristics and guidelines (such as various rep max tables, Prilepin
table, exercise max ratios to name a few) that helped me create strength training
programs. Unfortunately, these were usually spread all over the place: numerous books
and papers, countless Excel sheets and PowerPoint presentations. Every time I wanted
to quickly find something to reference and possibly to compare, it was a major pain in
the arse finding it. So I decided to put them all together in one place, where I can easily
find them and use them, possibly have it at arms reach in the gym.
Thus, I decided to create this manual. But please note that this manual is not an
in-depth how-to book, but a simple collection of useful tables and heuristics that you
can use as a starting point when designing your strength training programs. Having
said this, it is important to quickly go through some of the rationale and warnings
before diving into the material. It is a bit philosophical, but please bear with me for the
next few pages.
Precision versus Significance
“As complexity rises, precise statements lose meaning and meaningful statements lose
precision” - Lofti Zadeh
The material in this manual is WRONG. It is not precise. It will vary, sometimes
a lot, between exercises, individuals, and genders (all 457 of them). This should be
expected since day-to-day motivation and readiness to train, improvement rates,
testing errors, among others, are not constant and predictable, but rather represent
sources of uncertainty, often experienced when working with athletes or dealing with
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STRENGTH TRAINING MANUAL Volume One
any kind of performance enhancement. It is therefore up to you to update it with the
information you possess and gain through training iterations. Figure 1.1 below depicts
perfectly the difference between precision and significance, and the aim of this manual.
Figure 1.1. Difference between precision and significance. Image modified
based on image in Fuzzy Logic Toolbox™ User’s Guide (MathWorks, 2019)
Generalizations, Priors,
and Bayesian updating
Not sure if there is anything else that pisses me off more than hearing someone
say: “You cannot generalize!”. Yeah right, I will approach every phenomenon in the
Universe as unique and genuine. Not sure we have the brain power for that - that’s why
we try to reduce the amount of information by generalizing. There is no science without
generalization. That’s why we have generalizations, laws, archetypes, stereotypes.
But smart people are not slaves to generalizations - they start with generalizations,
but quickly update them with new information to improve their insights. For example,
one can say that females are generally weaker than males (yeah, sexist generalization),
which means two things: (1) average female is weaker than the average male, and (2)
randomly selected female will be very likely to be weaker than randomly selected male
in the population. Of course, we also need to take into account how much weaker, but
without making this a statistic treatise about magnitudes of effects, one cannot claim
that all females are weaker than all males. Even if we start with this generalization before
working with a new female individual client or athlete and assume generalization is true
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MLADEN JOVANOVIĆ
and we apply it to this individual as well (let’s call this prior belief), we need to update
this prior belief with observations and experience while working with this individual,
who might be a future or current world class powerlifter (and probably stronger than
90% of males).
This means that we need to update our prior beliefs (e.g. generalizations, or
heuristics) with our own observations in the process called Bayesian updating to gain
insights which will educate our decision making.
Prior
Insight
Observa�ons
Figure 1.2. Bayesian updating, simplified
This manual is full of generalizations. Hence, you need to look at them as a
starting point, which you should update with your own observations, experience,
experimentations, and intuition. Just don’t be a dumbfuck and blindly believe and adopt
everything that has been written. Again, use it as a starting point (prior).
Large and Small Worlds
The real world is very complex and uncertain. To help in orienting ourselves in it,
we create maps and models. These are representations of reality, or representations of
the real world. In the outstanding statistics book “Statistical Rethinking” (McElreath,
2015), author uses an analogy, originally coined by Leonard Savage (Savage, 1972;
Binmore, 2011; Volz & Gigerenzer, 2012; Gigerenzer, Hertwig & Pachur, 2015a), that
differentiates between Large World and Small Worlds:
“The small world is the self-contained, logical world of the model. Within
the small world, all possibilities are nominated. There are no pure surprises, like
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STRENGTH TRAINING MANUAL Volume One
the existence of a huge continent between Europe and Asia. Within the small
world of the model, it is important to be able to verify the model’s logic, making
sure that it performs as expected under favorable assumptions. Bayesian
models have some advantages in this regard, as they have reasonable claims
to optimality: No alternative model could make better use of the information in
the data and support better decisions, assuming the small world is an accurate
description of the real world.
The large world is the broader context in which one deploys a model.
In the large world, there may be events that were not imagined in the small
world. Moreover, the model is always an incomplete representation of the
large world and so will make mistakes, even if all kinds of events have been
properly nominated. The logical consistency of a model in the small world is no
guarantee that it will be optimal in the large world. But it is certainly a warm
comfort.”1
Everything written in this manual represents Small Worlds - self-contained
models of assumptions about how things work or should work. Although they are all
wrong, some of them are useful2 (to quote George Box), especially as a starting point in
your orientation, experimentation, and deployment to the Large World. It is important
to remember the distinction between the two. I embrace the integrative pluralism
(Mitchell, 2002, 2012) in a way that there are multiple models (Page, 2018) that we
should use to explain, predict and plan intervention in the Large World.
Different prediction errors
and accompanying costs
Since all models are wrong, but some are useful, we need to make sure they don’t
come with harmful errors and potential costs. We can make different types of errors,
and they come at different costs. Let’s take a simplistic model of predicting 1RM (onerepetition maximum, or maximal weight one can lift with a proper technique):
Table 1.1 represents a common scenario for predicting 1RM. The top row contains
two TRUE values (150kg and 180kg) and on the side, we have two predictions. The
grey diagonal represents correct predictions, while red diagonal represents erroneous
predictions. Type I is undershooting (predicting 150kg when the real value is 180kg),
1 Excerpt taken from “Statistical Rethinking” (McElreath, 2015), page 19
2 “All models are wrong, but some are useful” is aphorism that is generally attributed to the statistician
George Box. Nassim Nicholas Taleb expanded this aphorism to “All models are wrong, many are useful,
some are deadly”
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MLADEN JOVANOVIĆ
and Type II is overshooting (predicting 180kg when the real value is 150kg). Does
making these two errors come with different costs if the predicted 1RM is implemented
into the training program? Hell yes!
150 kg
180 kg
150kg
Correct
Error I
(undershoo�ng)
180kg
Predicted 1RM
Real 1RM
Error II
(overshoo�ng)
Correct
Table 1.1. Different types of prediction error
It must be noted that undershooting a lot is still safer than overshooting a little.
This is because when you undershoot, you can still perform training sessions and
easily update, while if you overshoot, you will hit the wall quite quickly, and potentially
injure someone or create expectation stress and/or heavy soreness. Plus, in my own
experience, it is easier to ask for more from an athlete, than less. Furthermore, imagine
that your program calls for 3 sets of 5 reps with 100kg, and your athlete feels great and
performs 8 reps in the last set instead of the situation where your program calls for 3
sets of 5 with 110kg and the athlete struggles to finish it, or might even need to strip
the weights down. Performing better than it has been written in the training program
is always motivational (first situation), whereas the opposite can be very discouraging
(second situation). Collectively, this approach represents protection from the downside
(i.e. injury) which can further allow us to invest in the upside (i.e. strength training
adaptation). But more about this in the next chapter.
The problem is that we cannot get rid of errors - we can balance them out by
accepting higher Type I error while minimizing Type II error, or vice versa. In this
manual I accepted the fact that when making errors (and I do make them), I want them
to be Type I errors, or undershooting errors since they come up with much less cost that
can easily be fixed through few training iterations. Because of that, you might notice
that some percentages in this manual are quite low. Therefore, I suggest you take a
similar philosophy when deciding about percentages and every other guideline in this
manual: lean on the side of conservatism and safety first.
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STRENGTH TRAINING MANUAL Volume One
Classification, Categorization
and Fuzzy borders
As it is the case with generalization, classifications and categorizations (which
I consider synonyms here and use interchangeably) are aiming to reduce the number
of dimensions and numbers of particular phenomena at hand (with the aim of easier
orientation and action). This eventually means that items in one bracket or class might
differ, while items from different brackets or classes might be similar. Besides, there
are multiple approaches to classifying phenomena which might have different depths
or levels of precision (see Figure 1.3). To paraphrase Jordan B. Peterson: “Categories
are constructed in relationship to their functional significance”, meaning there are no
objective or unbiased approaches to categorization and classification, and they depend
on how we aim to use those categorizations3. For example, powerlifter might classify
strength training means, methods, qualities, and objectives differently than Olympic
weightlifter or a soccer player. This is because they experience different phenomena
and demand a different forum for action. But if you ask your average lab coat to perform
unbiased and objective classification, he or she will usually perform it as a place of things
type of classification.
Categorization is not an exercise in futility, but rather helps us make better
decisions (more educated and faster decisions via information reduction and
simplification). This simplification has some similarities with heuristics (fast and
frugal rules of thumb that help to avoid overfitting in a complex and uncertain world).
Hence, categories should have functional significance. In other words, you want to use
those categories somehow. Therefore, one should stop categorizing once there is no
functional significance.
That said, categories should be in the lowest possible “compression” (lowest
resolution) that still conveys enough pragmatic information. Since there are numerous
ways to categorize certain items (see Kant’s thing in itself4), the way we approach
categorization and what we see, depends on what we plan using it for (see Figure 1.3). I
might be wrong, but this reminds me of both phenomenology5 (things as they manifest
3 Also check essentialism versus nominalism, realism versus instrumentalism/constructivism and how
they are integrated with pragmatist-realist position (Borsboom, Mellenbergh & van Heerden, 2003;
Guyon, Falissard & Kop, 2017)
4 From Wikipedia (“Thing-in-itself,” 2019): “The thing-in-itself (German: Ding an sich) is a concept
introduced by Immanuel Kant. Things-in-themselves would be objects as they are, independent of
observation”
5 From Stanford Encyclopedia of Philosophy (Smith, 2018): “Literally, phenomenology is the study of
“phenomena”: appearances of things, or things as they appear in our experience, or the ways we experience
things, thus the meanings things have in our experience. Phenomenology studies conscious experience as
experienced from the subjective or first-person point of view.”
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MLADEN JOVANOVIĆ
to us) and pragmatism6 (practical application), although they are radically opposed
philosophical positions (together with analytic philosophy, which can be considered
your average lab coat objective and unbiased approach to classification). It is beyond
this manual (and my current knowledge) to discuss these topics, but in my opinion,
philosophy is very much alive, and it needs to be taken into account especially with the
recent rise of scientism7 in sport science and performance.
"Thing in itself"
Classifica�on 1
Classifica�on 2
Classifica�on 3
Classifica�on 4
Classifica�on 5
Figure 1.3. There is no bias-free, objective way to classify phenomena.
Classification depends on what you plan to use it for8
Place of Things vs Forum for Action
Classification thus serves a dual purpose: place of things and forum for action.
By term place of things, I refer to simply classify phenomena relative to some objective
criteria (this is usually physiological, anatomical or biomechanical criteria), or using
an analytical approach. On the other hand, the forum for action refers to a classification
based on how we intend to use these classes in planning, action, and intervening.
In this manual, I am leaning more toward forum for action approach in classifying
phenomena, mostly as strength and conditioning coach of team sports athletes, rather
than powerlifting or a weightlifting coach. This doesn’t mean that powerlifting and
weightlifting coaches cannot use this manual (at the end of the day, we have common
6 From Stanford Encyclopedia of Philosophy (Legg & Hookway, 2019): “Pragmatism is a philosophical
tradition that – very broadly – understands knowing the world as inseparable from agency within it.”
7 Belief or stance that all things can be reduced to science (Boudry & Pigliucci, 2017)
8 Thing-in-itself: "What do you see? Depends on what do you want to use it for". Modified based on the
image from Maps of Meaning 5: Story and Meta-story course by Jordan B. Peterson (Peterson, 2017)
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STRENGTH TRAINING MANUAL Volume One
physiology, anatomy, psychology, and experience shared phenomena in training), but
that they might classify things a bit differently because their forum for action differs
than the forum for action of the non-strength-sport athletes.
It is also important to mention that class membership is not a TRUE/FALSE state
(although it does simplify things a lot), but rather fuzzy (or continuous) membership.
For example, is split squat double leg or single leg movement? For simplicity (Small
World model) it is easier to assume it belongs only to one class or category, but in real
life (Large World) we know it is not that easy to make a hard border between classes
(thus, it can be 60% double leg, and 40% single leg, or what have you). One helpful
approach, that helps me at least in minimizing how much I break my own balls over
categorization, is to ask “How do I plan using this classification and for whom?”. Also,
remember that you do not need to be very precise, but rather meaningful and significant
in helping yourself orienting from the forum for action perspective (see Figure 1.1).
Qualities, Ontology, Phenomenology,
Complexity, Causality
Most, if not all, coaching education material regarding planning and periodization
comes with highly biased classification using objective physiological and biomechanical
approaches (place of things; analytical approach (Loland, 1992; Jovanovic, 2018)). These
fields have a monopoly on defining ontology9 (“What exists out there”) of qualities and
methods: maximal strength, explosive strength, VO2max, anaerobic capacity, you
name it. Some individuals tend to wave around with this scientific method, as something
objective and unbiased, but they are just value signaling, because they are using a
scientific approach, and you, the little dungeon dweller, are not. But unfortunately,
there is no objective or unbiased approach, and you, the dungeon dweller, might engage
phenomena classification as you experience it (phenomenology) and you should not be
embarrassed about your subjectivity. Yes, you should understand anatomy, physiology
and biomechanics, but they should not hold the monopoly over how you classify the
phenomena of importance to you. They are necessary, but not sufficient knowledge.
Since these fields define what is real (ontology), it is natural to follow up with
an approach that assumes these qualities as the building blocks of periodized training
9 From Wikipedia (“Ontology,” 2019): “Ontology is the philosophical study of being. More broadly, it
studies concepts that directly relate to being, in particular becoming, existence, reality, as well as the basic
categories of being and their relations. Traditionally listed as a part of the major branch of philosophy
known as metaphysics, ontology often deals with questions concerning what entities exist or may be said
to exist and how such entities may be grouped, related within a hierarchy, and subdivided according to
similarities and differences.”
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programs. Beyond this, we assume very simplistic causal models (Small World models
of what causes what), where we further assume there is some magic training method, or
intensity zone, that drives adaptation of the qualities we need to address. For example,
we might claim that reps >90% improve maximal strength and that reps with 65% done
fast improve explosiveness. This is bullshit. Even worse than this is the Load Velocity
curve with associated qualities and intensity zones.
Unfortunately, or luckily, things are not that simple. Yes, we can use these as
Small World models, representations and heuristics (which they are), rather than the
factual state of the world (ontology). First, different individuals will manifest different
phenomena and will demand different quality identification as a forum for action.
For example, what is holding back a world-class powerlifter in the bench press of
200kg might be lockout strength or bottom strength (and these are phenomenological
qualities). Thus, one might approach intervention with these qualities in mind. This
will not be the case for your average soccer player since his bench press performance is
not the ultimate goal, but rather one aspect of what we might consider important for
him (i.e. horizontal pressing). Biomechanically speaking, they are identical (place of
things), but phenomenologically, they are very much different, especially in defining
the qualities from the forum for action perspective and deciding about intervention to
improve them.
Methods
Repeated Effort
Method
Repeated Effort
Method
Max Effort
Method
Dynamic Effort
Method
(<65% 1RM)
(75-85% 1RM)
(>90% 1RM)
(50-60% 1RM)
Complexes,
WODs, Circuit
Training
Anatomic
Adapta�on
Hypertrophy
Maximal
Strength
Rate of Force
Development
Strength
Endurance
Quali�es
Figure 1.4. An overly simplistic causal model of methods and qualities
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STRENGTH TRAINING MANUAL Volume One
Second, assuming there is an associated training method or intensity zone that
magically hits identified quality is a pipe dream. The causal network is very complex and
at the end of the day, we do need to realize and accept the fact that we are experimenting
using a case-by-case approach. There are still useful priors we can rely on (e.g.
scientific studies, best practices, old school methods) as a starting point in our
experimentation and updating process, but at the end of the day, we are experimenting,
and following some Russian lab coat’s program is a warm comfort of certainty
assumptions.
Philosophical stance(s)
and influential persons
Someone more versed in philosophy than myself currently, can probably put
me in certain philosophical stance brackets (i.e. classify me). My current reasoning,
besides being complementarist10 is that of integrative pluralist (Mitchell, 2002, 2012),
pragmatist-realist (Maul, 2013; Guyon, Falissard & Kop, 2017) and phenomenologist.
I am highly influenced by works of Robert Pirsig and his Metaphysics of Quality11 (Pirsig,
1991, 2006), Jordan Peterson (Peterson, 1999; Peterson, Doidge & Van Sciver, 2018),
Nassim Taleb (Taleb, 2004, 2010, 2012, 2018), and Gerd Gigerenzer (Gigerenzer, 2015;
Gigerenzer, Hertwig & Pachur, 2015a). These philosophical stances and personas are
highly influential on my approach to training (and life in general) and that will be quite
visible in the chapters to come. For that reason, I find it important to pinpoint to the
sources. I do think, especially with the recent rise of scientism (Boudry & Pigliucci, 2017),
particularly in our domain of sport performance and science, that philosophy is more
than needed. This introductory chapter and the following on the Agile Periodization are
very much philosophical and are covering mine philosophical stances.
What is covered in this manual?
It was important to vent the above out before presenting the rest of the material.
I take the percent-based approach to strength training since I find it a great prior for
being implemented concurrently with any other approach (velocity based, RPE based
10 Complementary Training is the name of my blog (www.complementarytraining.net) that I started in
2010, with the aim of reconciling opposing concepts in training using the complementary approach (Kelso
& Engstrøm, 2008).
11 You will probably read the word Quality numerous times in this manual
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MLADEN JOVANOVIĆ
approach, open sets and so forth), and because it can give a ballpark of where weights
should be. When I was working with soccer athletes, I first tried to implement open
sets (only prescribing reps) and to teach them how to fish by allowing them to progress
and select weights themselves by keeping a training log (which was usually forgotten
or slipped under treadmill). This failed miserably, since they didn’t give many fucks
regarding strength training. They wanted to get it done and play rondo. Therefore, I
decided to calculate the weights and the number of repetitions they needed to lift. You
know - being a Hitler and master of puppets. However, after that, I realized how all
these formulas and tables differ for a given individual, exercise, on a daily basis.
I needed something that is prescriptive enough to avoid fuckarounditis (“Tell me
how much I need to be lifting” and to make sure progressive overload happens over
time), but also flexible enough to take into account errors and uncertainties, individual
differences, and rates of improvement. That is how this manual was born.
This manual starts with Chapter 2 on Agile Periodization (Jovanovic, 2018), which
provides a rough outline of the concept, particularly iterative planning component, and
how it is applied to strength training planning, objectives classification, and goals
setting. Chapter 3 discusses strength training movements classification, as well as the
ratios between their maximum (which can be quite useful in estimating max for novel
exercise, at least until one gains more observation regarding the exercise in question
and update this model). Chapter 4 discusses 1RM estimation (particularly estimation
through iteration idea), rep max tables and how they can be useful. Chapter 5 discusses
the planning of the strength training phase and set and rep schemes. Chapter 6 covers
the review and retrospective of the strength phase (which I titled Rinse and Repeat).
Appendix consists of multiple chapters including case studies, as well as full list of
exercises, the most important tables and all set and rep schemes discussed in the book.
As already stated, the objective of this strength training manual is not to go
into theoretical nitty-gritty details, but to provide all the useful tables, formulas and
heuristics at one place.
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STRENGTH TRAINING MANUAL Volume One
2 Agile Periodization and
Philosophy of Training
Agile Periodization is a planning framework that relies on decision making in
uncertainty, rather than ideology, physiological and biomechanical constructs, and
industrial age mechanistic approach to planning (Jovanovic, 2018). Contemporary
planning strategies are based on predictive responses and linear reductionist analysis,
which is ill-suited for dealing with the uncertain and complex domain, such as
human adaptation and performance (Kiely, 2009, 2010a,b, 2011, 2012, 2018; Loturco &
Nakamura, 2016). The word agile comes from IT domain, where they figured out that
industrial age approach to project management (i.e., waterfall) doesn’t work very well in
highly changing and unpredictable environment of the software industry and markets
(Rubin, 2012; Stellman & Greene, 2014; Sutherland, 2014; Layton & Ostermiller, 2017;
Layton & Morrow, 2018).
Iterative Planning
Iterative planning consists of iterative processes of (1) planning, (2) development,
and (3) review and retrospective. These can be applied on different time scales, and here
I selected three as well: (1) release, (2) phase, and (3) sprint (see Figure 2.1). Sprint can be
considered one microcycle, the phase can be considered mesocycle, and the release can be
regarded as one macrocycle, for those familiar with more contemporary periodization
terms (Bompa & Buzzichelli, 2015, 2019).
Why did I choose different names? To act smart? First of all, different frameworks
demand different language. Second of all, planning in this framework, as opposed in
contemporary planning strategies, is iterative rather than detailed up-front. Taking all
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MLADEN JOVANOVIĆ
of that into account, it is essential to use the terminology which will better represent
the iterative planning approach and differentiate it from more common planning
strategies as well.
Plan
Plan
Phase #1
Plan
Sprint #1
Review &
Retrospec�ve
Plan
Sprint #2
Review &
Retrospec�ve
Plan
Sprint #3
Review &
Retrospec�ve
Plan
Sprint #4
Review &
Retrospec�ve
Plan
Sprint #5
Review &
Retrospec�ve
Plan
Sprint #6
Review &
Retrospec�ve
Plan
Sprint #7
Review &
Retrospec�ve
Plan
Sprint #8
Review &
Retrospec�ve
Plan
Sprint #9
Review &
Retrospec�ve
Plan
Sprint #10
Review &
Retrospec�ve
Plan
Sprint #11
Review &
Retrospec�ve
Plan
Sprint #12
Review &
Retrospec�ve
Review &
Retrospec�ve
Plan
Release #1
Phase #2
Review &
Retrospec�ve
Plan
Phase #3
Review &
Retrospec�ve
Review &
Retrospec�ve
Figure 2.1. Iterative Planning consists of three time-frames: release, phase and sprint, each having a
planning component, development component, and review & retrospective component (which are
needed to update the knowledge for the next iteration)
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STRENGTH TRAINING MANUAL Volume One
Top-Down vs. Bottom-Up
These three time-frames are needed to implement both top-down and bottomup planning, which I consider to be complementary (Kelso & Engstrøm, 2008), rather
than dichotomous (see Figure 2.2).
Top Down
Release Planning
Phase Planning
Sprint Planning
Bo�om Up
Figure 2.2. Top-Down and Bottom-Up planning as a complementary pair.
Top-down refers to seeing the big picture, deciding about goals, objectives and
strategies and answering the question "What should be done and why".
Bottom-Up refers to starting with “what can be done now and how”. Bottom-up
begins with the problems at hand (e.g., equipment and facilities, level of athletes, and
so forth), rather than with a vision (which is the goal of the top-down approach). Sprint
planning is mostly concerned with figuring out what can be done and how (within
constraints of the bigger picture established with release and phase plan). To utilize
bottom-up approach, one needs to embrace the concept of MVP, or minimum-viable
program12, which is the least complicated training program that serves one as a vehicle,
while one discovers what can and should be done and how.
12 The original idea comes from Lean Startup book (Ries, 2011) where MVP stands for Minimum Viable
Product
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MLADEN JOVANOVIĆ
An essential concept of MVP is that all qualities identified as important (from
the lowest resolution, or from functional significance perspective) are being addressed.
For example, making sure there is some speed/sprint work, quality strides, jumps, lifts
(major movement patterns being addressed) trumps worrying about chest flies, rear
deltoideus work or whether Nordic curls are better than RDLs. MVP is the epitome of
precision vs. significance conundrum (see Figure 1.1).
It is a myth, that when someone starts working with a team, they will immediately
know the objectives and what should be done (top-down approach) to improve
performance. That is bullshit. You need to figure out what you are dealing with first,
figuring out the problems before deciding about vision and long-term phases. Here is
the example: imagine starting to work with a soccer team and approaching planning
from these two perspectives:
Top-Down: The vision is that we need strong, fast, fit and healthy athletes.
We will start with whatever the fucking phase-potentiation/periodization
framework is modern nowadays. For example, start with the anatomical
adaptation phase, followed by max strength phase, followed by power and
then finally maintenance. This is of course planned before actually seeing
the athlete and the facilities. Why? Because if you don’t, you don’t have a
long-term plan and are clueless as a coach. And because Russian textbooks
say so.
Bottom-Up: I have 3 dumbbells, athletes who never lifted in their life, and
a head coach who doesn’t believe in physical preparation for soccer. What
am I supposed to do to get the MVP, build the trust with athletes, coaches,
and board, and go from there?
I am not saying that the top-down approach is not important, but since it has
been overemphasized in the contemporary planning and periodization literature,
while still missing to address issues from where the rubber meets the road, I believe that
what we need to do is to emphasize bottom-up approach more, to reach some type of
balance in the planning universe (pun intended). I also believe that both are important
and complementary, because if the only type of planning you do is bottom-up, how
you are going to judge the results without bigger picture, objectives, and vision. This is
the reason why both top-down and bottom-up approaches are implemented in Agile
Periodization using three components: release, phase, and sprint (see Figure 2.2).
Within each of these components (release, phase, sprint), there are three
distinctive and formal parts: (1) plan, (2) development, and (3) review and retrospective.
Let's see how this can be applied to strength training.
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STRENGTH TRAINING MANUAL Volume One
Phases of strength training planning
Strength training planning can be seen as consisting of three iterative
components:
1. Establish EDM (every-day maximum)
2. Plan the training phase
3. Rinse and repeat
Each of these phases will be covered in more details in following chapters
(Chapters 4-6), but it is essential to see how they correspond to the iterative nature of
sprint and phase components of the Agile Periodization (see Figure 2.3)
1 Establish EDM
2 Plan the Training Phase
Horizontal Planning
One Phase
(block)
Ver�cal Planning
Monday
Tuesday Wednesday Thursday
Friday
Workou A1 Workout B1
Workout C1 Workout D1
Saturday
Sunday
Next vertical planning stage
Monday
Tuesday Wednesday Thursday
Friday
Workou A2 Workout B2
Workout C2 Workout D2
Saturday
Sunday
Next vertical planning stage
Monday
Tuesday Wednesday Thursday
Friday
Workou A3 Workout B3
Workout C3 Workout D3
Saturday
Sunday
Next vertical planning stage
Monday
Tuesday Wednesday Thursday
Friday
Workou A4 Workout B4
Workout C4 Workout D4
Saturday
Sunday
One Sprint
(microcycle)
3 Rinse and Repeat
Figure 2.3. Three iterative components of strength training planning
In my view, these three components are building blocks of the bottom-up
approach, and this whole manual revolves around these three. I do believe that
these shorter iterative programs are needed to course correct and adapt to the newly
discovered observations and insights (see Bayesian updating in the previous chapter)
compared to longer top-down phases.
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Qualities, Methods, and Objectives
Coaches (luckily not all of them) often use the following mental model (Small
World; see previous chapter) that is dominated by physiology and biomechanics
reductionist approach (Figure 2.4):
Methods
Repeated Effort
Method
Repeated Effort
Method
Max Effort
Method
Dynamic Effort
Method
(<65% 1RM)
(75-85% 1RM)
(>90% 1RM)
(50-60% 1RM)
Complexes,
WODs, Circuit
Training
Anatomic
Adapta�on
Hypertrophy
Maximal
Strength
Rate of Force
Development
Strength
Endurance
Quali�es
Figure 2.4. An overly simplistic analytic causal model of methods and qualities
Since physiology and biomechanics define the place of things, we also automatically
assume that we know what to do with it (the forum for action). However, there are a few
issues with this. Firstly, qualities identified are usually related to some physiological
model of performance (for example in endurance we have VO2max, Lactate Threshold
and Economy as main qualities), or latent variables or constructs13. Secondly, we
immediately assume that once we identify those qualities, there are training methods
that can directly hit those qualities (sometimes we also refer to “training zones” or
“zones of intensity”). Unfortunately, this is a flawed model. The more realistic model
is the following (see Figure 2.5)
13 These latent variables or constructs are usually referred to as bio-motor qualities (e.g., strength, speed,
power, endurance, flexibility). From a realist perspective they represent real ontological qualities (i.e., they
are the cause for the observed variable, i.e., strength as a quality cause your manifested performance in
the bench press or a squat). Instrumentalist or constructionist perspective assumes that latent variables
represent just a numerical construct that helps in explaining manifested observations (i.e., manifested
performance in the bench press and squat can be correlated because you have strength trained) (Borsboom,
Mellenbergh & van Heerden, 2003; Borsboom, 2008; Maul, 2013). More about these topics will be covered
later in the chapter.
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STRENGTH TRAINING MANUAL Volume One
Methods
Repeated Effort
Method
Repeated Effort
Method
Max Effort
Method
Dynamic Effort
Method
(<65% 1RM)
(75-85% 1RM)
(>90% 1RM)
(50-60% 1RM)
Complexes,
WODs, Circuit
Training
Anatomic
Adapta�on
Hypertrophy
Maximal
Strength
Rate of Force
Development
Strength
Endurance
Quali�es
Figure 2.5. More realistic model, where there is no clear cut between Qualities and Methods
As mentioned in the previous chapter, rather than relying solely on physiology
and biomechanics to define what there is (although, I am by no means underestimating
the importance of knowing these disciplines and analytical approach) and what should
we do with/about it, I want to take more phenomenological (and pragmatic) approach in
this manual.
How does this relate to strength training? We tend to define objectives and
methods of strength training using the analytical approach of biomechanics and
physiology (Jovanović, 2008a,b,c; Jovanovic, 2017a,b):
1. Maximal and Relative Strength
- The goal is the development of maximal strength
- The method used for developing this motor quality is Maximal Effort, or ME
2. Explosive Strength
- The goal is the development of explosive strength, or the ability to produce
great force in the least amount of time
- The method used for developing this motor quality is Dynamic Effort or DE
3. Muscular Hypertrophy
- The goal is the development of muscular hypertrophy, without going into the
debate of sarcoplasmic vs. myofibrillar hypertrophy
- The method used for developing this motor quality is Submaximal Effort, or
SE (mostly for functional or myofibrillar hypertrophy) and Repetition Effort, or
RE (primarily for total or sarcoplasmic hypertrophy)
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4. Muscular Endurance
- The goal is the development of muscular endurance, fat loss, anatomic
adaptation and sarcoplasmic hypertrophy (depending on the context). Some
also put ’vascularization’, ’glycogen depletion’, ’mitochondria development’
as the goal of this method
- The method used for developing this motor quality is Repetition Effort or RE
So, we believe, that for example, if one wants to improve max strength, one needs
to use >85-90% 1RM loads. But then we have athletes coached by Boris Sheiko (Sheiko,
2018) who usually lift weights lower than 80% 1RM and are some of the strongest in the
world. So, these categories create paradoxes because they make us falsely confident in
the involved processes leading to a specific goal, but unfortunately, we are dealing with
complex systems and uncertainties.
What is the solution? In my opinion, the answer is using complementary
phenomenological objectives. Phenomenological approach defines qualities as they
manifest themselves in our experience or performance (Loland, 1992; Jovanovic, 2018).
For example, powerlifter in the competition struggles to lift his opener (first weight),
and that sets him up poorly for the other tries. From the analytical (i.e., biomechanical
and physiological) standpoint, one can dissect this to rate of force development, fast
twitch synchronization, or whatever I-want-to-sound-smart constructs. But from the
phenomenological perspective, one struggled to find the right mindset and use the suit
in the right way. Defining qualities like this gives more meaning and create affordances14
for action (something that is lacking in analytical approach - see Is/Ought problem later).
Another example might be an endurance runner (not the best example in Strength
Training manual right but bear with me for a second)15. This endurance runner’s result in
1500m competition is 3 minutes and 56 seconds. His VO2max is 68 ml/kg/min. And how
the hell does this help in figuring out the forum for action? What should he do to improve?
Phenomenologically, we might notice that he lost the pace in the last lap by losing his
rhythm. And this gives us more affordances for action - in other words, the forum for
action. The coach can make better prescription based on the phenomenological analysis.
So, rather than prescribing VO2max intervals (that sounds ‘scientific’ and ‘objective’),
she might make this athlete focus on his speed and pace after a long run. Could he be
a high-level 1500m without high VO2max? Or without elastic force generating ability?
Hell no! To put this in philosophical terms, high VO2max is a necessary condition to
be a high level 1500m runner, but it is not sufficient. Thus, one cannot make simplistic
14 Affordances are what the environment offers the individual (“Affordance,” 2019). Also see (Davids,
Button & Bennett, 2008; Renshaw, Davids & Savelsbergh, 2012; Gibson, 2014; Chow et al., 2016)
15 Outstanding book on endurance training, as well as the critique of the simplistic analytical models is
Science of Running by Steve Magness, which I highly recommend checking (Magness, 2014)
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STRENGTH TRAINING MANUAL Volume One
causal reasoning that one needs to perform VO2max intervals (e.g., 4x3min @105%
MAS or vVO2max), to improve VO2max, which will improve 1500m performance. The
causal network is very complex and unpredictable, which doesn’t mean understanding
physiology is unnecessary, but understanding it is not sufficient when it comes to
enhancing athletes’ performance.
Similar problems are experienced in other domains, for example, psychometry,
with the concepts of IQ, g-factor and Big Five factors of personality (Borkenau &
Ostendorf, 1998; Molenaar, Huizenga & Nesselroade, 2003; Borsboom, Mellenbergh &
van Heerden, 2003; Molenaar, 2004; Hamaker, Dolan & Molenaar, 2005; Borsboom,
2008; Molenaar & Campbell, 2009; Cramer et al., 2012; Borsboom & Cramer, 2013;
Schmittmann et al., 2013; Bringmann et al., 2013; Maul, 2013; Nesselroade & Molenaar,
2016; Borsboom et al., 2016; Guyon, Falissard & Kop, 2017; Kovacs & Conway, 2019). If
you are interested in this topic, I suggest you check the provided references. The key
takeaway is that causation is not as simple as Figure 2.4.
When it comes to strength training, using analytical perspective, strength
qualities are (1) maximal strength, (2) explosive strength, (3) strength endurance, and (4)
hypertrophy. The question is how do they differ and manifest themselves in powerlifter
versus soccer player? How do they differentiate into finer qualities? In my opinion, the
scientific analytical approach needs to be complemented (sometimes even replaced, or
started at least) with a phenomenological analysis of the qualities and methods. We do
need to understand that we are dealing with uncertainty and complexity, and pluralistic
approach of using multiple Small World models is needed, rather than ideological belief
in only one model (Mitchell, 2002, 2012; Page, 2018). This means that all pre-planning
serves only as a prior (see previous chapter on Bayesian updating) which needs to be
updated and experimented with, using the iterative approach of Agile Periodization.
Following long-term periodization phases of the Russians gives us a false sense of
certainty and comfort, but at the end of the day, we are experimenting.
It is important to realize that from the phenomenological perspective, qualities
have a hierarchy. The higher the level of the athlete, the more one needs to dig deeper
and with a finer resolution to figure out rate limiters that need to be addressed. This is
the difference between specialist (e.g., powerlifter) versus generalist (e.g., soccer player)
and their approach to strength training. From an analytical perspective, in my opinion,
this finer differentiation is missing. They both need maximum strength, hypertrophy,
and the rate of force development. But they have different phenomenological qualities
that are required, and hence training will be different.
To wrap up this philosophical treatise on qualities, please consider the gross
phenomenological strength qualities defined by coach and legend Dan John (John,
2017):
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ANACONDA STRENGTH
I love using goofy names to explain concepts to athletes. Anaconda strength is
the internal pressure we must exert to hold ourselves steady against the forces
of the environment or an implement. A highland game athlete tossing a caber
is fighting forces in every direction, yet maintaining his or her body as “one
piece.” Anaconda strength is the body squeezing and the inner tube of the body
pushing back to keep integrity.
ARMOR BUILDING
This is the kind of training that fighters, football teams, and rugby athletes
already understand. Armor building is the development of calluses or body armor
to withstand the contact and collisions with other people and the environment.
ARROW
This is the concept of learning how to turn yourself into stone. In football, this
the contact in tackling and blocking; in throwing, it is the block to put the energy
into the implement.
This might seem very similar to (1) Maximal Strength (Anaconda Strength), (2)
Hypotrophy (Armor Building) and (3) Explosive Strength (Arrow), and it actually is
similar, but it is defined more from the phenomenological perspective, and as such, it
will make more sense to the average soccer player or the head coach, because they think
and understand “phenomena” rather than scientific abstractions (“Yeah, this method
will increase your intra-muscular fast twitch coding, which should transfer to you being
more explosive on the pitch”, versus “This will make him ‘snap’ out of defender’s reach, like
shot from the sling”)
Anaconda Strength
Armor Building
Arrow
Vanilla Training
Mongoose Persistence
Figure 2.6. “Phenomenological” classification of strength training objectives
We can see that these objectives are very meaningful, but not very precise (see
Figure 1.1). Although I might use these objectives when categorizing set and reps
schemes, I am by no means forcing anyone to use these types of classifications - use
whatever is meaningful and actionable to you. Having said that, I might still use different
categorization when defining set and rep scheme (i.e., general strength schemes,
maximal strength schemes, hypertrophy schemes and so forth). In my view, Dan John’s
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STRENGTH TRAINING MANUAL Volume One
objectives give us the lowest resolution categories that can guide our decision making
while using the coaches’ language.
Two additional categories that I added to Dan John’s model are (1) Mongoose
Persistence, which is your usual MetCon, Strength Endurance, and Explosive Endurance
or any other dangerous definition you might use, and (2) Vanilla Training.
Mongoose Persistence represents the ability to prolong work, to reduce rest
between burst of strength and explosive power feats and so forth. Why “Mongoose
Persistence”? Because mongoose fight snakes, and we already have “Anaconda
Strength” in there. When it comes to team sports, I am not very convinced this should be
viable strength training objective, but it can certainly have some importance, although
small (i.e., core circuits, off-legs conditioning for the injured, and so forth).
Vanilla Training refers to your average low intensity, control, stabilizing, prehab,
Pilates type of work. If you ask Dan Baker, that is around 90% of my training time (he
saw me training a few times).
Since this manual promotes multi-model thinking (pluralism), there might be
multiple categorizations that have functional significance for you in your own context.
One does not need to use analytical-’unbiased’-’objective’ scientific approach to
objectives categorization, but one certainly needs to understand those disciplines
(necessary versus sufficient discussion). You certainly are not the useless piece of shit if
you are not using scientific analytic approach, and I want to empower you to build your
own categorization based on your functional significance and phenomenology.
Taking a phenomenological stance, anaconda strength, armor building, vanilla
training, mongoose persistence, and arrow are very potent as a forum for action when it
comes to strength training for team sports athletes. Powerlifters and other strengthbased athletes might need more resolution in the categorization because they have
different phenomena they need to wrestle with. Dan John’s categorization of objectives
is more than enough for team sport and other non-strength athletes (i.e., strength
generalists).
Dan John's Four Training Quadrants
It is very easy to get lost in the number and level of qualities that one might need
to develop. One quite handy model that helps in orientation is Dan John’s model of four
training quadrants (John, 2013) that is based on two continuums:
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MLADEN JOVANOVIĆ
1. The number of qualities an athlete must have to excel at a sport, and
2. How good the athlete needs to be at each of those qualities relative to how good any
athlete can be at that quality
For the sake of simplicity, these two continua are split in two (high and low),
which results in a quadrant (see Figure 2.7).
Understanding where you belong is quite handy to avoid getting lost. Quadrant
I represent physical education. Kids need to learn and acquire a bunch of low-level
qualities.
Team sports athletes, combat sports athletes, and some occupations belong to
Quadrant II, where lots of high-level qualities are needed. Recreative athletes usually
believe they belong to this quadrant, but that is a false belief.
Quadrant III is pretty much everyone. In quadrant III, athletes or recreational
athletes need few qualities at the low level (e.g., being mobile, not break one’s bones
when falling off the chair, minimal aerobic endurance).
Quadrant IV is your specialist - few qualities at the highest level. These are
powerlifters, Olympic weightlifters, sprinters and so forth.
Low Level Of Quali�es
High Level Of Quali�es
Low Number Of Quali�es
Who
Specialists, like powerli�ers,
track and field athletes,
Characteris�cs
Few quali�es at the
highest level
Who
Most people
Characteris�cs
Few quali�es, at low level
High Number Of Quali�es
Who
Team sports, combat sports,
few occupa�ons
Characteris�cs
Lots of high-level
quali�es
Who
Kids, physical
educa�on
Characteris�cs
Lots of low-level quali�es
Figure 2.7. Dan John four training quadrants. Image created based on the
infographic available at the On Target Publication website (John, 2015).
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STRENGTH TRAINING MANUAL Volume One
Quadrants model is quite useful in figuring out where you belong, and how your
training should be structured. The material in this manual can be applied to all four
quadrants since it provides a decision-making framework that can be implemented
together with Dan John quadrants. For more information about four quadrants, I highly
suggest reading Dan John material.
Goals Setting and Decision Making
(in Complexity and Uncertainty)
Ah, the goals setting. If you are not setting goals, you are an utter piece of clueless
shit that is aiming nowhere, right? Well, let me start by quoting Scott Adams from “How
to Fail at Almost Everything and Still Win Big” (Adams, 2014):
“To put it bluntly, goals are for losers. That’s literally true most of the
time. For example, if your goal is to lose ten pounds, you will spend every
moment until you reach the goal—if you reach it at all—feeling as if you were
short of your goal. In other words, goal-oriented people exist in a state of nearly
continuous failure that they hope will be temporary. That feeling wears on you.
In time, it becomes heavy and uncomfortable. It might even drive you out of the
game.”
“The system-versus-goals model can be applied to most human
endeavors. In the world of dieting, losing twenty pounds is a goal, but eating
right is a system. In the exercise realm, running a marathon in under four hours
is a goal, but exercising daily is a system. In business, making a million dollars
is a goal, but being a serial entrepreneur is a system.”
Another quote, from Jason Fried’s “It Doesn’t Have to Be Crazy at Work” (Fried
& Hansson, 2018):
“So imagine the response when we tell people that we don’t do goals.
At all. No customer-count goals, no sales goals, no retention goals, no revenue
goals, no specific profitability goals (other than to be profitable). Seriously.
This anti-goal mindset definitely makes Basecamp an outcast in the
business world. Part of the minority, the ones who simply “don’t get how it
works.”
We get how it works—we just don’t care. We don’t mind leaving some
money on the table and we don’t need to squeeze every drop out of the lemon.
Those final drops usually taste sour, anyway.
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Are we interested in increasing profits? Yes. Revenues? Yes. Being more
effective? Yes. Making our products easier, faster, and more useful? Yes. Making
our customers and employees happier? Yes, absolutely. Do we love iterating
and improving? Yup!
Do we want to make things better? All the time. But do we want to
maximize “better” through constantly chasing goals? No thanks.
That’s why we don’t have goals at Basecamp. We didn’t when we started,
and now, nearly 20 years later, we still don’t. We simply do the best work we
can on a daily basis.”
Charles Munger says the following on the value of long-term plans (quote from
“Seeking Wisdom” by Peter Bevelin (Bevelin, 2013)):
We have very much the philosophy of building our enterprise that Sir
William Osler had when he built the John Hopkins Medical School from a very
poor start into a model medical school for the whole world. And what Sir William
Osler said - and he quoted this from Carlyle - was: “The task of man is not to
see what lies dimly in the distance, but to do what lies clearly at hand.”
We try to respond intelligently each day, each week, each month, each
year to the information and challenges at hand - horrible assaults that have to
be deflected, things that have to be scrambled out of, the unusual opportunities
that come along - and just do the best job we can in responding to those
challenges. Obviously, you look ahead as far as you can. But that’s not very far.
But if you respond intelligently and diligently to the challenges before you, we
think you’ll tend to end up with a pretty good institution
Scott Adams is talking about goals versus systems, which is quite similar to the
classification of goal setting we tend to use in performance domain:
Outcome goals - For example, getting a medal on the Olympic Games is an
outcome goal
Performance goals - Improving your bench press 1RM for 5kg is a
performance goal
Process goals - Making sure you train bench press three times a week,
with a total of 50 reps over 75% 1RM is a process goal.
I am not that extreme as Scott Adams and Jason Fried, but I get their messages,
which is quite stoical: control what you can, and what is really important. And the only
things we can control are the process goals (sometimes not even them, at least not to
the degree we hope to). Figure 2.8 explains it perfectly:
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STRENGTH TRAINING MANUAL Volume One
Figure 2.8. Perfect depiction of Stoic philosophy of focusing on things you can control, and which are
important. Image modified based on Carl Richards sketches at Behavior Gap (Richards, 2017) .
But we do need some direction and understanding qualities and objectives as
priors (see previous chapter) is an important starting point. But it is a myth that one
immediately knows what the goals and objectives are - most of the time we do need
to discover them (and update them) through action and intervention using MVP
(minimum viable programs). John Kay, in his book “Obliquity” (Kay, 2012), makes a
distinction between direct and oblique approaches to decisions and problem-solving,
which I believe are more than related to planning strength training (see Table 2.1).
Objectives and goals
The Direct Approach
The Oblique Approach
High-level objectives are defined,
clear and can be quantified
High-level objectives are loosely defined
and multi-dimensional
There is a clear distinction between
high-level goals and the states
and actions that make their
achievements possible
There is no clear distinction between
objectives, goals, states and actions.
We learn about the nature of high-level
objectives by creating the states and
performing the actions that contribute to
their achievement
Interactions
Interactions with others are limited The outcomes of interactions with
others depend not just on the actions we
and their responses depend on the
perform, but also on the social context in
actions we take
which our actions are performed and on
other’s implementation of them
Complexity
The structure of the relationships
among objectives, states, goals and
actions is understood
Knowledge of the structure of
relationships among goals, states and
actions is imperfect and acquired as the
process goes on
(continued on the next page)
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(continued from the previous page)
The Direct Approach
The range of options is fixed and
Problems are
known
incomplete and
uncertainty widespread
The Oblique Approach
Only a limited number of options are
identified or perceived as available.
In defining objectives, closure means
deciding what to bring in and what to
leave out
Risk in the environment can be
described probabilistically
The environment is the uncertain. Not
only do we not know what will happen,
but we do not know the range of events
that might happen
Abstraction
The problem can be well described
by a single analytic model
Appropriate simplification of a complex
problems depends on judgement and
knowledge of context
Summary
- Objectives are clear
- Systems are comprehensible
- We know the available options
- What happens happens because
someone intended it
- Rules can define the system
- Direction provides order
- Good decisions are the product of
good processes
- We learn about our objectives as we
strive for them
- Systems are complex and depend on
unpredictable reactions
- We can consider only a few possibilities
- There is no clear link between intention
and outcome
- Expertise is required, tacit knowledge is
essential
- Order often emerges and is achieved
spontaneously
- Good decisions are the product of good
judgment
Table 2.1. Characteristics of direct and oblique approaches to decisions and problem-solving.
Based on work by John Kay (Kay, 2010, 2012).
I believe that the direct approach is equal to the top-down approach, and the
oblique approach is equal to the bottom-up approach of planning. Contemporary
planning strategies (and periodization books) assume predictability of the system,
using the analytical approach in defining the qualities and objectives, and top-down
(direct) approach to planning. This is highly influenced by the industrial age approach
to management (Kiely, 2009, 2012, 2018; Jovanovic, 2018), but it just doesn’t work in
the complex domain such as training athletes. Agile Periodization takes another route:
oblique or bottom-up. This is because most of the time we do not know the objectives
right off the bat and we have no clue how things will emerge over time. But this is not
to say that aimlessly experimenting is the goal or method of Agile Periodization. Au
contraire - we do need directions that are set with the phase and release planning
process. Figure 2.9 depicts the big picture of goal settings and decision making in the
Agile Periodization framework:
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STRENGTH TRAINING MANUAL Volume One
Top Down
Phase Planning
Performance Goals
Sprint Planning
Process Goals
OKRs
Oblique
Direct
Vision
Oblique
Outcome Goals
Direct
Release Planning
MVP
Bo�om Up
Figure 2.9. How everything fits together in the Agile Periodization framework
OKRs
OKRs stand for Objectives and Key Results and are now currently hot-topic goal
setting framework in the IT industry since this approach provides transparency and
alignment in teams implementing Agile Project management (Wodtke, 2015; Doerr,
2018). In simple terms, OKRs represent the following:
I will ________ as measured by ____________.
I will (Objective) as measured by (this set of Key Results).
I do believe that OKRs system can span both Outcome and Performance goals (“I
will win the powerlifting competition by improving my total for 15kg”) and Performance
and Process goals (“I will improve my bench press by accumulating 50 reps >75% 1RM
in a week”).
OKRs is extremely useful goal setting framework and I urge you to check the
following references for more details (Wodtke, 2015; Doerr, 2018).
My only issue with OKRs is that they also lean more towards direct or top-down
approach, since you do need to know what the goals/objectives are, to define key results
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(besides how do I know that accumulating 50 reps >75% 1RM in a week will increase
one’s performance goals?), but luckily OKRs are Agile and iterative which allows
them quick updates based on discovery across sprints and phases. For example, one
might figure out that the easiest way to reach an outcome and performance goal (e.g.
increasing total) is not through improving one’s bench press, squat, and deadlift, but
by decreasing bodyweight and entering lower weight division. It is hence important to
make OKRs oblique as well.
Designing MVP
MVP stands for minimum viable program. MVP is the program that is simple
enough to hit all (or most of) the a priori identified important qualities (in the lowest
resolution; see previous chapter, and 1/N heuristic later), and flexible enough to be
adaptable to newly discovered objectives and goals (Ries, 2011; Jovanovic, 2018). Hence
it serves as a vehicle for discovery while still being robust enough to work in different
scenarios and uncertainties by providing a minimum viable performance of the athletes.
Figure 2.10 contains a simplified example of what MVP is for a powerlifter:
Walkout
Walkout
Squat
Strength in the hole
Deadli�
Strength in the hole
Walkout
Squat
Strength in the hole
Explosivness
Explosivness
Explosivness
Grip strength
Grip strength
Grip strength
Strength in the hole
Bench Press
Squat
Deadli�
Strength in the hole
Deadli�
Strength in the hole
Finish
Finish
Finish
Structure at the bo�om
Structure at the bo�om
Structure at the bo�om
Explosivness off the chest
Bench Press
Lockout
Not this!
Explosivness off the chest
Bench Press
Explosivness off the chest
Lockout
Lockout
Nor this!
THIS - MVP!
Figure 2.10. MVP is making sure that all the major qualities are being addressed
at the functional significance level (lowest resolution). Later on, as one discovers,
more precise plan and a program can be created
Is/Ought Gap and Hero’s Journey
Just because we have set the objectives and are aware of the current state (place
of things), we do not know how to act (the forum for action) (Jovanovic, 2018). I call this
the is/ought gap (see Figure 2.11):
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STRENGTH TRAINING MANUAL Volume One
IS
OUGHT
Figure 2.11. Is/Ought Gap
Just because we know one 1RMs, EMG activities, rate limiters, phenomenological
qualities and what have you, we still lack the idea of how to act. What should be done?
Most of our ideas of how to act come from the previous experiences, best
practices, scientific journal, ideologies and so forth (let’s call this the known), which can
be considered a prior when setting up an experiment (training phase) for an individual
or a group of people. But how they will respond, is completely unpredictable. Of course,
we know that lifting weights will make one stronger (the known), but we cannot predict
one’s response (we can predict the direction of the response, but not exact quantity).
We have an idea where certain things might take us (from group-based and averagebased approaches as used in the scientific studies and from those walking the path
before us – representing the collective known), but we do not know how it will work for
a particular individual at particular time and place. This is even more of a problem when
one is breaking a personal record, and especially when one is trying to breach the world
record performance. It is the unknown, the Chaos.
This can be seen as archetypal Hero’s journey myth (Campbell, Moyers & Flowers,
1991; Peterson, 1999; Campbell, 2008; Neumann, 2014; Farrow, 2017, 2018). Individual
needs to step from the known (Order) to the unknown (Chaos) to bring something useful
back (you can call this to step out of his comfort zone). If I am a rookie, improving my
personal bench press from 70kg to 80kg, will demand me getting to the unknown (“What
is that thing you call lifting weights? Oh fuck, I am sore!”) and bringing back something
useful for me personally (performance gains). Many have done this before me, so I
can use this knowledge to gain direction and orientation (collective known, prior and
Bayesian updating - see previous chapter). When I detrain, and start training again, I
have an idea of the terrain and what it takes (unless I get older by 20 years and gain a
shitload of weight, then the terrain is different) so it will be a bit easier. If I am elite, at
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the brink of the world record, then - shit, I am alone! I am entering into the unknown,
not only for myself but for collective performance as well (assuming no one has done it
before). Phenomenologically, this is the archetypal story of the Hero’s journey.
I am a bit sick of seeing Hans Selye theory of adaptation and supercompensation
(Kiely, 2016; Cunanan et al., 2018) in training books, so this is an alternative
phenomenological explanation: one needs to step into Chaos (somewhere you
personally haven’t been before, at least, not in the recent times, or when no one has
ever been before) to bring something useful back (Figure 2.12). And this is not only
related to physiology. That’s why it is a meta-story. In the known domain, the path is
broadly predictable on a population-wide basis whereas, at the individual level, it is
not. In other words, known and unknown are different for the individual vs. collective
in general.
What should be:
What should be:
The ideal future
The ideal future
What is:
The unbearable present
What is:
The unbearable present
Figure 2.12. Training as Normal Story and Revolutionary Story (Regeneration of Stability from the
Domain of Chaos). Modified based on Jordan B. Peterson work (Peterson, 1999)
Before you start to question my sanity, I firmly believe it was important to
introduce these archetypal meta-stories as the explanation of your journey through
strength training. From the phenomenological perspective, it can be portrayed as
such, and I think it can infer more forum for action, than analytical physiological/
biomechanical place of things approach. Long story short, you are a hero, embracing a
journey into the unknown, to bring something useful back and enlarge the known circle
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STRENGTH TRAINING MANUAL Volume One
(which can be considered performance potential). The path of those before you can give
you some direction, not exact scripts (see Figure 1.1, priors and Bayesian updating in
previous chapter). Which brings me to evidence-based practices
Evidence-based mumbo jumbo
Waving evidence-based flag is a simple virtue signaling for the lost lab coats.
Citing and referencing studies and meta-studies done on grade motivated studentathletes while bitching on the old school as something terrible, and you unscientific
practitioner, with the aim of providing evidence for the intervention, is a fragilista and
intellectual-yet-idiot (to use Nassim Taleb’s terminology (Taleb, 2004, 2010, 2012,
2018)) wet dream.
In my opinion, these sources of knowledge represent only one aspect of prior
information (from the known domain, see Figure 2.12) we can use to start experimenting
with. I have represented this in Figure 2.13
Figure 2.13 represent more complex Figure 1.2 on Bayesian updating. I have tried to
combine the famous Deming PDCA (plan-do-check-adjust) (“PDCA,” 2019) loop with
the iterative aspect of updating prior information with the experiment (intervention). Is/
Ought gap represents the embedded and inescapable uncertainty of how interventions
will work. This is especially the case in a complex domain such as human performance
and adaptation. Equally to evidence-based (using scientific studies and meta-analysis),
the data-driven approach should be treated as only one source of prior information in
decision making and should probably change the name to ‘data-informed’. These two
are not fail-safe, predictable, certainty strategies - they are necessary to be considered,
but far from sufficient in guarantying wanted outcomes. It is the same story with preplanned periodization schemes - if those fancy blocks seem to be working, then most
if not all athletes would reach personal best, or at least seasonal best, at the major
competition. Yet, that number is not very optimistic (Loturco & Nakamura, 2016). Well,
if performance goals are tough to reach in individual sports, then team sports are even
more notorious, uncertain and unpredictable. So, just because you are using ‘evidencebased’, ‘data-driven’ or ‘Eastern European periodization’ approaches, at the end of the
day, you are still experimenting and gambling against unpredictable complex systems
and environments. They do provide warm comfort though. If put at the right place, these
strategies represent one source of prior knowledge, that needs to be updated through
iterations and experimentation. This is the idea that Agile Periodization embraces and
focus on wholeheartedly.
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PLAN
DO
Best prac�ces &
tradi�on
CHECK
Uncertainty
(randomness, noise, error)
Scien�fic literature
Opinion and wisdom
of the crowds
Heuris�cs & models
OUGHT
Experiment
Observa�ons
Randomiza�on
Barbell strategy
MVP
Current state &
context
Priors
Pseudoscience, noise
& ideology
IS
Plan
Intui�on
Preferences
Itera�ons
Objec�ves
Previous
experimenta�on
Insights
ADJUST
Figure 2.13. The evidence-based approach of using studies and meta-studies is just one component
of the prior that needs to be updated with the iterative intervention and experiment for a particular
individual and a group
Certainty, Risk, and Uncertainty
Similar to the already discussed direct versus oblique decisions and problem
solving, decision making differs in predictable versus unpredictable environments
(Gigerenzer, 2004, 2008, 2015; Gigerenzer & Gaissmaier, 2011; Neth & Gigerenzer,
2015; Gigerenzer, Hertwig & Pachur, 2015b,b). What needs to be done is to differentiate
the worlds of certainty, risk, and uncertainty (see Table 2.2).
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STRENGTH TRAINING MANUAL Volume One
Realm
Certainty
Type of Problem
All op�ons and consequences are
known for certain (known knowns)
Type of inference Appropriate Tool
Deduc�ve
Logic
inference
Risk
All op�ons and consequences are
known, and their probabili�es can be
reliably es�mated (known unknowns)
Induc�ve
inference
Uncertainty
Ill-posed or ill-defned problems
(unknown unknowns)
Heuris�c inference Heuris�cs, ecological
ra�onality
Probability theory,
sta�s�cs
Table 2.2. Three Realms of Rationality: Certainty, Risk, and Uncertainty.
Modified based on (Neth & Gigerenzer, 2015)
Dave Snowden with his Cynefin framework (Brougham, 2015; Berger & Johnston,
2016) differentiates between certainty (obvious), risk (complicated), uncertainty
(complex) with the additional domain of chaos (Figure 2.14):
COMPLEX
COMPLICATED
Cause and effect seen in retrospect
and do not repeat
Cause and effect separated
over time and space
Good practice
(Sense-Analyse-Respond)
Predictive planning
Rules
Expert Analysis
Emergent practice
(Probe-Sense-Respond)
Pattern management
Heuristics
“More stories like this, less like this”
Sensemaking; stories;
monitor coherence
CHAOS
Cause and effect not usefully perceivable
Novel practice
(Act-Sense-Respond)
Act to bring stability
Crises management
Experience informs decisions; action is required;
Data provides options; experts interpret;
measure goodness
Disorder
OBVIOUS
Cause and effect repeatable
known and predictable
Best practice
(Sense-Categorize-Respond)
Standard operating procedure
Automation
Data provides answers; anyone can interpret;
measure best
Figure 2.14. Dave Snowden’s Cynefin Framework. Image modified based on work by Dave Snowden
(Brougham, 2015; Berger & Johnston, 2016; Fernandez, 2016).
The takeaway point is that different domains demand different decision
making. The question is to which domain sports performance belongs to? Well, if you
consult contemporary planning strategies that were highly influenced by Taylorism
and industrial age approach to management, they belong to Complicated domain
(or risk domain). In this domain, probabilities of events are known, and with certain
mathematical tools (like expected utility formulas), one can calculate the optimal
choice. But, to paraphrase Nassim Taleb: “Life is not a casino!”.
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In my opinion and experience, our domain is a Complex domain. We just cannot
oversee and nominate all the potential outcomes, their probabilities, and costs.
Let me quote the description of excellent free course “Introduction to Dynamical
Systems and Chaos” from David Feldman (Feldman, 2017):
“Deterministic dynamical systems can behave randomly. This property,
known as sensitive dependence or the butterfly effect, places strong limits on
our ability to predict some phenomena.
Disordered behavior can be stable. Non-periodic systems with the
butterfly effect can have stable average properties. So, the average or statistical
properties of a system can be predictable, even if its details are not.
Complex behavior can arise from simple rules. Simple dynamical systems
do not necessarily lead to simple results. In particular, we will see that simple
rules can produce patterns and structures of surprising complexity.”
The bold emphasis is mine and it is related to the already stated idea that we can
predict the average effects and directions of intervention, but we cannot predict the
details and exact values. For this reason, we combine the prior knowledge and beliefs
with iterative experimentation through MVP.
Please remember the Small Worlds versus Large Worlds from the previous chapter,
wherein Small Worlds we are able to nominate all the outcomes and probabilities, but
they are simplifications of the Large Worlds. This process is useful, but let’s not forget
the distinction. This puts all these “optimal loads”, “optimal progression”, “optimal
sequencing” approaches on its heads. They are interesting and useful priors we can
consider but trying to find ‘optimality’ in complex domain is flawed and based on
predictable and stable assumptions and behaviors of the system and its environment. As
outlined in Table 2.2 and Figure 2.14, Complexity (or uncertainty on Table 2.2) domain
demands the use of probing, heuristics and satisficing (good enough) approaches.
Optimal versus Robust
The
whole
analytical
(physiology/biomechanics)
approach
utilized
in
contemporary planning (as seen in the top-down approach) is based on the predictable
behavior of the system, in which optimal decisions can be estimated. There is an
optimal training load distribution, there is optimal intensity zone for developing
certain qualities, there are optimal days for high loads and so forth. This is, of course,
the property of the Small World, where all outcomes can be nominated and their
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probabilities calculated, hence optimal decision can be estimated. But this optimality
revolves on the assumptions that things are stable and predictable, and they usually are
not. Figure 2.15 depicts an example of how optimal day to perform speed work in team
sport fails miserably when faced with the unforeseen event (for example head coach
not giving a shit about your speed work):
Difference between OPTIMAL and ROBUST planning strategies
OPTIMAL is the “best” solu�on under given constraints and assump�ons of the “Small World” (model, or the map of the “Big World”). For
example, the “op�mal” �me to do speed training in team sports, would be G+3 or G+4 (3rd or 4th day a�er a game).
The problem with ”op�mal approach” is assuming constraints will stay fixed as well as assump�ons are true. But if they change, or are not
true representa�on of the “Big World”, then the “best” might also become the worst.
In the given example, the weather might be really bad, and one cannot perform sprints at op�mal condi�ons or at all, which means that using
the “op�mal �me” will make athletes being two weeks without speed work. This “op�mal approach” soon becomes “dangerous”.
Sunday
Speed
Monday
Tuesday Wednesday Thursday
Game
Friday
Saturday
Sunday
X
Game
Speed
Monday
Tuesday Wednesday Thursday
Game
Friday
Saturday
Sunday
Speed
Monday
Tuesday Wednesday Thursday
Game
Friday
Saturday
Sunday
If something happens, athletes will miss speed work for 14 days!
ROBUST is a solu�on that is “good enough” under mul�ple condi�ons and assump�ons. It is “sa�sficing” solu�on, rather than the “best”, but
it seems to be performing good enough under different condi�ons. Using the example above, more “robust approach” would be to “microload” speed over the week. If condi�ons change, the athletes won’t be nega�vely affected. This solu�on is not “op�mal”, but it is “robust” to
perturba�ons.
Sunday
Game
Monday
Speed
Speed
Speed
Tuesday Wednesday Thursday
Speed
Friday
Speed
Saturday
Sunday
Monday
X
Game
Speed
Speed
Speed
Tuesday Wednesday Thursday
Game
Speed
Friday
Speed
Saturday
Sunday
Game
Monday
Speed
Speed
Speed
Tuesday Wednesday Thursday
Speed
Friday
Speed
Saturday
Sunday
ROBUST > OPTIMAL
Figure 2.15. Difference between optimal and robust planning on the example
of speed work in team sports
To quote Gerd Gigerenzer: “When faced with significant irreducible uncertainty,
the robustness of the approach is more relevant to its future performance than its
optimality.” And this cannot be emphasized enough in the Complex domain. So rather
than trying to figure out the ‘optimal’ scenario (from physiological and biomechanical
perspectives), try to find the most robust scenario that will be satisficing (good enough)
when assumptions break (Jovanovic, 2018; Jovanovic & Jukic, 2019). The concept of
MVP revolves around providing the most robust plan one can rely on when the shit hits
the fan. This is also the basis of the bottom-up approach to planning. Certain solutions
might not be ‘optimal’ from physiological perspectives, but they will be more robust to
logistical issues (such as missing sessions in Figure 2.15).
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Positive and Negative knowledge
Nassim Taleb brings the distinction between positive knowledge and negative
knowledge (Taleb, 2012). Positive knowledge relates to the knowledge of things that
work, while negative knowledge relates to the things that don’t work and are probably
harmful. Stuart McMillan, sprint coach and CEO of Altis, stated that 80% of success
is knowing what doesn’t work and what not to do. I wholeheartedly agree with this,
since negative knowledge is more robust than positive - things that don’t work most
likely won’t work across scenarios, while things that work probably work across
a smaller number of scenarios. This can be extended to via Positiva and via Negativa
approaches to intervention (Taleb, 2012). Via Negativa means succeeding by not going
bust or improving by not injuring someone. Via Negativa, therefore, means avoiding
the downsides. On the other hand, via Positiva means pursuing the upsides. Similar to
positive and negative knowledge, via Negativa is more robust - it works across various
scenarios. Most people fail similarly, while people succeed differently. Understanding
what doesn’t work for sure trumps knowledge what can work.
One particular story I like to use to demonstrate via Positiva and via Negativa
aspects is the following. Imagine fire starts in the kindergarten full of kids. Janitor of
the kindergarten sees the smoke, alarms everyone and extinguish the fire. No harm
done. Newspapers calls him a hero. This is via Positiva. In some alternate universe, this
same janitor a day before during a regular inspection spots few cables melted in the
electricity cabinet. He switches the electricity off in the kindergarten for 30min (while
everyone bitch on him) and reinstall the wires. Fire never started. He is an asshole for
shutting down cartoons for 30min. This is via Negativa.
Also, next time someone brags how many Olympic champions she has coached,
ask her how many died in the process and have never seen the spotlight.
Via Positiva and via Negativa can be expanded to interventions for improving
performance. For example, via Positiva is about adding the good stuff, while via
Negativa is removing the limiters and pruning the unnecessary stuff (see later growing
and pruning complementary pair). Becoming stronger by lifting more is an example of
via Positiva strategy, where becoming stronger by getting rid of that extra fat layer
(or improving chaotic sleep hygiene) is an example of via Negativa approach. First get
rid of the stupid and unnecessary stuff, before adding new stuff. Via Positiva and via
Negativa represent complementary aspects of different approaches to intervention.
And this is the basis of the robust approach in MVP and Agile Periodization: make
sure to avoid the downsides (adverse effects, or via Negativa) first, before chasing the
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STRENGTH TRAINING MANUAL Volume One
upsides (positive effects, or via Positiva). Or as my boxing coach used to say: “Make
sure you are defended before you attack”. And this brings us to the concept of the barbell
strategy.
Barbell Strategy
Via Positiva and via Negative approaches can be combined with a decision
making strategy outlined by Nassim Taleb (Taleb, 2012; Jovanovic & Jukic, 2019):
barbell strategy (see Figure 2.16). Barbell strategy has two ends: the left end is focused
on protecting from the downside, while the right end is focused on chasing the upside.
The distribution is not 50:50, but asymmetrical where the left side of the barbell is more
dominant.
Low Risk
High Risk
Protect from the downside
“Conserva�ve”
Invest in the upside
“Aggressive”
Figure 2.16. Nassim Taleb’s Barbell Strategy
Protecting from the downside involves using the most robust strategies in
uncertainty, and one of the most researched is 1/N heuristic, which we covered indirectly
in the MVP discussion. 1/N means that all important qualities (at the lowest resolution)
should maintain some volume of, in our case, training dosage. This means, that even
if we screw everything else up, we are still going to avoid the catastrophic downsides.
This is the via Negativa approach: we try to avoid the downside, by simplifying and
stripping down unnecessary complexity of the training program and hitting all the
important qualities in the minimal amount, pretty much all the time. This is indicated
by an equally distributed pie chart on the left side of the barbell on the Figure 2.16. In
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training, this could mean microdosing or making sure that all the important qualities
receive a minimal effective dose of work on almost every day (Jovanovic, 2018; Jovanovic
& Jukic, 2019). Strategies for planning using microdosing will be mentioned again in
Chapter 5.
Once we covered the left side of the barbell, we are free to experiment and invest
in high-risk-high-reward decisions. For example, we might emphasize or saturate a
given method that we speculate will improve a rate-limiting quality (e.g. specialized
exercises for the bench press lock-out for a powerlifter), or we might plan to spend
20-30min in the team session to develop power and speed, or we take the manifested
opportunity to hammer the athletes without (or with less) fear of them getting sore the
next day (because we have been microdosing important qualities).
The barbell strategy can also be applied to the classification of phenomenological
strength qualities (see Figure 2.6) where certain qualities are more likely to improve
performance by protecting from the downside, rather than reaping the benefits of
the upside. For example, in team sports, increasing strength can act as a shield that
makes athletes more robust and more receptive to specific loads, rather than directly
improving performance. Thus, it protects from the downside. Figure 2.17 contains a
hypothetical distribution of phenomenological strength qualities into protecting from
the downside versus pursuing the upside, from a non-strength sport perspective. This
will again differ from sport to sport, but the take-home message is that we need to
think about intervention and its effects in complementary aspects of protecting from
the downside versus pursuing the upside.
Arrow
Anaconda Strength
Armor Building
Vanilla Training
Avoid downside
Anaconda
Strength
Mongoose
Persistence
Pursue upside
Figure 2.17. Phenomenological strength training objectives can be distributed on the barbell
The barbell strategy also helps us in bridging the Is/Ought gap (see Figure 2.11)
by taking the shield (protect from the downside) and sword (reap the benefits of the
upside) to fight the Dragon of Chaos (pun intended) (Figure 2.18).
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STRENGTH TRAINING MANUAL Volume One
Figure 2.18. Fighting the Dragon of Chaos (Uncertainty) demands the use of the shield to protect from
the downside (protect your own ass first), and a sword, to pursuit the upside (kill the dragon, take the
Princess/Gold). Image used under license from Shutterstock.com (delcarmat, 2019)
Randomization
Let me start by quoting from the outstanding book “Seeking Wisdom” by Peter
Bevelin (Bevelin, 2013):
“Being flexible and learning a variety of options to choose from to deal
with the world is of great value. This implies that finding new ways to deal
with the world is superior to overtraining old patterns. For example, studies
of honeybees show that they navigate according to a map-like organization
of spatial memory. When bees are over-trained to find a single nectar site, it
is easy for them to find their way back to the hive from that site, but not very
well from other sites. But when the same bees are trained to many nectar sites,
they are much better in finding their way home to the hive from a range of
different locations. Further studies suggest that we learn better when we mix
new information with what we already know. “
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All our efforts to find the best or the most optimal training plan and stick to it
might be actually making athletes fragile (Jovanovic, 2018; Jovanovic & Jukic, 2019).
They adapt to a certain, what we deem optimal, schemes and if anything changes in the
competition they are screwed. Make athletes adaptable, not adapted!
This is achieved by allowing some randomization. We tend to fear randomization
because it seems, well, random and pulled out of our own ass. But constrained
randomization can be helpful in finding a better solution and making athletes
adaptable. For example, we might choose to do explosive exercises after the strength
exercises when the athletes are tired. Optimal? Fuck no. But will make athlete perturbed
to maybe find a better movement pattern, different solutions and become adaptable to
various scenarios. And this can be utilized beyond strength training - for example in
skill learning (Davids, Button & Bennett, 2008; Renshaw, Davids & Savelsbergh, 2012;
Chow et al., 2016) . In my opinion, it can be implemented on the right side of the barbell
(see Figure 2.16), where we might experiment when protection from the downside is
covered. For example, we might experiment with higher frequency workout over a
specific phase to explore how individual responds (as long as the major qualities are
covered using 1/N heuristic, or the left side of the barbell), or we might try a higher
volume of the specialized exercise to see if it will bring adaptation to a stuck athlete.
Another idea is to define the sequence of the training sessions using Markov Chains and
Don’t Break The Chain strategy (see Jovanovic & Jukic, 2019 and Chapter 5).
Latent vs. Observed
Imagine collecting the data for a large number of athletes using various
performance metrics and tests (e.g. maximal bench press, squat, 10m time, 1500m time,
you name it). We expect specific tests and metrics to correlate between each other (e.g.,
bench press 1RM to correlate with military press 1RM), while not correlating with other
tests and metrics (e.g. we do not expect bench press 1RM to correlate with VO2max or
1500m time trial). The analysis that helps us find these groups or clusters of metrics is
called factor analysis (Borsboom, Mellenbergh & van Heerden, 2003; Borsboom, 2008)
i.e., the process that produces the concrete data patterns on which statistical analyses
are executed. For a variable to count as observed through a set of data patterns, the
relation between variable structure and data structure should be (a. Factor analysis
helps us in figuring out if there are any latent (or hidden) variables or constructs that
explain observed (or manifested) tests and metrics. Theoretically, these factors (i.e.,
latent variables or constructs) should be aligned with the concept of biomotor abilities
(i.e. strength, speed, endurance, flexibility, etc). But to my knowledge, the current body
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of literature on latent variable modelling is very limited, meaning our understanding is
also constrained.
There are three major positions (Borsboom, Mellenbergh & van Heerden, 2003;
Borsboom, 2008; Borsboom & Cramer, 2013; Schmittmann et al., 2013; Maul, 2013;
Guyon, Falissard & Kop, 2017) regarding the ontological status of latent variables (see
Figure 2.19).
Latent
Observable
Observable
x1
x1
x2
x2
x3
x3
x4
x4
x5
x5
Construct
Reflec�ve model
Latent
x1
Construct
x2
x3
Forma�ve model
x5
x4
Network model
Figure 2.19. Three major positions regarding ontological status of latent variables
Realist perspective assumes latent variables to represent (ontologically) real
constructs that cause manifested observations. This realist perspective is represented
with a reflective model and essentialism in classification. Essentialism is the view that
latent variables have a well-defined hidden nature; and because these constructs
exist independent of our classifications, categories formalize this underlying nature
(Borsboom, Mellenbergh & van Heerden, 2003; Borsboom, 2008; Maul, 2013; Guyon,
Falissard & Kop, 2017). For example, we might assume from the realist perspective that
there is the strength as a latent construct that causes observable features or expressions
of strength.
On the other hand, instrumentalist or constructionist perspective assumes that
latent variables represent just a numerical construct that helps in explaining manifested
observations (Borsboom, Mellenbergh & van Heerden, 2003; Borsboom, 2008; Maul,
2013; Guyon, Falissard & Kop, 2017). This perspective is represented with the formative
model and nominalism in classification. Nominalism is the view that latent variables
are constructed categories without natural referent, merely practical categories for
particular uses (Guyon, Falissard & Kop, 2017). With the constructionist perspective,
latent variables are not causes of observable performance.
I believe that the dichotomy between realism and instrumentalism/constructivism
can be overcome by a complementarism and pragmatist-realist positions (see the
previous chapter) (Kelso & Engstrøm, 2008; Guyon, Falissard & Kop, 2017). One such
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approach that treats constructs as the emergent phenomena is network analysis. From
a network perspective, a construct is seen as a network of manifested variables (Cramer
et al., 2012; Borsboom & Cramer, 2013; Schmittmann et al., 2013; Bringmann et al., 2013;
Epskamp, Borsboom & Fried, 2016; Guyon, Falissard & Kop, 2017)
One needs to keep in mind that the results of factor analysis depend on the
variables selected, how they are normalized (e.g. are we going to use absolute bench
press 1RM in kgs, or we are going to scale it with mass or use allometric scaling? (Folland,
Mccauley & Williams, 2008)) and who are the subjects. For example, if we test a bunch of
under 8-year-olds with a battery of tests, there might be only one or two major factors
that explain manifested performance. If we split them up to a more or less advanced,
we might get a different latent variable structure. As they age and gain experience,
this latent structure might differentiate into specific subdomains that can be specific
to given strata (subgroup) or even individuals (see next section). Unfortunately, such
studies are non-existent in sports performance domain.
Interven�on
Max Effort
Method
Latent
Strength
Realist model
Observable
Interven�on
Observable
Bench Press
Max Effort
Bench Press
Back Squat
Max Effort
Back Squat
Pull-Ups
Max Effort
Pull-Ups
Military Press
Military Press
Lunges
Lunges
Latent
Strength
Construc�onist model
Figure 2.20 Realist perspective and constructionist perspective on intervention
and ontology of constructs (biomotor abilities)
It is important to keep in mind that all three approaches are Small World
models (see the previous chapter), aiming at simplifying a complex reality. The thing
I personally have issues with is the theory of biomotor abilities, where we assume
realist and essentialist position assuming there are ontologically real constructs,
such as strength, speed, flexibility that cause manifested (observable) performance.
This mental model further assumes that there are methods of interventions that hit
those constructs, which eventually results in improved performance (see Figure 2.4
and Figure 2.20). For example, one trains strength (biomotor ability or quality) with
maximum effort method, which results in improved strength as a latent variable and
consequently improved manifested performance (see left side in Figure 2.20). In this
case, improving strength, as a latent construct, will reveal as improved performance in
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all performance tests and metrics (even in those that are not utilized in the intervention;
in this case military press and lunges which are grey on Figure 2.20)16.
Although I am a complementarian and pragmatist-realist, I am leaning
more towards constructionist perspective here, where one intervenes not on latent
constructs, but on manifested performance. This way, we do not train strength, we
train exercises. On the right side in Figure 2.20, we intervene on exercises, and not
on some latent constructs. The improvement is seen not because strength as a latent
construct is improved, but because observed tests are improved. The unused exercises
in this example might also see improvements, but not due to the improvement in
the underlying construct, but more because of transfer and similarity between other
exercises.
It is important to remind you again that both of these perspectives are Small
World models. They might seem as unnecessary philosophical mumbo-jumbo in what is
supposed to be a practical strength training manual, but they are very much useful. For
example, if you compare different schools of training (e.g., Westside Barbell (Simmons,
2007) versus Boris Sheiko (Sheiko, 2018)), you might find different philosophical
perspectives of training qualities and interventions. Westside Barbell might approach
training strength using different specialized exercises and methods that are supposed
to tap underlying qualities on which manifestation of strength depends and is caused
by. Boris Sheiko, on the other hand, might approach things differently, aiming and
improving observable exercises (e.g., bench, squat, and deadlift). I am not here to
tell you which one is correct or not; I am here to tell you that both are Small World
models and I am encouraging you to be a multimodel thinker (Page, 2018) and take
the Agile Periodization approach and embrace the fact that we are still pretty much
clueless. Having said this, both Westside Barbell and Boris Sheiko school had produced
numerous world-class powerlifters and feats of strength.
Unfortunately, there is not much research behind latent variables (particularly
regarding the longitudinal change, or dynamic factor modelling), and we seem to take
for granted the realist perspective of biomotor abilities theory. But here is the catch I do not think that biomotor theory explains ontological qualities (a place for things),
particularly because there is almost no research on this topic, but rather represents
16 Please bear in mind that a single snapshot of multiple performance variables can be explained
with a few latent variables, but the change after intervention in those performances might not
be. The current states of multiple athletes over multiple tests can be explained by few latent
constructs, but after interventions, the changes in those tests might not be explained with the
same constructs. In plain English, the current bench press and military press might be explained
by a construct called upper body pushing strength since they are correlated, but after training
intervention, their individual changes might not be correlated, hence cannot be explained by the
same constructs. This represents an additional manifestation of Is/Ought Gap
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a heuristic approach to classify forum for action, which aims to classify interventions
instead. Having said that, I think a better term for strength training (which assumes
perspective where one trains latent construct strength) would be resistance training
(which assumes method or intervention). I am not sure if we are hitting latent construct
strength with strength training, but I am certain we are using heavy objects in resistance
training. For example, resistance training might not only improve (and serve to
improve) strength performance (as measured by 1RMs in say bench press and squat),
but can also improve 10-20m times, vertical jump height, the robustness of the athletes
and so forth. Since I do not have a clue about causal place of things that underlie complex
human performance (and particularly of one individual), I will not pretend that I am
training and hitting strength (or accelerative strength, explosive strength, reactive strength
and what have you) and fawning around since I am using scientific terms, I would
instead approach these complex issues from a forum for action and phenomenological
perspective.
You might ask why didn’t I name this manual Resistance Training Manual? Simple
- because of sales and keywords, and the fact that strength training is used more than
resistance training.
The takeaway message, when it comes to classifying your plan components, is
to classify them based on the phenomenological forum for action, rather than a place of
things and potential goals and constructs being hit. For example, if your training plan
has the following components: aerobic endurance, fast twitch hypertrophy, cardiac
output, lactate endurance, repeat sprint ability and so forth, you are classifying using
place of things approach where you use objectives and constructs as classifiers. Well, fuck
that! As alluded multiple times, we never know if those are the qualities we are going to
hit. Rather, use classification based on action and phenomenology (a forum for action):
long intervals, clusters, long runs, short intervals, high rep work, repeat sprint training
and so forth. Yes, qualities give you objectives to aim for, but use forum for action as an
approach to categorizing your training. Stoically, control what you can, and what you
can control are the actions you are going to take, not the constructs you plan hitting.
Inter-Individual vs. Intra-Individual
Latent variable modelling is quite common in psychometrics. For example, IQ and
Big Five personality tests are the results of years and years of testing and factor analysis
(and are still the hot topic of arguments and discussions). For example, imagine asking
thousands of people shitload of different questions (e.g., “I prefer to stay home and
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read” or “I like going to the parties”) and then performing factor or latent variable
analysis. This was actually done, and this results in the famous Big Five model of
personality, where latent factors or constructs represent personality traits: openness,
conscientiousness, extraversion, agreeableness, and neuroticism (see Figure 2.21).
Openness
Neuro�cism
Conscien�ousness
Personality
Agreeableness
Extraversion
Figure 2.21. The big five personality traits
In a big field such as psychometrics, Big Five latent variable model (as well as IQ)
has been heavily debated and criticized, and the arguments are still very much alive.
One such critique is that Big Five, as well as other latent variable models, is based on
inter-individual analysis, where we take a single snapshot (occurrence) of bunch of
individuals on a bunch of variables and perform factor analysis. The problem of course,
is that we take this inter-individual analysis and make inferences on a particular
individual (Borkenau & Ostendorf, 1998; Hamaker, Dolan & Molenaar, 2005; Molenaar
& Campbell, 2009). The question is if this is a valid approach17
17 This is usually termed ergodic or non-ergodic. An ergodic process is the one that is the same
for inter-individuals, as well as intra-individual, where non-ergodic is not.
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As it seems to be the case with Big Five, when applied repeatedly to individuals
over time (Borkenau & Ostendorf, 1998; Hamaker, Dolan & Molenaar, 2005; Molenaar
& Campbell, 2009) each individual has different latent structure! So, although Big
Five is sound for inter-individual comparison, it is not valid for intra-individual
understanding, predictions and intervention.
Figure 2.22 depicts famous Cattell’s Data-Box model (Molenaar, Huizenga &
Nesselroade, 2003; Molenaar, 2004; Hamaker, Dolan & Molenaar, 2005; Molenaar
& Campbell, 2009; Nesselroade & Molenaar, 2016) that makes a distinction between
inter-individual analysis (or R-technique, where multiple individuals are sampled
once for multiple variables) and intra-individual analysis (or P-technique, where a
single individual is sampled over multiple occurrences for multiple variables)
Interindividual Analysis
(R-Technique)
Intraindividual Analysis
(P-Technique)
Figure 2.22. Cattell’s three–dimensional data–box (individuals × variables × occasions of measurement).
Image used and modified under license from Shutterstock.com (Chernetskiy, 2019)
With the recent developments of longitudinal data analysis, such as dynamic
factor analysis (Hamaker, Dolan & Molenaar, 2005), the intra-individual analysis is
definitely possible, but it is very much lacking in sport performance domain. Therefore,
the question is which scientific findings based on inter-individual variation can be
applied to an individual subject? (Molenaar, Huizenga & Nesselroade, 2003; Molenaar,
2004; Hamaker, Dolan & Molenaar, 2005; Molenaar & Campbell, 2009; Nesselroade
& Molenaar, 2016). In other words, those who peacock around waving the evidence55
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based flag, are using inter-individual evidence, which might or might not be applied to
a particular individual. Although it definitely is a starting point (see prior and Bayesian
updating in the previous chapter), it indeed isn’t deterministic enough to explain
and predict individual effects based on interventions. When it comes to a particular
individual, even when we are using evidence-based meta-studies and bitch about it on
Twitter, we are still facing the Dragon of Chaos and Is/Ought Gap.
My solutions to these uncertainties are not blind faith in evidence-based metastudies, Russian biomotor abilities, assumptions of predictability of responses and
performances, but rather embracing uncertainties through phenomenology, MVP,
barbell strategy, iterations and other ideas from Agile Periodization framework.
Substance vs. Form
Additional mental model (Small World) worth mentioning is the dichotomy to
substance and form (Figure 2.23)
Substance
Constructs
Form
Constrains
Figure 2.23. Substance vs. Form, or Potential vs. Realization.
Let me give you a simple example. Imagine you get a chance to ride Formula 1 car
for the first time in your life. You jump into the car, take a time trial on the track - and you are shit! Why is that? Is it because the Formula 1 car is slow? Or because you are not
skillful enough to use the car’s potential? I bet my life it is the latter.
A more concrete example might be someone who is muscular, but lifts like a
Disney princess (ahem - me). The potential is there, but what seems to be lacking is the
ability to use that potential. In this case to recruit those muscles.
I like to think about this mental model as substance~form complementary pair.
According to this Small World model, manifested performance is the combination of
substance and form (Figure 2.24)
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+
Substance
=
Form
Manifested Performance
Figure 2.24. Manifested performance as a combination of substance and form
As Figure 2.23 indicates, the substance can also be called constructs, which is,
you guessed correctly, very much related to the latent variable modelling. For example,
you might have a shot-putter who has 200 kg incline bench press but is unable to throw
more than 18 meters. The question is why? And what should be done about it? Should
he continue improving his potential (in this case identified as incline bench press, or
strength as a construct), or develop his form (skill of throwing)?
Using the example of Westside Barbell and Boris Sheiko again, Westside might
approach the problem by increasing the potential (substance) using specialized
exercises and method, and hoping that this will be manifested on the competitive
moves, while Sheiko might approach improvement from the form perspective, where
he might improve execution skills. Either way, neither is correct, but both are useful
Small World models.
This mental model is very much used all the time to make decisions, whether
you are aware of it or not. Figure 2.25 depicts Yuri Verkhoshansky line of reasoning,
whereas manifested performance (S or x-axis on the figure) improves, ability to use
Figure 2.25. The relationship between potential (p) and ability to utilize potential (T) as performance
improves (S). R line represents increase in intensity of the training stimuli. Courtesy of Yuri
Verkhoshansky. Modified based on “Main Features of a Modern Scientific Sports Training Theory”
(Verkhoshansky, 1998).
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potential (T line on the figure) increases. This results in the idea that potential (p on the
figure) eventually creates a bottleneck, and to increase performance, one must increase
potential. Other authors, such as Frans Bosch would not agree with this model, probably
me neither. But it is still a useful model to think about and consider. It can be considered
as an extension of the necessary vs. sufficient model (see the previous chapter). Using our
shot putter example, incline bench pressing a lot might be necessary precondition to
throw long distance shot put, but it is not sufficient.
This is indeed a useful model to consider in our multi-model reasoning and
decision making when deciding about what might be a bottleneck (i.e., rate limiter) and
where should we intervene. Also, this model is scale-free, which means that it can be
applied to different levels of analysis. For example, we might conclude that substance
in the bench press is cross-sectional area (CSA) of the pecs. Once we examine the CSA
of the pecs, we might identify a deeper substance, for example, CSA of the fast twitch
fibers. Going down the rabbit hole even further, the CSA of fast twitch fibers depends on
the myofibril surface versus connective tissues, and so forth.
The same model can be applied to team sports. The substance would be individual
skills of the players, while form would be the ability to play coordinated as a team.
Extensions of this model could be the Fitness and Fatigue model. One might have
potential (Fitness), but it is masked by form (Fatigue). This mental model is truly overencompassing and can be applied to different levels of analysis, from nations, groups to
individual cells. Further discussion on this topic can be found in my other book “HIIT
Manual” (Jovanovic, 2018).
Other complementary pairs
I tried to cover many complementary pairs that guide my decision making and
Agile Periodization in this chapter. However, there are many more that share some
similarities and that will be introduced thorough this manual. I will shortly introduce
them here for the sake of completeness.
Explore – Exploit
The first time I heard about explore – exploit was from the book “Algorithms
to Live By” (Christian & Griffiths, 2017) and it immediately clicked with me. Imagine
you get to work with a soccer club or a new powerlifter. Unless you are blind ideologue
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that want to impose particular training ideology, you will probably have to spend some
time exploring and probing soccer players or powerlifter. To fulfil this objective one can
utilize MVP, which allows exploration while minimizing the downside. As one acts, over
time things and useful information will manifest itself. Once one gains more insight
into what might be working (using cost–benefit analysis and watching for the Is/
Ought gap), then exploitation can begin. This might mean focusing more attention to
a particular quality or a rate limiter that one deems will bring the biggest bang for the
bucks.
In a way, this is similar to oblique vs direct decision and problem-solving
introduced earlier. These two aspects of program design should always be utilized in
a higher or lower degree. Exploration can come in a form of randomization, which can
also make athletes adaptable as opposed to adapted to a particular optimal program
(exploitation). Exploration can be also seen as a play element and fun, while exploitation
can be seen as flipping-the-burgers, work and routine. Similar complementary pair is
stability – variability, which represents interplay between stable elements of the plan
and variable elements (e.g., main exercises might be stable across the training phase,
while assistance exercises might be variable and self-selected during the workout).
“To live in a restless world requires a certain restlessness in oneself. So long
as things continue to change, you must never fully cease exploring. “ (Christian &
Griffiths, 2017)
Growing - Pruning
Growing and pruning are quite to similar to via Positiva (gaining by adding) and
via Negativa (gaining by subtracting), but also to explore and exploit. Pruning means
removing waste and focusing on what matters the most (i.e., exploiting). The problem
with this is that sometimes we do not know what matters the most, thus one needs
to grow (i.e., explore). Experienced athletes, over time figure out what seems to be
working for them and what does not, so they can remove the unnecessary load and
stress and focus on the most important qualities in training. One model that will be
introduced in Chapter 5 assumes that to move forward, the training load needs to be
increased over time, particularly for the advanced athletes. This is generally true but
cannot happen for the unlimited number of qualities. Experienced athletes can proceed
to prune unnecessary waste, so does the overall load might actually decrease since
they are focusing (i.e., exploiting) qualities of the biggest importance. On the flip side,
some retired athletes might actually try exploring again (while focusing on the most
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important qualities), or should I say playing, since there is no competition pressure
and associated stress, which can result in some athletes actually hitting personal bests
while retired.
Since we are dealing with a complex system, it is hard to give concrete rules and
steps. It is then more important to understand complementary components and the
constant tug -of-war between them.
Develop – Express
Develop – express are very much related to substance and form complementary
aspects. Will take soccer player as an example again – just because one is sprinting in
a game or practice (i.e., express or manifest), doesn’t mean one is developing speed.
Or just because one is demonstrating strength (i.e., express) in the gym using sets
of one, doesn’t mean one is developing strength. Just because one is doing the most
specific exercises (i.e., form), doesn’t mean one is developing the underlying qualities
(i.e., substance). This can also be seen from another complementary pair: simulate
– stimulate. This complementary aspect will be utilized when discussing exercises
specificity in Chapter 3.
Maintain – Disrupt
According to Vladimir Issurin (Issurin, 2008a,b, 2013, 2015, 2019), most
generalized biological mechanisms of human adaptation involve (1) Homeostatic
regulation, and (2) stress adaptation. From (Issurin, 2019): “The theory of homeostatic
regulation presupposes maintenance of the most rigid and relevant biological constants
necessary for protecting general life conditions” and “The fundamental theory of stress
adaptation explains human reactions to extraordinary demands such as highly intense
and severe workloads. This type of training mobilizes energy resources that exceed the
metabolic levels necessary for homeostatic regulation and trigger endocrine responses
of stress-related hormones”. According to Vladimir Issurin (Issurin, 2008a,b, 2013,
2015, 2019) training methods and loads tapping these two different generalized
biological mechanisms of human adaptation should be separated (see Saturated Separated, and Complex/Parallel - Unidirectional in Chapter 5) in different blocks. This
is thus the basis of the Block Periodization. There is a recent critique of this line of
reasoning (Kiely, Pickering & Halperin, 2019).
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Although I agree with the critics (Kiely, Pickering & Halperin, 2019), I do believe
that there is this complementary aspect of homeostatic maintenance and homeostatic
disruption involved in biological mechanisms of human adaptation and beyond (see
Chapter 5 for Hero’s Journey model and known/unknown domains). But I do not believe
they are clear cut and that they need to or can be separated. For example, highly stressful
workout (i.e., HIIT training, like sprint-interval training, or SIT, which might involve
30sec all out running) might be an archetype of the homeostatic disruption workload, but
it might force the body to adapt by improving its homeostatic maintenance processes.
Or long slow run might be an example of the homeostatic maintenance process, but it
might also improve the ability to disrupt the same. This is another example of Is/Ought
gap. Kiely, Pickering and Halperin (Kiely, Pickering & Halperin, 2019) called it Nonsequiturs, or the construction of superficially rational chains of reasoning, which on
closer inspection are missing critical links.
But I think there is something to these two complementary components. Research
into affective responses to training intensity (Ekkekakis, Parfitt & Petruzzello, 2011;
Ladwig, Hartman & Ekkekakis, 2017; Hartman et al., 2019) particularly valence utilizing
pleasure/displeasure scale, shown that when exercising above lactate threshold there
seems to be increased in the displeasure ratings. It might be then theorized that ratings
of pleasure/displeasure indicated the severity of homeostatic perturbation (Hartman
et al., 2019). I guess this is also related to the ratings of exertion, although more about
it in Chapter 5. Theoretically, lactate threshold or critical power represent thresholds
after which body is unable to maintain its homeostasis and one is performing on the
“borrowed time” (for more info about endurance and training see (Jovanovic, 2018).
Research into training load distribution with endurance runners by Stephen Seiler et al.
(Eriksson; Seiler & Kjerland, 2006; Seiler & Tønnessen, 2009; Seiler, 2010; Muñoz et al.,
2014) shows that following the polarized distribution of the training load leads to better
outcomes. This means that the gross of training load distribution (e.g., 80-90%) is under
aerobic threshold (which is approximately below 75% HRmax), and some training load
(e.g., 10-20%) is over anaerobic or lactate threshold (which is approximately above 90%
HRmax). The middle zone, between two thresholds is minimized (75-90% HRmax).
This is similar to the late Charlie Francis idea of avoiding the medium zone (i.e., 70-95%
of maximal velocity) when training sprinters. It seems that this middle intensity, both
in Seiler research with endurance runners and with Charlie Francis experience with elite
sprinters, yields too much downside for the upside it produces. For these reasons, I think
that maintain – disrupt complementary aspects have an application to training, although
they do not need to be separated in distinctive blocks as Vladimir Issurin suggested.
What this has to do with strength training? I think that maintain – disrupt can
be related to develop – express, as well as extensive – intensive complementary pair
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(discussed in Chapter 5). I do believe, that when applied beyond biology (see Hero’s
Journey model in Chapter 5), the idea behind maintain – disrupt can be very applicable.
When it comes to training load, it is hard to pinpoint which zones improve the ability
to maintain homeostatic control, versus which zones improve the ability to disrupt it. I
do think that some ideas from polarized training distribution can be applied to strength
training, which is discussed in Chapter 5, but the main application, in my opinion, is
beyond biology and it is embedded in the concepts of push the ceiling – pull the floor.
These are all discussed in Chapter 5.
Structure - Function
Structure - function, although similar to substance – form, is more related to
physiology and biology. When it comes to strength training, structure involves the
cross-sectional area (CSA) of the muscles, fast vs slow twitch percentage, tendons
thickness and stiffness (although stiffness can be more related to function), joint
characteristics, bone structure and so forth. Function is more related to CNS and actual
performance, and how this structure is utilized (hence the similarity with the substance
– form). This might mean motor unit recruitment, discharge frequency, coordination
and so forth. Armor building methods might be more structure directed, where Arrow
methods might be more function directed to give an example.
One useful heuristic is that structural change takes longer to create, but also
longer to lose, where functional change might be a bit faster to acquire and faster to lose
(and maybe faster to re-acquire as well). Some of the phase potentiation sequencing
discussed in Chapter 5 rely on this complementary aspect. For example, anatomic
adaptation, followed by hypertrophy phase relies on the assumption that structure is
built, and this will allow phases that follow (maximum strength, power conversion)
better potentiation since they rely more on function effects of strength training.
The debate in strength training circles weather structure limits function (in this
case weather CSA limits strength; for example see (Buckner et al., 2016; Taber et al.,
2019)) is still ongoing.
Weaknesses – Strengths
Once one discovers athlete qualities, compared to something else (e.g., other
athletes in the group, previous athlete level, research results) these qualities can be
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considered as strengths (if better than something else), or weaknesses (if worse than
something else). This categorization can be tricky and biased (e.g., physiological lab
coat working with soccer athletes and deciding that the forwards have low VO2max
values). What is even trickier is figuring out what to about it (see Is/Ought gap).
One heuristic or an approach would be to utilize the Liebig’s law of the minimum
(“Liebig’s law of the minimum,” 2018) which comes from agriculture and states:
“This concept was originally applied to plant or crop growth, where it
was found that increasing the amount of plentiful nutrients did not increase
plant growth. Only by increasing the amount of the limiting nutrient (the one
most scarce in relation to “need”) was the growth of a plant or crop improved.
This principle can be summed up in the aphorism, ‘The availability of the most
abundant nutrient in the soil is only as good as the availability of the least
abundant nutrient in the soil.’ Or, to put it more plainly, ‘A chain is only as
strong as its weakest link.’”
The above quote is taken from Wikipedia article (“Liebig’s law of the minimum,”
2018) and the bold emphasis “A chain is only as strong as its weakest link” is mine.
Liebig’s law of the minimum is usually visually explained very neatly with the Liebig’s
barrel (“Liebig’s law of the minimum,” 2018) which is depicted on Figure 2.26. Just as
the capacity of a barrel with staves of unequal length is limited by the shortest stave, so
a plant’s growth is limited by the nutrient in shortest supply.
Figure 2.26. Liebig’s barrel and the law of the minimum. Just as the capacity of a barrel with staves of
unequal length is limited by the shortest stave, so a plant’s growth is limited by the nutrient in shortest
supply. Image modified from Wikipedia (“Liebig’s law of the minimum,” 2018)
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Using “A chain is only as strong as its weakest link” would imply that the Ought
should be in investing in improving the weakest quality. This also assumes that the
easiest quality to improve would be the weakest. Some criteria-based periodization
strategies, such as Al Vermeil’s approach (Vermeil, Helland & Gattone, 1999), involves
emphasizing certain lacking quality for a given period of time (while working on
other important qualities as well), rather than following pre-planned block sequences
(see Chapter 5). If an athlete lacks hypertrophy, then one might spend some time
in hypertrophy emphasized training phase. Once certain criteria are met, another
identified quality can be emphasized.
A similar approach can be utilized in powerlifting. Theoretically, the easiest way
to improve one's total would be to focus on the weakest lift for a period of time. The
rationale is that this might be the easiest to fix.
But this is tricky, or should I say complex (please note that we have jumped
over Is/Ought gap). One needs to utilize the Barbell Strategy here as well. Maybe, that
weakness is there for a reason. Maybe fixing this weakness will screw up strengths,
directly or indirectly through second order effects. We never know. For that reason,
Barbell Strategy comes handy: protect from the downside (in this case screwing up the
strengths) and pursue the upside (in this case improving the weakness).
Another approach might be to focus on one’s strengths. Assume you have a
kickboxer as an athlete, and he is really bad at clinch game. Would you be willing to fix
it? What if this lad is tall, short leverage and prefer to fight from the rim? Working on the
clinch exclusively might cause a lot of frustration and might decrease his confidence,
particularly if it is before a fight. Maybe focusing on one strengths and trying to play on
that card should be the focus?
This is not to say that either approach is better or worse. They are approaches
to a complex problem, and both of them are jumping over the Is/Ought gap. There
are opposite proverbs of course18 (Page, 2012), and to be wise one needs to know in
what situation to apply a particular proverb. I also think that the opposite provers
phenomenally depict the complementary nature of the complexity.
The mentioned kickboxer in a given training session or sparring can focus on
his strengths (e.g., circling around and working from a rim range), or focus on his
weaknesses (e.g., actually entering clinch range more frequently to work on it). These
are thus complementary aspects, and both should be present in a higher or lower degree
across different phases of the training (week, sprint, phase, release, career) all the time.
18 For example, consider the following opposite proverbs:
“You’re never too old to learn” Vs. “You can’t teach an old dog new tricks”
“Don’t change horses in midstream” Vs. “Variety is the spice of life”
“Birds of a feather flock together” Vs. “Opposites attract”
“Too many cooks spoil the broth” Vs. “Two heads are better than one”
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The Function of Muscles
in the Human Body19
According to Frans Bosch (Bosch & Klomp, 2005; Bosch, 2015) every muscle in
your body is structured20 (evolved) with a specific movement role and purpose. Although
muscles can work in different ways (e.g., hamstrings is „designed“ to operate reactively
/ isometrically, athletes can use it concentrically when performing leg curl exercises),
as the speed of the movement increases, and thus becomes less volitionally controlled,
muscles start to work to their specialized structure.
Taking this into account, the proposed generalized classification of muscles is
the following:
Concentric-explosive muscles
•• Single-joint (cross over only one joint)
•• They have spindle-shaped structure (the muscle fibers extending parallel to the line
of the pull and tendon)
•• They are suitable for positive (concentric) work and strength training
•• Have a greater area of force production under the force-length curve, thus they can
express force over different lengths. Wider operating range
•• ‘Stupid’ muscles
•• Example: m. gluteus maximus, m. iliopsoas, m. vastus lateralis et medialis
Reactive-elastic muscles
•• Multi-joint (cross over two or more joints, bi-articulate)
•• Have pennate structure (muscle fibers extending at an angle in relation to the
tendon)
•• The pennate design allows greater physiological cross-section area (CSA) for the
same muscle mass in relation to the spindle-shaped muscles, which enables them
to achieve greater force production per kilogram of mass
•• Pennate design means that the muscle fiber length changes significantly when
changing the total length of the muscle, resulting in a smaller area of force
19 This part is modified article that I have published at the Complementary Training website (Jovanovic,
2010) which was a review of Frans Bosch book and theories (Bosch & Klomp, 2005)
20 See structure – function complementary pair. Structure defines function (from the ontogenesis
perspective in the higher degree), but function over time defined structure (from phylogenesis perspective
in a higher degree). This makes them complementary pair.
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production under the force-length curve. To put it simply, pennate muscles can
achieve maximum force production only at certain lengths. Narrower operating
range.
•• Have developed important passive structures (tendons, fascia, etc.).
•• Able to absorb and process the external force
•• Structured (evolved) for isometric work because of their narrower force-length
relationship.
•• Isometric function and the pre-activation of these muscles are the prerequisites
for its reactive-elastic function, which makes the muscle contractile elements (CE)
stiff, and allows the muscles to use its serial elements (SE): tendon and other passive
elements within the muscle structure
•• ‘Intelligent muscles’ – require more effort and coordination to be used effectively
•• Example:
m.
erector
spinae,
m.
biceps
femoris,
m.
et
semitendinosus
semimembranosus, m. rectus femoris, abdominal muscles.
Of course, this is a rough division. In reality, the muscles are flexible and can have
characteristics of both groups. However, the division between the two groups is very
practical, especially in organizing training, rehab, and injury prevention programs21.
Since movement is interplay between stability and mobility22 certain muscles
can contribute to these specific functions. In short, using stability - mobility continuum,
a muscle can be classified to (Comerford & Mottram, 2001, 2015)23:
1. Local stabilizer
2. Global stabilizers
3. Global mobilizers
21 The implication of this, at least according to Frans Bosch (Bosch & Klomp, 2005; Bosch, 2015) training
hamstrings more isometrically and reactively, rather than concentrically and eccentrically (e.g., Nordic
curls) is more aligned with their structure and purpose hence more efficient in injury prevention in high
speed running (Van Hooren & Bosch, 2017a,b)
22 Stability and mobility can be also considered complementary pair. One can look at stability as prerequisite
for mobility (similar to homeostatic maintenance and homeostatic disruption complementary pair).
“How fast would you drive Ferrari in the city with the malfunctioning breaks?”. For example, improving
punching power might be limited by the breaks, or muscles that decelerate the punch (i.e., last, rhomboids
and general pull muscles). This puts a concept of specificity and dynamic correspondence into perspective
(see next chapter), since maybe the improvement in particular movement is limited not by prime movers
and addressed with specific exercises, but by stabilizing muscles and addressed with general and actually
opposite means (e.g., movements/muscles of opposite direction). There is always Is/Ought gap involved,
just realize that the jump often done by the similarity and association bias (i.e., assumption that since the
mean is specific, or looks similar, it must be effective).
23 This structural approach is often used in pain and dysfunction diagnostics and management. For
example, low back pain is due dysfunction of the local stabilizers that should be targeted (with Vanilla
training). There are critiques of this model, as well as other alternatives, such as biopsychosocial model
(Stilwell & Harman, 2019)
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The mentioned classification of (1) Concentric-explosive muscles and (2)
Reactive-elastic muscles refers only to Global mobilizers.
In my opinion, and I may be wrong, muscles are flexible in terms of their function
and can express different functions under certain context. This may be a good thing
and it may lead to dysfunctions and pain too (from a structural perspective to pain and
dysfunctions; see footnotes). Anyway, there is a certain attractor in their functioning
based on their structure and location. What is important is to understand that certain
coordination dynamics that emerge under constraints can result in a good performance,
but also in pain and dysfunction.
Our understanding of muscles is dominated by the model that muscles have
only one function of overcoming the external load. However, this is only part of the
story. Muscle function is more complex and more versatile (Bosch & Klomp, 2005;
Bosch, 2015):
•• Muscles overcome the external load (force and power production)
•• Muscles pre-stretch elastic tissues
•• Muscles have a role in the transfer of energy from one joint to another
•• Muscles facilitate other muscles by eccentrically loading them
Muscles overcome the external load (force and power production). The
contractile element of the muscle (CE) has the ability to generate force, and thus allows
the muscles to generate torque in the joints, which in turn allow movements of the
human body and overcoming of the external load by the system of levers (bones and
joints).
Muscles pre-stretch elastic tissues. For the muscle to function reactiveelastically, before the advent of external loads (e.g. for running this is the time interval
before the foot contacts the ground) it needs to be isometrically contracted (precontraction), and to tighten the series elastic tissues (i.e., to remove the slack). Since in
that situation the muscle is stiffer than the serial elastic tissues, which are lengthened
by external load and accumulate energy, serial elastic tissue acts as a spring which
returns that same (there is some hysteresis) energy back afterward. In this way,
muscles function more economically (saving metabolic energy and relying more on
elastic energy), but also improves its ability to generate force.
Muscles have a role in the transfer of energy from one joint to another. The
phenomenon of energy transfer from joint to joint (Prilutsky & Zatsiorsky, 1994) is
a very interesting mechanism that along with reactive-elastic function allows costeffective functioning of the human body. An illustrative example of energy transfer is
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a function of hamstrings. M. quadriceps extends the knee joint, and if the length of
your hamstring is the same (isometric contraction) i.e., such as a non-elastic rope,
extension of the knee will ‘transfer’ over the hamstring to hip extension too. In this way
m. Quadriceps extends the hip with the help of coordinated actions of the hamstring
muscles. These ’energy transfer’ phenomena occur in all bi-articulated muscles (ones
that cross two joints).
The implications of this phenomenon are very interesting if we take into
account the distribution of the muscles in the body. During running approximately
80% of energy is used to accelerate/decelerate the segments of the body. In order to
improve efficiency (reduce energy cost), the amount of mass in the distal segments
should be as small as possible (this will reduce the moment of inertia). This is why
the calf is bi-articulated muscle (m. gastrocnemius) and pennate. Pennate structure of
m. gastrocnemius enables the production of higher isometric force for the same muscle
mass compared to a spindle-shaped (parallel) structure. To enable the transfer of
energy from the much larger and stronger knee extensor muscles of the proximal part
of the leg (m. quadriceps) to extension (plantar flexion) of the foot, m. gastrocnemius
crosses both joints (knee and ankle) and as an in the hamstring example, functions
isometric-reactive-elastic. In this way, it reduces the moment of inertia and provides
a stronger extension of the foot. Truly intelligent solution of the Mother Nature
(for Evolutionist readers) or God (for Intelligent Design readers)!
Muscles facilitate other muscles by loading them eccentrically. This function of
the muscles is also very interesting. Because the muscles are placed at an angle in each
joint, they cause different moments (torques) in different axes. In practice, this means
that every muscle causes flexion/extension, adduction/abduction, and external/internal
rotation in different proportions. For this reason, our movements are mostly spiral and
diagonal (as one school in physical therapy – PNF uses as one of its basic principles), and
not ‘Robotic’ in one plane. Because the ability of the muscles to generate force decreases
with increasing shortening velocity (force-velocity relationship), the action of adjacent
muscles in a certain way can reduce the speed of the main muscle shortening and thus
enable the generation of larger forces in the target plane of the movement. Example
of this mechanism is seen during the acceleration phase in running, where most of
the propulsive force is generated by m. gluteus and m. quadriceps. Since m. gluteus
produce extension and external rotation of the hip, torsion of the pelvis and use of the
arm swings will lead to the internal rotation in the hip of the standing leg, which has
the effect of the ‘elongation’ (i.e. reducing shortening velocity) of the m. gluteus, which
as a result, according to the force-velocity relationship, contributes to the greater force
production in the direction of the hip extension, and thus the greater propulsive forces
and greater acceleration of the body.
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The human body is an extremely complex and ‘intelligent’ machine, whose
modes of operations we are just beginning to understand. Error in the past approaches
was that we tried to explain the functioning of the whole by understanding the
characteristics of the parts. However, things do not work that way. The whole is not a
simple collection of the parts (see substance – form complementary pair). Thus, the
function of the muscles should not be analyzed separately, but in the way they fit into
the functioning of the whole body, the way they ‘cooperate’ with each other, in order
to maximize the effectiveness, efficiency and produce movement. The reductionist
approach to the analysis of movement should be replaced by newer methods of nonlinear open and adaptable complex systems, which studies the self-organization of the
motor system and views the variability in the movement as something useful not only
as a “noise and error.
Grand Unified Theory
It bears repeating that I am not trying to sell you certain model as the best or
the only objective truth, but instead promote multi-model thinking, pragmatic realism,
phenomenology, and integrative pluralism. These models are only Small World models
of the complex reality. Some serve as a warm comfort, some serve certain ideologies of
training, but all are wrong. For that reason, you need to keep in mind that these are just
simplified representations of the complex reality and neither solves the Is/Ought Gap.
One model that I developed over the years (Jovanovic, 2018), in an attempt to
combine my current understanding is Grand Unified Theory (GUT) of Everything
(sports performance related) (see Figure 2.27).
IS
OUGHT
Protect from the Downside
Task
via Posi�va
Is/Ought Gap
Quality
Form
Rate-Limiter
Substance
Environment
via Nega�va
Organism
Invest in the Upside
Figure 2.27. Grand Unified Theory
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In the GUT model we are still facing the Is/Ought Gap. Quality is manifested under
constraints of Task, Environment, and Organism (individual athlete). This is quite
similar, if not the same with the Constraints-led Approach (CLA) to motor learning
and skill acquisition (Davids, Button & Bennett, 2008; Renshaw, Davids & Savelsbergh,
2012; Chow et al., 2016). This is pragmatic-realist position (Maul, 2013; Guyon,
Falissard & Kop, 2017), where more analytical (e.g., objective) qualities are manifested
under real-world conditions. In the above example of Formula 1 car, you might test
curve performance of a driver in laboratory settings, but driver manifests bad quality
when pressured by other opponents and heavy rain. That IS the current state (place of
things). What needs to be done about it? Better traction? By adding better tires, removing
weight? By teaching the driver how to enter the curve better? By adding more practices
under pressure or by figuring out that he was under heavy stress lately because his wife
was cheating him and his daughter is seriously sick. These are all under the domain of
OUGHT.
From what is written already, the OUGHT part is about identifying (or guessing
through iterations, MVP, randomization and pure luck) bottleneck or the rate limiter
and deciding what to do about it. Multiple complementary aspects are involved here:
substance - form, via Positiva - via Negativa, and investment in the Upside -protection
from the Downside. I believe that these aspects, implemented in the Agile Periodization
framework, help in bridging the Is/Ought Gap.
GUT model is also scale-free, which means it can be applied to different levels
of analysis, from a single cell to a nation. It represents a more holistic approach as
opposed to reductionistic physiological/biomechanical models and analysis, as well
as ideological training systems. It is a great tool both for decision making, and when
analyzing other training systems to figure out which aspect is being emphasized and
why (e.g., Westside Barbell vs Boris Sheiko).
Shu-Ha-Ri and Bruce Lee’s punch
Aikido master Endō Seishirō shihan stated (“Shuhari,” 2019):
“It is known that, when we learn or train in something, we pass
through the stages of shu, ha, and ri. These stages are explained as follows.
In shu, we repeat the forms and discipline ourselves so that our bodies
absorb the forms that our forebears created. We remain faithful to these
forms with no deviation. Next, in the stage of ha, once we have disciplined
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ourselves to acquire the forms and movements, we make innovations.
In this process the forms may be broken and discarded. Finally, in ri, we
completely depart from the forms, open the door to creative technique,
and arrive in a place where we act in accordance with what our heart/mind
desires, unhindered while not overstepping laws.”
Bruce Lee stated the following:
“Before I learned the art, a punch was just a punch, and a kick, just a kick.
After I learned the art, a punch was no longer a punch, a kick, no longer a kick.
Now that I understand the art, a punch is just a punch and a kick is just a
kick.”
I think that as physical preparation coaches we pass through these stages. I
remember when I started, I was obsessed with the correct execution of exercises,
classifications, and periodization models. Particularly in finding THE optimal and right
ones. Later I realized there are numerous solutions, whose application depends on the
context. Everything was “It depends”. But now I think I am in a more ri phase, where “a
punch is just a punch and a kick is just a kick”. Yeah, everything depends, but there are
stable and best practices, but also explorations and creativity around those. Tradition
is there for a reason24 but one doesn’t need to be a slave to it. Unfortunately, one cannot
jump phases, and simplicity of an expert can be seen as ignorance of the beginner.
I am thus more than aware that this manual will not be attractive to readers in the
shu phase, who might be looking for a simplified “do this” type of a book, but rather to
those in ha phase by presenting various options and progressions, and most probably
to those in ri phase questioning contemporary models and practices.
Summary
I am glad we have reached this point so I can focus on more pragmatic topics in
this manual. I am pretty sure that going through this chapter was painful, but it was
needed since I am approaching planning from another perspective, rather than the
physiological/biomechanical analytic perspective. My viewpoint is Agile Periodization,
where I realize that we are experimenting and dealing with a bunch of uncertainties. The
Outlined rationales are the building blocks of Agile Periodization and were essential to
be introduced and understood before digging into more practical stuff in the chapters
that follow. Let’s go!
24 See Lindy Effect (Taleb, 2012; “Lindy effect,” 2019).
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3 Exercises
What is the point of exercise classification? To impress girls with differentiating
between exercises for the long and short head of the biceps muscle? To pass the
biomechanics class exam?
None of this, of course. The purpose of classification is not to create a place of
things, but a forum for action. Creating categories from place of things perspective always
comes with two issues. First one is that creating more than needed precision with
categories represent exercise in futility and a rabbit hole (e.g., why having categories
of exercises for long vs. short biceps head if you do not plan using them somehow?).
There are always unlimited ways to classify exercises, depending on what criteria is
being used. Besides, these criteria will be usually in some type of a conflict (later in
the chapter you will see few of those on figures). Second issue is that because there is
a category, you will have a proclivity to use it in planning, when there is no practical
significance in doing so. For example, having vertical and horizontal press category
will create more proclivity do designate training slots for them, but they might not need
special treatment (for example with strength generalists, like team sport athletes).
The goal of exercise classification is thus to help you in planning and to simplify
complexity (i.e., Small World model) and to direct your decision making. It bears
repeating that categories are artificial, and that border is fuzzy rather than either/or,
which means that some exercises can belong to multiple groups (e.g., is split squat
single leg or double leg movement?), and exercises from a particular group can differ
(e.g., step-ups vs lateral lunges - one is vertical and the other is lateral, although both
are single leg movement). It also bears repeating Jordan B. Peterson: “Categories
are constructed in relationship to their functional significance”. This means that
categorization will depend on the potential use, particularly if you work with strength
specialists (e.g., powerlifters, strongman, weightlifters, and heavy athletics like a shot
put) or strength generalists (e.g., everyone else that uses resistance training to help in
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achieving performance in something else, like team sports athletes, combat athletes or
what have you).
General vs. Specific
Strength specialists might prefer to utilize classification based on specificity or
how similar particular exercises are to competitive exercises. For example, powerlifter
might classify exercises using their similarity to competitive bench press, squat, and
deadlift. One common approach (Small World, or mental model) that implements this
idea is a simple classification to general exercises and specific exercises (see Figure 3.1):
General category
Specific category
Specificity
Figure 3.1. Exercise classification based on specificity into general and specific. Note the fuzzy border
between groups, rather than either/or distinction
According to Grand Unified Theory (GUT; see the previous chapter) model,
general exercises usually develop some innate (latent) quality (substance) by providing
an overload, and specific exercises express that potential (form) through skill
development and manifestation (see Figure 3.2). This dichotomous thinking (either/
or: either you overload with general mean or you transform with specific, or develop vs.
express dichotomy) is quite common, although not many coaches are aware of using it.
For example, improve VO2max (potential) and your running performance in the game
will improve, or in a shot put improve your strength using bench press and transform
it by doing a shot put.
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Skill/Manifesta�on
Form
Substance
Specific
General
Quality/Overload
Figure 3.2. Substance and Form of the Grand Unified
Theory applied to general versus specific exercises
Keep in mind that this is also a Small World model and that different camps utilize
this model (or other models) differently. For example, a shot putter (who we might
consider strength specialist in this case) might use incline bench press to improve the
potential and utilize shot putting to manifest (or transform) that potential. This apparent
dichotomy of ability versus skills (or substance and form) is being used in some schools
(to my knowledge in American T&F schools) while being critiqued in others (for example
in Bondarchuk’s approach to hammer throwing (Bondarchuk & Yessis, 2007, 2010)).
Another example might be the use of specialized exercises in Westside powerlifting
(Simmons, 2007) to target specific quality or weak links (i.e., potential), which will be
later converted to competitive performance using the most specific lifts (i.e., form). In
contrary, Sheiko powerlifting school (Sheiko, 2018) might approach things differently
(using a different Small World model) by being less dichotomous and treat specific lifts
(bench press, squat and deadlift) as developmental and skill dependent, rather than just
a sole manifestation of underlying potential that is being developed with specialized
exercises. Again, these are all Small World representations, and as we all know, both
schools of powerlifting are more than successful in developing world-class lifters. An
example from soccer might involve arguing with the head coach who says: “Players
never squat in a game” (referring to form), while you try to convey that they do need to
strength train to improve underlying potential or substance (to improve performance on
the pitch, but also to protect from the Downside, i.e., injuries).
Extension of this model (by including additional categories in general vs. specific
continuum) is the model by Dr. Anatoly Bondarchuk (Bondarchuk & Yessis, 2007, 2010)
which is quite famous and utilized in track and field circles (see Figure 3.3)
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{
Specific Development
Exercises (SDE)
Specific Preparatory Exercises (SPE)
}
Substance
Barbell Strategy
Specificity
Form
Pursue Upside
Compe��ve
Exercises (CE)
Avoid Downside
General Preparatory Exercises (GPE)
Figure 3.3. Exercise classification based on the work of Dr. Anatoly Bondarchuk
(Bondarchuk & Yessis, 2007, 2010) and its relationship to the barbell strategy
In addition to GUT’s substance-form complementary pair, utilization of CE and
SDE exercises can be considered investing in the Upside (improving performance), while
utilization of the SPE and particularly GE exercises can be regarded as protection from
the Downside (making sure you don’t fuck yourself up with too specific work). For a
powerlifter, this might mean doing some stability work, stretching, or horizontal and
vertical pulling (should we call it Vanilla training - see the previous chapter) or some
aerobic conditioning or bodyweight strength circuits (to improve Mongoose Persistence?;
also see the previous chapter) which can all help in protecting from the Downside.
I have personally used Bondarchuk categories in my work and previous writings,
and I believe they are a beneficial mental model. I have used them to help me categorize
speed, power, and other strength and conditioning components, and I will continue to
use them as a tool in the toolbox (i.e., multi-model thinker), particularly for strength
specialists (or athletes that compete in cm/kg/sec sports). The dealbreaker issue I have
with this model is that its categories depend on what we use to judging specificity.
The categories of exercises might be very different for a powerlifter, as opposed to a
rugby player. Take into account that specificity and hence exercises categorization
for a rugby player which involves sprinting, acceleration, jump, ruck, maul, shoulder
tackling and so forth. That being said, it is hard to pinpoint the exact category of an
exercise in complex team sports (i.e., strength generalists). After all, most if not all
strength exercises for team sport athlete will be in the GPE and SPE category. In that
way, although very useful as a general viewpoint, Bondarchuk categorization is not
very useful (lower functional significance) in team sports or for strength generalists.
For this reason, I will utilize few different categorizations that I have found to have the
biggest forum for action, which will guide my decision making and help me to decide
what are the big buckets (or planning slots) that I have to take care of. The following
categorization models are mostly aimed at strength generalists, although they can
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STRENGTH TRAINING MANUAL Volume One
be utilized for strength specialists, potentially as sub-categories of the SPE and GE
categories in the Bondarchuk categorization model.
Grinding vs. Ballistic
Grinding movements are slow, controlled, compound movements (e.g., squats,
deadlift, bench press) with constant tension, while Ballistic movements are fast and
explosive (e.g., jump squats, hang cleans) with a burst of tension followed by relaxation,
and they usually involve a flight of the body or the implement (e.g., barbell or a medicine
ball). Additional categories involve Control movements (mostly for Vanilla Training,
e.g., local and global stabilizers, but also has a lot similarity with complex movements
category later in the chapter which demands symmetry and stabilization) and Other
(that annoying category for exercises you do not know where they belong to). As with
any categorization, it is hard to draw a fine line between categories since there are some
similarities between them. Here, Figure 3.4 illustrates one possible classification of the
Slow tempos
Eccentric
Additional weight
isoHolds
Action
isoPush
Isometric
isoSwitch
Grinding
isoCatch
Segments
* overcoming immovable object
* quickly switching sides/extremities (e.g. hamstring
bridge)
* catch after an airborne phase (similar to catching
exercises in the ballistic category)
* your normal lifting, but it can be solely concentric
(e.g. sled pushing)
Concentric
Other
* holding position (e.g., side bridge)
* Accommodating resistance, isokinetic, etc
Compound
Isolation
Ground
Olympic Lifting
Strength Training
Movements
Hang
Blocks
Fast Grinding
*See categories for Jumping
Explosive (Static Position)
Reactive (Countermovement)
Ballistic
Jumping
Continuous (Rhythmical)
Catching (EccentricDeceleration)
Throwing
Sprinting
Relaxed
Maximal
* Similar to isoCatch
*Same categories as Jumping
*Mostly Sled variations
Other
Control
Other
* Exercises belonging mostly to the Vanilla training
category (e.g., local/global stabilizers)
* Those annoying exercises that you do not know
where they belong
Figure 3.4. Categorization of movements based on their type
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MLADEN JOVANOVIĆ
movements. Please keep in mind that there are numerous ways to classify and enter
the rabbit hole - I have included only the categories that I think have the most forum for
action when working with strength generalists.
Figure 3.5 contains the hypothetical (and very simplified) relationship between
Grinding, Ballistic, and Control towards developing Anaconda Strength, Armor
Building, Arrow, Vanilla Training and Mongoose Persistence qualities.
Grinding
Ballis�c
Control
Armor
Building
4
3
4
Anaconda
Strength
5
4
2
Arrow
2
5
1
Mongoose
Persistence
3
2
3
Vanilla
Training
1
1
5
Figure 3.5. What qualities development are grinding, ballistic and control movements good for.
The higher the number is, the better fit it is. Keep in mind that this is just a speculative highly
simplified model.
Grinding movements
Figure 3.4 contains the additional classification of the grinding movements
based on muscle action and the number of segments involved. Using muscle action,
we can classify grinding movements to predominantly (1) eccentric, (2) isometric, (3)
concentric, and (4) other25.
Eccentric category usually involves an emphasis on slow lowering phase
(eccentric phase) or somehow adding extra weight on the lowering part (e.g., leg press
with two legs, lower with one).
Isometric category involves categories coined by colleague Alex Natera (see
Figure 3.4 for details). IsoHold can also belong to Control movements, while isoCatch is
very similar, if not the same to catch exercises in the ballistic category.
The Concentric category are your regular lifting movements, although specific
apparatus can be used to perform movements concentrically only (e.g., heavy sled
pushes and pulls).
Other category involves, well everything else, from accommodating resistance to
using EMS (Electric Muscle Stimulation).
When it comes to the number of segments involved, the simplest classification
involves isolated movements (e.g., chest flies, biceps curls) and compound movements
(e.g., bench press, pull-ups).
25 It is always useful to have the “Other” category, in which you put items you do not know where they
belong. After the number of these items increases, it might be a time to revisit your overall classification
model. Having said this, classification is also “iterative”, rather than set in stone. This also means that the
classifications in this book are “work in progress”, rather than the final picture.
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Ballistic movements
Figure 3.4 contains additional classification of the ballistic movements to (1)
Olympic lifting, (2) Fast Grinding (think of dynamic effort squats or bench press with
50-60% 1RM (Simmons, 2007)), (3) Jumping, (4) Throwing, (5) Sprinting (mostly
heavy sled towing/pushing exercises), and of course the (6) Other category.
Olympic lifting is further classified based on the starting positions: (1) ground,
(2) hang, or (3) blocks. Additional classification might involve catching position (e.g.,
full, power, muscle), but that would be an overkill for this simple big picture overview.
Additional subcategories for fast grinding, jumping and throwing are categories
based on the action, and they involve (1) explosive from a static position (e.g., think of
squat jumps from pause), (2) reactive (e.g., counter-movement jump or depth jump),
(3) continuous (e.g. rhythmical jump squats that can be all-out, or sub-maximal
rhythmical), and (4) catching oriented (e.g., jump and land). We can probably add other
categories here as well, pick up every other variation that one might use for jumping,
throwing and fast grinding movements (e.g., combining grinding movement with
ballistic in a contrast super-set or what have you).
Control movements
Control movements category is a bloody mess, and involves everything from core
stuff, to BOSU ball and breathing fuckarounditis. Vanilla Training mostly utilizes these
movements with the aim of protecting from the Downside.
Simple vs. Complex
What can be put on top of grinding and ballistic classification (one can include
control category here, but I will leave it out to simplify26) are simple versus complex
movements. This way we get a quadrant: on the x-axis, we have movement time (a
long time for grinding movements, and short time for ballistic movements), and on the
y-axis, we have complexity axis (from lower complexity to higher complexity). I like to
refer to this model as Time-Complexity quadrants (TCQ) (See Figure 3.6).
26 Please beware the "curse" of classification, particularly quadrants and matrix which results when we
combine two or more criteria. Sometimes we are "forced" to fill in the spots to fit the model. Remember
that you can have a blank spot in your model and not everything should fit nicely. But sometimes we can
‘predict’ novel things (e.g., periodic table allowed us to predict yet unknown elements found later)
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Complex
Simple
Movement Complexity
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Ballis�c
Grinding
Movement Time
Figure 3.6. Time-Complexity quadrants
To make the need for such a categorization model easier to understand, think of a
few examples for each quadrant (see Figure 3.7). Complex refers to how many segments
are utilized and whether the stability is compromised. It might be hard to pinpoint to
exact biomechanics principles, but from a phenomenological perspective, it is quite
easy to understand (e.g., “I know it when I see it”).
Grinding-Simple: Bench Press
Grinding-Complex: Standing (Split Squat) Landmine Press
Ballistic-Simple: Hang Clean
Ballistic-Complex: SLRDL to Clean with Box Step (an example of Frans Bosch
(Bosch, 2015) drills), anything ballistic with a water ball, or some other fancy explosive
step up
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Movement Complexity
STRENGTH TRAINING MANUAL Volume One
Ballis�c
Grinding
Movement Time
Figure 3.7. Example of TCQ exercises
Exercises from all quadrants can be represented in the training program, in a
higher or lower degree, depending on the objectives, needs, and context. TCQ allow a
place for things, particularly when someone starts bombarding you with fancy Instagram
exercises. Now you have a drawer to put them in, and use them if and when needed.
Fundamental movement patterns
Not sure who figured out this categorization thing first, but I guess that Ian King
(King, 2002) was one of the first to write about it. Different coaches utilized different
classifications, of which I am the most thankful to Dan John (John & Tsatsouline, 2011;
John, 2013) (who added loaded carries which I am more than grateful for), Michael
Boyle (Boyle, Verstegen & Cosgrove, 2010; Boyle, 2016) (mainly for his view on single
leg movements), and Joe Kenn (Kenn, 2003) (whose book I consider one of the most
important books written for generalist strength training). Figure 3.8 contains my
current classification of the fundamental movement patterns in the lowest resolution:
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MLADEN JOVANOVIĆ
Grinding
Ballis�c
Push
Push
Pull
Pull
Squat
Squat
Hinge
Hinge
Carry/Push
Rota�on
Core
Other
Other
Figure 3.8. Fundamental human movements (for strength training purpose)27
27 Different authors name these categories differently. For example, Squat category is usually named
Knee-Dominant or Lower Body Push, while Hinge is oftentimes named Hip-Dominant or Lower Body Pull.
Few things might be missing, e.g., calves, hip flexor. These can be in the “Other” category, but if they
become important aspect of your program, you are more than free to create additional categories.
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STRENGTH TRAINING MANUAL Volume One
As mentioned multiple times through this manual, categories should be as simple
as possible (lowest resolution), while still being functionally significant (provide a
forum for action). Some of these categories could be further divided into horizontal/
vertical (e.g., horizontal push, vertical push; horizontal jump, vertical jump) or double
leg/single leg (single leg squatting movements, double leg squatting movements), but
that can quickly become an exercise in futility (which I will do anyway). If it suits your
programming and hence provides functional significance, then please do include some
extra categories. I need something as simple as possible, to which I can easily reflect on
to see if I am hitting all the major movements that I have to address - hint: 1/N heuristic
and MVP).
It is always good to include the “Other” category. I have learned this from the
“productivity movement”. It is like the bottom drawer in which you put things you are
not sure how to categorize. Once this drawer fills up too much, well I guess it is time to
use a different categorization model. It bears repeating that everything in this manual
are simple heuristics and strategies that you can use as a starting point and modify to
suit your needs. For example, one can put “Vanilla” training exercises (breathing drills,
DNS rolling on the ground, PRI drills and so forth) into category “Other”.
One can also include gymnastic movements such as falls, rolls, and various holds
as special categories, which are quite useful but for now, we can leave them in the
“Other” category. If these represent a major part of your training philosophy, then, by
all means, I encourage you to make your own categories.
Some exercises can be combined into multiple movements, and that is not
worrisome, but something to keep in mind (remember the fuzzy borders? One exercise
can belong to multiple categories). I am not trying to split the hair with 100% accurate
categorization here. Remember that we are more into functional significance and
simplicity, rather than 100% correct categorization.
Grinding movement patterns
Figure 3.9 contains the more detailed classification of the grinding movements
into fundamental movement patterns
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Push
Vertical
Pull
Single Arm
Horizontal
Double Arm
* Same categories as
* Same categories as
Horizontal
Push
Double Leg
Supported
* Double leg?! E.g., split squats,
Bulgarian split squats, lateral split squats
Static
Squat (Lower Body Push)
Vertical
Single Leg
Unsupported
Accelerative
Horizontal
Lateral
Rotational
Decelerative
Grinding Movements
Single Leg
Hinge (Lower Body Pull)
* Same categories as
Accelera�ve
Straight
Bent
Double Leg
Straight
Bent
Forward
Carry/Sled
Backward
Lateral
Anterior
Core
Posterior
Lateral
Rotational
Other
Figure 3.9. Fundamental movement patterns of the grinding movements
The classification, as well as pretty much everything else in this manual, is work
in progress. The classification of the single leg movements is very much influenced
by Michael Boyle classification (Boyle, Verstegen & Cosgrove, 2010; Boyle, 2016). As
you can see in Figure 3.9, supported single leg movements (e.g., split squats) can be
considered double leg movements with a staggered stance. These things can be argued
until the cows come home, so the key message is again forum for action, rather than
an ideally precise place of things (see Figure 1.1). Figure 3.10 contains some example
exercises for the main categories of the grinding movements.
Push
Push Ups
Bench Press
DB Bench Press
KB Press
Standing Cable Press
Ring Push Ups
Pull
Cable Row
Pull Ups
Lat Pull Downs
Inverted Row
Bench DB Rows
Prone Rows
Squat
Front Squat
Hex Bar Squat
Split Squat
Bulgarian Split Squat
Lateral Squat
Lunges
Hinge
Romanian Deadli�
Hyperextension
Deadli�
Hip Thrust
SLDL
SL Hyperextensions
Carry/Push
Farmers Walk w/Hexbar
Overhead KB Carry
Single Side
Overhead Waterball
Sled Marches
Lateral Sled Marches
Core
Roll-Out
Pallof Press
L-Sit
Side Bridge
RKC Plank
Hangling Leg Li�s
Other
Breathing Drills
Hip Ext Rota�ons
DNS Rolls
Falls
TYWL Shoulder
Calves?
Figure 3.10. Exercises examples for major categories of the grinding movements
One thing you could do, and I will come back to this later in this chapter, is to enlist
all the exercises you can coach and perform (or your athletes can perform) under your
constraints. You can include whatever sub-categories you prefer if they are actionable
(provide a forum for action) to you.
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Ballistic movement patterns
Figure 3.11 contains the more detailed classification of the ballistic movements.
For the most part, categories are quite similar to grinding movements (after all, the
anatomy is the same).
Push
Horizontal
Vertical
Pull
Single Arm
Double Arm
* Same categories as Horizontal
* Same categories as Push, although
Pull movements are generally "tricky" to
be performed ballistically
Squat (Lower Body Push)
Hinge (Lower Body Pull)
Single Leg
Double Leg
* Same as with Pull categories, generally
"tricky" to be performed ballistically
Rotation
Ground
Ballistic Movements
Starting Position
Hang
Blocks
Full
Olympic lifting
Power
Finishing Position
Muscle
Split
Pull
Forward
Sled
Backward
Lateral
Other
Figure 3.11. Fundamental movement patterns of the ballistic movements
As can be seen from Figure 3.11 pulling and hinge movements are a bit tricky when
it comes to ballistic movements (i.e., hang clean can be considered ballistic hip hinge),
but either way, Figure 3.12 contains few exercise examples.
Push
Explosive Push Up
Bench Throws
Medball Throws
Pull
Explosive Bench Pull
Medball Slams
Explosive Pull-Up
Squat
Scissor Jumps
Squat Jumps
Hex Bar Jumps
Hinge
Broad Jump
KB Swings
Hanging Clean
Rota�on
Rota�onal Medball
Explosive Landmine Rot
Chops with band
Other
Pogo Jumps
Hip Flexor throws
Figure 3.12. Exercises examples for major categories of the ballistic movements
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An additional category is Olympic Lifting, which I classified in this example
using starting and catching positions. Figure 3.13 depicts something that I like to call
the Olympic Lifting Matrix (although jerk is not very well represented here) and can
be useful in understanding different Olympic lifting variations. Again, the purpose is
not the ideal place of things, but a functional forum for action. With these examples, I
want to motivate you to start thinking in terms of your forum for action when devising
categories.
Star�ng Posi�on
Ground
Low hang
(below the knees)
Hang
(squat)
Hang
(hip hinge)
High Hang
Blocks
(low, med, high)
Full Catch
(Olympic)
Catching Posi�on
Squat Catch
(thigh parallel)
Power
(high squat)
Power Hang Snatch
Power Hang Clean
Muscle
(straight legs)
Split Catch
Shrug
Pull
High Pull From
Blocks
(Clean Grip)
High Pull
Figure 3.13. Classification matrix for the Olympic weight lifting exercises
Combining movement patterns
with the Time-Complexity quadrants
To make our lives very miserable, we can connect Time-Complexity quadrants
(see Figure 3.6 and 3.7) with movement patterns. I do not think this is particularly
useful to be done with extreme precision - but it is essential to understand the
difference between simple and complex categories. Figure 3.14 contains an example
model, although the ballistic side (left side) is applied to more things besides lifting
ballistically (e.g., sprinting, jumping, throwing). Digging more into this will demand
another manual (manual on Speed and Power; which I am working on), but for the sake
of completeness, it is mentioned here.
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Simple
Movement Complexity
STRENGTH TRAINING MANUAL Volume One
Speed
Overhead sprints w/water
bags and rota�ons
Push
Standing Landmine Press
Agility/COD
Partner drills (Tags)
Pull
Standing Keiser Row
Reac�ve
Skips w/rota�ons & water
bags
Squat
Single Leg, Offset &
Unstable varia�ons
Explosive
Step-up with hip lock
Hinge
Single Leg, Offset &
Unstable varia�ons
Deccelera�on
Various catches & drops
w/perturba�ons
Carry/Push
Water filled objects
Low intensity
Low box, ladder
w/perturba�ons
Core
Chops & Li�s
Speed
Hill sprints, Flat sprints
Push
Bench Press
Agility/COD
Simple COD drills
Pull
Pull-Ups
Reac�ve
Skips, hudrles
Squat
Front Squat
Explosive
Trap Bar jumps
Hinge
RDL
Deccelera�on
Drop jumps
Carry/Push
Trap Bar Carry, Heavy Sled
March
Low intensity
Low box, ladder
Core
Roll-out
Ballis�c
Grinding
Movement Time
Figure 3.14. Combination of the time-complexity quadrant and fundamental movement patterns
Exercise Priority/Emphasis/Importance
Having an exercise pool for grinding and ballistic movement patterns is a necessary
starting point, but not sufficient in deciding how to create a training program. The
problem is how to choose the exercises? Which one is more important, which one should
have higher priority?
To solve these problems, coaches usually utilize some type of exercises
classification based on what they think is important. Importance can mean different
things to different coaches and athletes of course, but the goal is to simplify decision
making when selecting what exercises to perform. The most common classification
based on importance is classification to main exercises and assistance exercises. Figure
3.15 contains example categories from Jim Wendler (Wendler & Koss, 2013; Wendler,
2017), Joe Kenn (Kenn, 2003) and Mike Tuchscherer (Tuchscherer, 2008).
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MLADEN JOVANOVIĆ
Jim Wendler
Joe Kenn
Mike Tuchscherer
Main Li�s
Supplement Li�s
Assistance Li�s
Founda�on Exercises
Supplemental
Major Assistance
Secondary Assistance
Compe��on
Assistance
Supplemental
General
Figure 3.15. Exercise classification based on importance
Importance is again a complex concept and can mean different things. Mike
Tuchscherer utilizes specificity to competition lifts as a criterion, and his classification
model is very similar to Bondarchuk model (see Figure 3.3). Thus, importance in this
strength specialist example refers to specificity and similarity with the main movements
(squat, bench press, and deadlift). Figure 3.16 contains example exercises for each
category for squat, bench press and deadlift.
Squat
Bench Press
Deadli�
Compe��on
Squat
Bench Press
Deadli�
Assistance
Pin squats
Pause squat
Squat with chains
Pause bench
Board press
Pin press
Sling shot bench
Incline bench press
Deadli� + bands
Alternate stance deadli�
Deficit deadli�
Supplemental
Leg press
Single leg
Good morning
Military press
DB bench
Dips
Close grip incline
RDL
Good morning
Front squat
General
Figure 3.16. Mike Tuchscherer classification
Specific exercises can be selected based on the individual lifters qualities and
needs, although a generic approach can exist (see Bayesian updating in Chapter 1).
When it comes to strength generalist approach to exercise importance
classification, usually we have some idea of the biggest bang for the bucks, amount of
joints and muscle mass involved, or exercises that allow highest loads. But again, there
is no right or wrong answer here. An example of major grinding categories can be seen
in Figure 3.17
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STRENGTH TRAINING MANUAL Volume One
Push
Pull
Squat
Hinge
Core
Carry
Main Li�s
Bench Press
Pull-Ups
Front Squat
RDL
Roll-Out
Hex Bar Carry
Supplement Li�s
KB Overhead
Press
Inverted Rows
Split Squat
Hyperextension Side Bridge
Double KB
Overhead
Assistance Li�s
Ring Push-Ups
Face Pulls
Lateral Lunges
Single Leg Bridge Palloff Press
Suitcase Carry
Figure 3.17. Importance categories for major grinding movement patterns
But sometimes, these importance categories represent variants of the lifts under
a given category (to hit sub-categories, such as horizontal vs. vertical, and single vs.
double leg) without any specific importance weight. Nothing, absolutely nothing wrong
with that. It bears repeating that these classifications should help you provide a forum
for action under your constraints, context, and philosophy. For example, these could
be exercises you are confident coaching and performing, or you have equipment for
(this represents a bottom-up approach to planning). Figure 3.18 contains an example
exercises for major categories when one doesn’t have access to barbells:
Push
Pull
Squat
Hinge
Core
Carry
Varia�on #1
Ring Push-Ups
Ring Pull-Ups
Goblet Squat
SL RDL
Roll-out
Overhead DB
Varia�on #2
DB Press
Inverted Rows
DB Step Up
Hip Thrust
Side Bridge
Suitcase DB
Varia�on #3
Dips
DB Ver�cal Row DB Lateral Lunge Hyperextension Landmine Rot
Lateral Sled
Figure 3.18. Example of exercise variations for major grinding categories when
there is no access to barbells
The exact number of variants depends on the program you might be running
with your team or yourself. If you prefer more or fewer categories (e.g., horizontal vs.
vertical, single vs. double leg) you are more than free to do it. This is just a framework
to help you make more informed decisions based on importance or emphasis.
Session Position
Unfortunately, not every exercise can be given the same emphasis in a single
workout. For example, we will see better (faster) progress in exercises that are performed
first (since you are exercising fresh) rather than later in the workout. There are few
heuristics, such as “Perform compound movements earlier in the workout, isolation
later”, or “Do ballistic movements at the beginning”, but these rules are meant to
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be broken if a situation demands it. For example, you might be doing full body session
(which generally indicates that all movement categories are represented in a single
session, give or take), and doing heavy deadlifts will leave you fucked up for everything
else. So, you might opt for doing core stuff first (to warm-up), upper body stuff and
then finish with a heavy deadlift, drink shake and banana, hit the shower and go home.
To alleviate this emphasis problem, one can (please notice my choice of words;
I’ve used can and not must) rotate the order of exercises (see Figure 3.19) across
sessions:
Emphasis 1
Emphasis 2
Emphasis 3
Emphasis 4
Emphasis 5
Emphasis 6
Session A
Squat Movement
Pull Movement
Hinge Movement
Push Movement
Carry
Core
Session B
Hinge Movement
Push Movement
Squat Movement
Pull Movement
Carry
Core
Session C
Pull Movement
Squat Movement
Push Movement
Hinge Movement
Carry
Core
Session D
Push Movement
Hinge Movement
Pull Movement
Squat Movement
Carry
Core
Figure 3.19. Rotation of exercises, so that each movement pattern receives an equal amount of
attention (assuming earlier in the workout means more attention)
Use of the Slots and Combinatorics
By combining exercise importance categorization with session position, one can
easily create an evolved planning system. One such system is Joe Kenn’s Tier System
(Kenn, 2003) which was highly influential on my development as a strength coach.
If we consider that a given session position receives more emphasis, it is logical to
insert more important exercises to more emphasized positions. This way, we combine
the two approaches (see Figure 3.20). I call this the Slots approach. The slot is a functional
cell (or unit) on which exercise selection and other categories are applied. I like the term
slots since slots need to be filled.
Main
Main
Supplement
Assistance
Any
Any
Session A
Squat Movement
Pull Movement
Hinge Movement
Push Movement
Carry
Core
Session B
Hinge Movement
Push Movement
Squat Movement
Pull Movement
Carry
Core
Session C
Pull Movement
Squat Movement
Push Movement
Hinge Movement
Carry
Core
Session D
Push Movement
Hinge Movement
Pull Movement
Squat Movement
Carry
Core
Figure 3.20. Combining session emphasis/position with exercises importance
The Slots approach can be expanded to involve other things, besides exercise
importance. For example, categories can be qualities, methods, volume, toughness and
so forth (Figure 3.21).
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Exercise
Category
Main
Main
Supplement
Assistance
Quality
Arrow
Anaconda
Armor
Vanilla
Method
5/4/3/2/1
5x5 @70
3x10
3x10
Volume
High
High
Medium
Easy
Easy
Easy
Session A
Squat Movement
Pull Movement
Hinge Movement
Push Movement
Carry
Core
Toughness
Hard
Easy
Medium
Medium
Easy
Easy
Session B
Hinge Movement
Push Movement
Squat Movement
Pull Movement
Carry
Core
Session C
Pull Movement
Squat Movement
Push Movement
Hinge Movement
Carry
Core
Session D
Push Movement
Hinge Movement
Pull Movement
Squat Movement
Carry
Core
Figure 3.21. Variations in categories can create evolved systems
One can also flip the table, where the order of exercises is the same (i.e., movement
pattern), while the categories change across workouts (Figure 3.22):
Quality
Method
Volume
Toughness
Arrow
5/4/3/2/1
High
Hard
Anaconda
5x5 @70%
Low
Easy
Armor
3x10
Medium
Medium
Vanilla
3x10
Low
Easy
Movement
Squat Movement
Pull Movement
Hinge Movement
Push Movement
Carry
Core
Session A
Session B
Session C
Session D
Figure 3.22 One can also transpose the table. This way the order of the exercises (movement patterns)
will be the same while other categories will differ across days
Playing with the above, based on the level of the lifter, the number of sessions,
categories and so forth, can create very evolved systems. Since I am not trying to sell
you any in particular, consider this Slot system a combinatorics framework that you can
use to analyze and create workout plans.
If we assume that different qualities, methods, volumes, and toughness are
achieved with different set and rep schemes, we can eventually create the following
quadrant for every slot (or cell):
Varied
Same Exercises
Same Set and Rep Schemes
Varied Exercises
Same Set and Rep Schemes
Same Exercises
Varied Set and Rep Schemes
Varied Exercises
Varied Set and Rep Schemes
Set and Rep Schemes
Same
Exercises
Varied
Same
Figure 3.23. Variation Quadrant
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MLADEN JOVANOVIĆ
For example, one might use different exercises for upper body pushing (e.g., bench
press, military press, DB press, Dips) and stick to one set and rep scheme (e.g., 3x10
@65% 1RM), but also use same exercise for lower body squat (e.g., front squat), but use
different set and rep schemes (e.g., 3x30sec isometrics, 3/2/1 and 2x12). This can work
very well if one needs more upper body mass while sticking to leg size and improving
strength or if someone wants to emphasize the most specific exercise or quality and so
forth. Keep in mind that categorizations of qualities, methods, and movement patterns
are up to you and the athletes you coach. Thus, you are free to experiment with this
framework.
Slots can also be linked (e.g., apply same set and rep schemes for upper body
pulling and hinge movements, or apply different set and rep schemes for the same
objective or quality). Possible combinations are unlimited, and this represents a very
fruitful tool or framework that I will expand upon in Chapter 5, where I am going to talk
about horizontal and vertical planning, as well as divisive and un-divisive approaches.
The slots approach, and hence the variation quadrant can be applied to strength
specialist as well. For example, Mike Tuchscherer has days with different specificity and
movement pattern slots. It bears repeating that this represents a tool, rather than a
specific sequence you need to follow. I highly suggest checking the Tier system by Joe
Kenn (Kenn, 2003), as an example of how this approach28 is applied to athletic strength
training (strength generalist).
The use of Functional Units
in Team Sessions
In the ideal world, you will not be constrained with exercise choices, and you
would choose the best exercise to achieve a given goal. But in the real world, we are
limited and restricted with the equipment, coaching awareness, time, preferences, and
so forth. Most of the time, we will have a whole team in the gym, some athletes more
experienced, most of them clueless. For this reason, exercise selection needs to take
into account equipment, flow in the gym, the experience of the individuals (besides
their needs), how much attention you need for a given exercise (i.e., you probably need
to coach RDLs more than you need to coach push-ups) and so forth.
Most gyms are organized (if you are lucky) using functional units (see Figure
28 It is actually the opposite - I have been highly influenced by Joe Kenn Tier System (Kenn, 2003), that
understanding combinatorics involved led me to find common denominators and propose the slots
approach.
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STRENGTH TRAINING MANUAL Volume One
3.24), most likely around the squat rack. Although this doesn’t necessarily need to be
the case, the idea of having units is particularly useful if you are working with more
than one athlete at the same time.
Group A
Group B
Squat Rack
Squat Rack
Barbell, plates, movable bench
Mobility
Barbell, plates, movable bench
Mobility
Core
Bands, slideboards, massage
tables, foam
rollers…
Core
Bands, slideboards, massage
tables, foam
rollers…
Mini bands, rollouts,
paralle�es…
Mini bands, rollouts,
paralle�es…
Dumbbells Sta�on
Dumbbells Sta�on
DBs, KBs, Rings, bands, boxes,
slide-boards, benches
DBs, KBs, Rings, bands, boxes,
slide-boards, benches
Figure 3.24. Functional units. Gyms are usually organized around the squat racks.
Figure 3.24 depicts two functional units that involve four stops, where for
example 2x8 (2 athletes per station) athletes can work out at the same time. This way
one can maintain some type of order during the workout, mainly if there is a time limit
to finish (e.g. you have 20 min to finish these exercises).
Sometimes specific equipment is limited, and thus shared, as outlined in Figure
3.25, and this needs to be taken into account when planning.
Group A
Group B
Squat Rack
Squat Rack
Barbell, plates, movable bench
Mobility
Barbell, plates, movable bench
Mobility
Core
Bands, slideboards, massage
tables, foam
rollers…
Bands, slideboards, massage
tables, foam
rollers…
Mini bands, roll- outs, paralle�es…
Dumbbells Sta�on
DBs, KBs, Rings, bands, boxes,
slide-boards, benches
Dumbbells Sta�on
DBs, KBs, Rings, bands, boxes,
slide-boards, benches
Figure 3.25. Functional units with shared area/equipment
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MLADEN JOVANOVIĆ
The functional units represent archetypal bottom-up planning approach, where
one starts with the constraints of the equipment, rather than top-down of what needs
to be done for the next 6 months. One approach to exercise selection is depicted in
Figure 3.26, where two circuits are performed on the same functional unit (e.g., 20min
for the first circuit and 20 min for the second).
Squat Rack Sta�on
Mobility Sta�on
DB Sta�on
Core Sta�on
Circuit A
Split Squat
Lat Stretch
KB Press
Roll-out
Circuit B
Bench Press
Stretch
SL RDL
Palloff Press
Figure 3.26. Exercises selection based on the equipment and functional unit constraints
Proper organization will maintain the flow between multiple athletes and avoid
any potential bottlenecks. Sometimes you do need to see it in action in order to pinpoint
potential issues with the equipment and the flow. If you are a single coach, or there is
a insufficient number of coaches, you need to be very selective with coaching intensive
exercises and limit it to one per circuit,and hopefully located very close between the
groups. In examples here, you will probably stick to coaching Split Squat at the squat
rack station. If you have multiple exercises that you need to be present at, you will be
having a hard time coaching and you will eventually have to decide what is of a greater
importance at the moment.
You also need to pay close attention to minimize athletes asking you stuff while
you are coaching. For example, athlete interrupts you while you are coaching Split
Squat to ask you how much they need to lift and for how many reps on the KB Press. For
this reason, particularly for coaching groups, I prefer to use a percent-based approach
and give some flexibility to athletes (see Chapter 5), rather than give them full freedom.
Workout card can be personalized and given to athletes (unless you have soccer athletes
who keep losing their workout cards), or printed somewhere centrally on a bigger paper
or using some type of a projector or touch screen with athletes and exercises enlisted.
These strategies will be covered in more detail in Chapter 5.
1RM relationships
Since I am a proponent of percent-based approach (as a general framework, or
as a starting point of implementation of the other methodologies), how does one know
1RMs (or one-repetition-maximums) for exercises? Next chapter will deal with 1RMs in
detail, mainly how they are estimated for the main movements (see Figure 3.15), which
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STRENGTH TRAINING MANUAL Volume One
is another reason why they are considered to be main. But how does one know 1RMs for
all the other exercises? For example, if I know someone’s bench press 1RM, how can I
prescribe DB Bench Press?
Before expanding, it is important to state my opinion regarding 1RMs. 1RMs are
not goals in itself - just because I am using 1RMs to prescribe training, doesn’t mean the
objective of training is solely to increase 1RMs. Thus, 1RMs serve more of a prescriptive
role, rather than descriptive. Next chapter will expand more on these concepts, but it
was important to state them to prevent readers from jumping to conclusions so easily.
As you will see, sometimes testing 1RMs is not necessary, and definitely, it is not needed
for all assistance movements.
Having said this, how does one estimate 1RMs of all assistance movements?
Dan Baker (Baker, 2015) was one of the first to my knowledge to suggest the
following table (Figure 3.27)
Upper Body Press
Bench Press
100%
Decline Press
105%
Incline Press
80%
Narrow Grip BP
90%
Close Grip BP
80%
DB Bench Press
each 33%
Push Press
75%
Military Press
55%
Press Behind Neck
55%
DB Overhead Press
17.5%
Upper Body Pull
Supinated Pull-Up
100%
Pronated Pull-Up
95%
Supinated Pull-Down
95%
Pronated Pull-Down
85%
Wide Grip Front PLD
80%
Wide Behind Neck PLD
75%
Seated Row
75%
Bench Pull
65%
Upright Row
50%
1-arm DB Row
each 33%
Lower Body Squat and Hinge
Full Squat
100%
Front Squat
80%
Overhead Squat
70%
Lunge
40%
Step-Up
40%
1-leg Squats
40%
Lateral Lunge
25%
Romanian DL
75%
Power Shrug
85%
Clean Pull
85%
Figure 3.27. Dan Baker’s 1RMs relationship table (Baker, 2015)
For example, if you know your or your athlete’s back squat 1RM, let’s say 150kg,
then you can expect that he or she is able to lift approximately 75% of 150kg in the
Romanian Deadlift (or RDL), which is 110kg. If one lifts 120kg in the bench press, his
1RM in the dumbbell bench press is approximately 33% of 120kg, or 40kg (each hand).
Of course, this varies for every individual. The point is not being precise, but having
some prior that we can update (see Chapter 1).
It is easy to jump to the conclusion, that there is something wrong with someone
lifting 150kg in the back squat, but not being able to lift 110kg in the RDL. But that is
not the purpose of this table - the aim is, when the new exercise is introduced, one
can develop a MVP (minimum viable product) and start with that. It is not to identify
weaknesses (e.g., comparing clean to front squat, although useful sometimes; see GUT
and substance - form complementary pair, where front squat is a potential one should
realize or manifest in the clean), but to have a rough gauge to help prescribe weights
and reps.
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MLADEN JOVANOVIĆ
From Chapter 1 you remember that we always make prediction mistakes, but I
want to make sure that those are Type I errors (undershooting). For this reason, we
usually don’t use 1RMs, but EDMs (Every Day Maximum), which is approximately 8090% of 1RM. This makes predictions conservative and most likely undershooting the
real 1RMs (which is better than overshooting, since you can always increase the weight,
plus one feels much better being able to do MORE rather than LESS of what is being
prescribed). But again, the precise prediction is not the goal - the goal is a forum for
action, or having something good enough for you to start implementing (without losing
time testing and finding the perfect estimate) and iterating. Next chapter will go deeper
into estimation through iteration approach to 1RM estimation.
For this reason, Dan Baker table is extremely useful for the first iteration,
when one knows 1RMs/EDMs of the main moves but doesn’t know 1RMs for all other
assistance exercises.
Searching the web (Boyle, 2011; Millette, 2014; Shute, 2015; Thibaudeau, 2015;
“Olympic Weightlifting Calculator,” 2017; Waxman, 2017) and from my personal
experience, I managed to create the following 1RM tables for upper body, lower body
and combined. Missing values were input using the script I wrote in the R language
(RStudio Team, 2016; R Core Team, 2018). First, I filled in the known relationships,
and then I let the iterative algorithm to find the missing values. Perfect? Hell no, but a
good starting point. Just don’t be a stupid and try to predict 1RM in the hang clean from
barbell curls. That being said, try to stick to the same movement pattern for the most
reliable prediction.
Upper Body
Figure 3.28 contains relationship matrix for the upper body push and pull
movements. Ideally, you want to stick within movement pattern when it comes to
prediction, although combining the two is possible, but be conservative.
Let’s say that one wants to predict military press from known bench press.
Finding military press on the rows and bench press on the columns indicate that the
relationship is around 55%.
Military Press = 0.55 x Bench Press
So, if your bench press is 120kg, military press is around 66kg. Again, this is a
starting rough estimate, which will differ from person to person.
For exercises where you are lifting your bodyweight (BW), such as dips and pullup variations, one needs to take BW into account. For example, if you weight 85kg and
lift 40kg in the pull-up for 1 rep (1RM), then your 1RM in the pull-up is 85kg + 40kg,
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STRENGTH TRAINING MANUAL Volume One
which is equal 125kg. As you will read in the next chapter, one should use 125kg (total
system 1RM) when prescribing strength training using a percent-based system, rather
Preacher Curl
Single Arm DB Row
Upright Row
Bench Pull
Seated Row
Wide Grip Behind Neck PD
Wide Grip Front PD
Pronated Pull Down
Supinated Pull Down
Pull-Up
Chin-Up
DB Overhead Press
Millitary Press
Push Press
DB Bench Press
Floor Press
Close Grip BP
Dips
Incline Bench Press
Decline Bench Press
Bench Press
than 40kg (only external load).
Bench Press
100%
95%
125%
85%
125%
110%
285%
135%
180%
500%
95%
100%
100%
110%
120%
125%
125%
145%
190%
270%
250%
Decline Bench Press
105%
100%
130%
90%
130%
115%
300%
145%
185%
525%
100%
105%
105%
115%
125%
130%
130%
150%
200%
285%
260%
Incline Bench Press
80%
75%
100%
65%
100%
90%
230%
110%
140%
400%
75%
80%
80%
90%
95%
100%
100%
115%
150%
215%
200%
Dips
120%
115%
150%
100%
150%
130%
340%
160%
210%
595%
110%
120%
120%
130%
140%
150%
150%
170%
225%
320%
300%
Close Grip BP
80%
75%
100%
65%
100%
90%
230%
110%
140%
400%
75%
80%
80%
90%
95%
100%
100%
115%
150%
215%
200%
Floor Press
90%
85%
115%
75%
115%
100%
255%
120%
160%
450%
85%
90%
90%
100%
105%
115%
115%
130%
170%
240%
225%
DB Bench Press
35%
35%
45%
30%
45%
40%
100%
50%
60%
175%
35%
35%
35%
40%
40%
45%
45%
50%
65%
95%
85%
Push Press
75%
70%
90%
60%
90%
80%
210%
100%
125%
365%
70%
75%
75%
80%
85%
90%
90%
105%
140%
200%
185%
Millitary Press
55%
55%
70%
45%
70%
60%
160%
80%
100%
280%
55%
55%
55%
60%
65%
70%
70%
80%
105%
150%
140%
DB Overhead Press
20%
20%
25%
15%
25%
20%
55%
25%
35%
100%
20%
20%
20%
20%
25%
25%
25%
30%
40%
55%
50%
Chin-Up
105%
100%
135%
90%
135%
120%
305%
145%
190%
530%
100%
105%
105%
120%
125%
135%
135%
155%
200%
285%
265%
Pull-Up
100%
95%
125%
85%
125%
110%
290%
135%
180%
505%
95%
100%
100%
110%
120%
125%
125%
145%
190%
270%
250%
Supinated Pull Down
100%
95%
125%
85%
125%
110%
290%
135%
180%
505%
95%
100%
100%
110%
120%
125%
125%
145%
190%
270%
250%
Pronated Pull Down
90%
85%
115%
75%
115%
100%
260%
125%
160%
450%
85%
90%
90%
100%
105%
115%
115%
130%
170%
245%
225%
Wide Grip Front PD
85%
80%
105%
70%
105%
95%
245%
115%
150%
425%
80%
85%
85%
95%
100%
105%
105%
120%
160%
230%
210%
Wide Grip Behind Neck PD
80%
75%
100%
65%
100%
90%
225%
110%
140%
400%
75%
80%
80%
90%
95%
100%
100%
115%
150%
215%
200%
Seated Row
80%
75%
100%
65%
100%
90%
225%
110%
140%
400%
75%
80%
80%
90%
95%
100%
100%
115%
150%
215%
200%
Bench Pull
70%
65%
85%
60%
85%
75%
200%
95%
125%
350%
65%
70%
70%
75%
80%
85%
85%
100%
130%
185%
175%
Upright Row
55%
50%
65%
45%
65%
60%
150%
70%
95%
265%
50%
55%
55%
60%
60%
65%
65%
75%
100%
145%
135%
Single Arm DB Row
35%
35%
45%
30%
45%
40%
105%
50%
65%
185%
35%
35%
35%
40%
45%
45%
45%
55%
70%
100%
95%
Preacher Curl
40%
40%
50%
35%
50%
45%
115%
55%
70%
200%
40%
40%
40%
45%
45%
50%
50%
60%
75%
110%
100%
Figure 3.28. Upper body exercises 1RM relationships
Let’s say you want to predict dips 1RM from known pull-ups 1RM. From the upper
body relationship matrix, dips are 120% of pull-ups, so:
Dips = 1.2 x Pull-Up
Dips = 1.2 x 125kg
Dips = 150kg
According to this formula, 1RM in dips is 150kg. Deducting BW, one gets 150kg 85kg, or 65kg, which represents external load attached on the dip belt. If some of these
predictions seem too high, you should always lean on the side of conservatism.
What if you have multiple known exercises and want to predict the unknown
one? For example, you might know bench press, military press, and pull-ups, but you
want to predict incline bench press.
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MLADEN JOVANOVIĆ
Bench Press = 120kg
Military Press = 75kg
Pull-Ups = 110kg
Using relationship matrix and the above we get three predictions for the incline
bench press:
Incline BP = 0.8 x Bench Press = 0.8 x 120kg = 96kg
Incline BP = 1.4 x Military Press = 1.4 x 75kg = 105kg
Incline BP = 0.8 x Pull-Ups = 0.8 x 110kg = 88kg
We got 96, 105, and 88kg. Which one to use? The simplest approach would be to
take the average:
Incline BP = (96kg + 105kg + 88kg) / 3 = 96kg
Other approach, which quickly becomes exercise in futility, is to give higher
weight (importance) to the estimate using the most similar exercises (e.g. more weight
given to bench press than pull-up). This is called weighted average. Let’s say we give
bench press 5 weight, 4 to military press and 2 to pull-up:
Incline BP = (5 x 96kg + 4 x 105kg + 2 x 88kg) / (5 + 4+ 2)
Incline BP = (480 + 420 + 176) / 11
Incline BP = 1076 / 11 = 98kg
If you don’t mind this approach of giving more weight to the most similar
exercise, be my guest and use it. At the end of the day, it is still an estimate just like
everything else.
Lower Body
Figure 3.29 contains relationship matrix between lower body squat (push) and
hinge (pull), and Olympic lifting exercises. The calculus is precisely the same as with
the upper body movements
From Figure 3.29 we can see that Clean is around 75% of Back Squat. So, someone
back squatting 170kg, should probably clean around 125kg. The key word here is should.
For example, for someone never tried the clean before, you can be confident that this
value is much lower. If we look at the GUT model, the potential is there (i.e., back squat
performance), but the athlete needs to learn how to express or manifest it in the clean
(i.e., realization). More advanced lifters might have clean higher than 75% of the back
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STRENGTH TRAINING MANUAL Volume One
squat, and you might use that as a starting hypothesis for experimentation through
iteration (agile periodization) and assume that maybe, just maybe, this athlete might
need to improve strength (i.e., potential) rather than trying to chase more volume
of specific realization work (i.e., Olympic lifting). I am definitely not against this
application of the relationship matrix, but I would be very cautious when making bold
Back Squat
Front Squat
Deadli�
Overhead Squat
Split Squat
Lunge
Step-Up
Good Morning
Lateral Split Squat
Lateral Lunge
Romanian Deadli�
1-Leg Romanian Deadli�
Hip Thrust
1-Leg Hip Thrust
Clean and Jerk
Snatch
Clean
Jerk
Power Clean
Power Snatch
Hang Clean
Hang Snatch
Muscle Snatch
Power Shrug
Clean Pull
Snatch Pull
claims.
Back Squat
100%
120%
80%
145%
200%
250%
250%
200%
335%
400%
135%
220%
100%
180%
135%
155%
135%
125%
155%
180%
140%
160%
255%
110%
120%
135%
Front Squat
85%
100%
70%
125%
170%
215%
215%
170%
285%
345%
115%
190%
85%
155%
120%
135%
115%
110%
135%
155%
120%
140%
220%
95%
100%
115%
Deadli�
125%
145%
100%
180%
250%
315%
315%
250%
415%
500%
165%
280%
125%
225%
165%
195%
165%
155%
190%
230%
175%
205%
320%
140%
150%
170%
Overhead Squat
70%
80%
55%
100%
140%
175%
175%
140%
230%
275%
90%
155%
70%
125%
90%
105%
90%
85%
105%
125%
95%
110%
175%
75%
80%
95%
Split Squat
50%
60%
40%
70%
100%
125%
125%
100%
165%
200%
65%
110%
50%
90%
65%
80%
65%
65%
75%
90%
70%
80%
130%
55%
60%
70%
Lunge
40%
45%
30%
60%
80%
100%
100%
80%
135%
160%
55%
90%
40%
75%
55%
60%
50%
50%
60%
75%
55%
65%
105%
45%
45%
55%
Step-Up
40%
45%
30%
60%
80%
100%
100%
80%
135%
160%
55%
90%
40%
75%
55%
60%
50%
50%
60%
75%
55%
65%
105%
45%
45%
55%
Good Morning
50%
60%
40%
70%
100%
125%
125%
100%
165%
200%
65%
110%
50%
90%
65%
80%
65%
65%
75%
90%
70%
80%
130%
55%
60%
70%
Lateral Split Squat
30%
35%
25%
45%
60%
75%
75%
60%
100%
120%
40%
65%
30%
55%
40%
45%
40%
40%
45%
55%
40%
50%
75%
35%
35%
40%
Lateral Lunge
25%
30%
20%
35%
50%
65%
65%
50%
85%
100%
35%
55%
25%
45%
35%
40%
35%
30%
40%
45%
35%
40%
65%
30%
30%
35%
Romanian Deadli�
75%
85%
60%
110%
150%
190%
190%
150%
250%
300%
100%
165%
75%
135%
100%
115%
100%
95%
115%
135%
105%
120%
190%
85%
90%
100%
1-Leg Romanian Deadli�
45%
50%
35%
65%
90%
115%
115%
90%
150%
180%
60%
100%
45%
80%
60%
70%
60%
55%
70%
80%
60%
75%
115%
50%
55%
60%
Hip Thrust
100%
115%
80%
145%
200%
250%
250%
200%
335%
400%
135%
220%
100%
180%
130%
155%
130%
125%
155%
180%
140%
160%
255%
110%
120%
135%
1-Leg Hip Thrust
55%
65%
45%
80%
110%
140%
140%
110%
185%
220%
75%
120%
55%
100%
75%
85%
70%
70%
85%
100%
75%
90%
140%
60%
65%
75%
Clean and Jerk
75%
85%
60%
110%
150%
190%
190%
150%
250%
300%
100%
170%
75%
135%
100%
125%
95%
95%
115%
140%
105%
125%
195%
85%
90%
105%
Snatch
65%
75%
50%
95%
130%
160%
160%
130%
215%
260%
85%
145%
65%
115%
80%
100%
85%
80%
100%
120%
90%
105%
165%
70%
75%
90%
Clean
75%
90%
60%
110%
155%
190%
190%
155%
255%
305%
100%
170%
75%
140%
105%
120%
100%
95%
120%
140%
105%
125%
195%
85%
90%
105%
Jerk
80%
90%
65%
115%
160%
200%
200%
160%
265%
320%
105%
175%
80%
145%
105%
125%
105%
100%
120%
145%
110%
130%
205%
90%
95%
110%
Power Clean
65%
75%
50%
95%
130%
160%
160%
130%
215%
260%
85%
145%
65%
120%
85%
100%
85%
80%
100%
120%
90%
105%
165%
70%
75%
90%
Power Snatch
55%
65%
45%
80%
110%
135%
135%
110%
185%
220%
75%
120%
55%
100%
70%
85%
70%
70%
85%
100%
75%
90%
140%
60%
65%
75%
Hang Clean
70%
85%
60%
105%
145%
180%
180%
145%
240%
290%
95%
160%
70%
130%
95%
115%
95%
90%
110%
130%
100%
115%
185%
80%
85%
100%
Hang Snatch
60%
70%
50%
90%
125%
155%
155%
125%
205%
245%
80%
135%
60%
110%
80%
95%
80%
75%
95%
110%
85%
100%
160%
70%
75%
85%
Muscle Snatch
40%
45%
30%
55%
80%
100%
100%
80%
130%
155%
50%
85%
40%
70%
50%
60%
50%
50%
60%
70%
55%
65%
100%
45%
45%
55%
Power Shrug
90%
105%
70%
130%
180%
225%
225%
180%
300%
360%
120%
200%
90%
165%
120%
140%
120%
115%
140%
165%
125%
145%
230%
100%
105%
125%
Clean Pull
85%
100%
70%
120%
170%
210%
210%
170%
280%
340%
115%
190%
85%
155%
110%
130%
110%
105%
130%
155%
120%
135%
215%
95%
100%
115%
Snatch Pull
75%
85%
60%
105%
145%
185%
185%
145%
245%
295%
100%
165%
75%
135%
95%
110%
95%
90%
115%
135%
100%
120%
185%
80%
85%
100%
Figure 3.29. Lower body exercises 1RM relationships
Combined
Figure 3.30 contains major exercises from upper body push and pull, lower body
squat and hinge, and Olympic lifting categories. Since the numbers are estimated using
the iterative algorithm, they might differ between tables (Figure 3.28 and Figure 3.29).
98
Bench Press
Military Press
Push Press
DB Bench Press
Chin-Up
Bench Pull
Single Arm DB Row
Back Squat
Front Squat
Deadli�
Romanian Deadli�
Overhead Squat
Split Squat
Hip Thrust
Clean and Jerk
Clean
Jerk
Snatch
Power Clean
Power Snatch
Muscle Snatch
Clean Pull
Snatch Pull
MLADEN JOVANOVIĆ
Bench Press
100%
180%
135%
285%
95%
145%
270%
75%
100%
60%
100%
110%
155%
75%
100%
100%
95%
120%
110%
140%
195%
90%
105%
Military Press
55%
100%
80%
165%
55%
80%
155%
45%
50%
35%
60%
65%
90%
45%
55%
55%
55%
70%
65%
80%
115%
50%
60%
Push Press
75%
125%
100%
210%
70%
105%
200%
55%
70%
45%
75%
80%
115%
55%
75%
75%
70%
90%
85%
105%
145%
65%
80%
DB Bench Press
35%
60%
45%
100%
35%
50%
95%
25%
30%
20%
35%
40%
55%
25%
35%
35%
35%
40%
40%
50%
70%
30%
35%
Chin-Up
105%
185%
140%
300%
100%
155%
285%
80%
100%
65%
110%
115%
160%
80%
105%
105%
100%
125%
120%
145%
210%
95%
110%
Bench Pull
70%
120%
95%
200%
65%
100%
190%
55%
65%
40%
70%
75%
105%
55%
70%
70%
65%
80%
80%
95%
135%
65%
75%
Single Arm DB Row
35%
65%
50%
105%
35%
55%
100%
30%
35%
25%
40%
40%
55%
30%
35%
35%
35%
45%
45%
50%
75%
35%
40%
Back Squat
135%
220%
175%
375%
125%
190%
355%
100%
120%
80%
135%
145%
200%
100%
135%
135%
125%
155%
155%
180%
255%
120%
135%
Front Squat
100%
190%
145%
310%
100%
155%
295%
85%
100%
65%
110%
120%
165%
85%
120%
110%
105%
130%
125%
150%
215%
100%
115%
Deadli�
165%
285%
220%
470%
155%
235%
445%
125%
150%
100%
165%
180%
250%
125%
165%
165%
155%
195%
190%
230%
320%
150%
170%
Romanian Deadli�
100%
170%
130%
280%
95%
140%
265%
75%
90%
60%
100%
110%
150%
75%
100%
100%
95%
115%
115%
135%
190%
90%
100%
Overhead Squat
90%
160%
120%
260%
85%
130%
245%
70%
85%
55%
90%
100%
140%
70%
90%
90%
85%
105%
105%
125%
175%
80%
95%
Split Squat
65%
115%
90%
185%
60%
95%
175%
50%
60%
40%
65%
70%
100%
50%
65%
65%
60%
75%
75%
90%
130%
60%
70%
Hip Thrust
130%
230%
175%
375%
125%
190%
355%
100%
120%
80%
135%
145%
200%
100%
130%
130%
125%
155%
150%
180%
255%
120%
135%
Clean and Jerk
100%
180%
130%
280%
95%
140%
265%
75%
85%
60%
100%
110%
150%
75%
100%
95%
95%
125%
115%
140%
195%
90%
105%
Clean
100%
175%
135%
290%
95%
145%
275%
75%
90%
60%
105%
110%
155%
75%
105%
100%
95%
120%
120%
140%
200%
90%
105%
Jerk
105%
185%
140%
300%
100%
150%
285%
80%
95%
65%
105%
115%
160%
80%
105%
105%
100%
125%
120%
145%
205%
95%
110%
Snatch
85%
145%
115%
240%
80%
120%
230%
65%
75%
50%
85%
95%
130%
65%
80%
85%
80%
100%
100%
120%
165%
75%
90%
Power Clean
90%
150%
115%
250%
80%
125%
235%
65%
80%
55%
90%
95%
130%
65%
90%
85%
85%
100%
100%
120%
170%
80%
90%
Power Snatch
70%
125%
95%
205%
70%
105%
195%
55%
65%
45%
75%
80%
110%
55%
70%
70%
70%
85%
85%
100%
140%
65%
75%
Muscle Snatch
50%
90%
70%
145%
50%
75%
140%
40%
45%
30%
50%
55%
80%
40%
50%
50%
50%
60%
60%
70%
100%
45%
55%
Clean Pull
110%
195%
150%
315%
105%
160%
300%
85%
100%
70%
115%
120%
170%
85%
110%
110%
105%
130%
130%
155%
215%
100%
115%
Snatch Pull
95%
165%
130%
275%
90%
140%
260%
75%
90%
60%
100%
105%
145%
75%
95%
95%
90%
110%
110%
135%
185%
85%
100%
Figure 3.30. Combined exercises 1RM relationships
What should you do next?
Here is what I suggest, and I found it very useful in my coaching practice, because
it reduces cognitive load every time I need to write a program (so I don’t need to reinvent
the wheel). It also revolves around the “bottom-up” approach (see Chapter 1). I suggest
you create an exercise pool. Just go to the gym, keep in mind the number of athletes you
are working with at the same time, their level, and equipment available and enlist as
many exercises you can think of following the covered categories (or come with your
own). I suggest using Microsoft Excel, Google Sheets or Apple Numbers to create such a
list. One such exercise list can be found in Chapter 7.
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Figure 3.31. Exercise pool in Excel
Trust me - enlist all the exercises you can think of, and keep updating the list as
soon something new crosses your mind. This is just a mental dump, and it will allow
you to easily find exercises later on, rather than breaking your head against the wall
every time you need to write a new program.
This filing system has a few columns (see Figure 3.31):
–– Name
–– Category (e.g., grinding, ballistic)
–– Pattern (e.g., push, pull, squat, hinge)
–– Variant (e.g., horizontal, vertical, single leg)
–– Relationship to the main exercise (e.g., 55% to Back Squat)
–– Percent of BW used (usually 0%, but 100% for dips and pull-ups)
–– Equipment used (useful to filter out exercises based on your equipment constraints)
–– Extra Note
You are more than welcome to come with your own list of exercises, and I think
it is extremely handy. You are also free to go with your individual columns, and add
additional ones, such as coaching dependent (for example if you need to be there to
observe and coach), and so forth.
Having this pool of exercises is VERY usable in a constrained environment (and
pretty much all of them are). You have limited equipment, limited focus to observe and
correct everyone on every exercise, and you have multiple athletes in the gym at the
same time, so you are pretty much “bound” and you need to figure out what CAN be
done quickly (i.e., bottom-up planning). Using this exercise pool (or list) allows you to
quickly sort, filter and figure out the best options without a sweat.
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MLADEN JOVANOVIĆ
The next chapter will expand on the topic of 1RM estimation, as well as how to
prescribe using percent-based approach.
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STRENGTH TRAINING MANUAL Volume One
4 Prescription
Before diving deep into the planning section, it is important to understand
the basis of the percent-based approach to strength training, particularly what these
percentages are based upon, how to test 1RM and prescribe a training while using it
as a reference point, how to compare individuals and other topics. As explained in
the previous chapter, we made a rough division of the exercises into grinding and
ballistic movements. Most of this chapter will deal with the grinding movements, but
applications to ballistic movements will be covered as well in the later section. The
reason for this is to avoid confusion - prescribing for ballistic movements is a bit trickier
and it is important to digest grinding ones first for easier comprehension. Let’s start by
discussing the concept of intensity.
Three components of Intensity
(Load, Intent, Exertion)
One of the most important concepts in strength training is intensity. Unfortunately,
intensity is not a clear-cut concept, and different coaches and lab coats define it in
different ways. For this reason, I am providing my own explanation of the concept.
Intensity in strength training has the following three components:
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MLADEN JOVANOVIĆ
Load
Load-Exer�on
Table
Load-Velocity
Profile
weight, %1RM
Exer�on
Reps, RPE, RIR, V-drop, V-stop
Intent
Initial velocity
?? RIR-Velocity
Profile
Figure 4.1. Intensity Trinity; or three components of intensity
Load – relates to the weight the athlete is lifting in a given exercise expressed
either in absolute terms (i.e., kilograms or pound), or in relative terms using the percentage
of one’s 1RM (% of 1RM). For example, if an athlete is performing bench press with
100kg (absolute load), and his known 1RM is 110kg, then the load is 90% (relative load).
Additional way to describe and prescribe intensity would be using repetition-maximums
or RM. For example 12RM load is the weight that can be lifted for 12 reps without technical
failure. This type of load prescription combines load with the exertion component and
utilized load-exertion relationship or table (see later in the chapter). Novel way to express
load is using velocity (i.e., initial rep should have mean concentric velocity of 0.8 m/s),
but this type of load description utilizes load-velocity profile (see later in this chapter)
and demands special equipment for measurement.
Sometimes athletes’ bodyweight needs to be taken into account (e.g., chins, pullups, dips and even squats). For this reason we differ between external load (external
weight attached, using barbell or dip belt) and total system load (which is total load that
athlete is lifting or overcoming, usually bodyweight plus external load). As you will read
later in this chapter, we can use both when prescribing using a percent-based approach.
Intent – relates to an athlete’s will to perform a repetition of a given exercise
with maximum possible acceleration and speed, usually in the concentric phase. Effort
could be maximal (the synonym would be C.A.T. – compensatory acceleration training)
or it could be sub-maximal (lifting with certain tempo). Tempo is usually prescribed
using the following nomenclature:
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STRENGTH TRAINING MANUAL Volume One
top-stop / lowering-eccentric / bottom-stop / lifting-concentric
For example, prescribing squat with 1/3/2/X tempo means the following: hold
for 1 second at the top, lower down for 3 seconds, hold for 2 seconds at the bottom, and
lift as fast as possible (“X”) on the way up. These tend to become a bit confusing in the
pulling movements and deadlift, where one starts with the concentric movement first.
In this case I suggest writing tempo with a note to avoid confusion.
Different authors and coaches prescribe lifting tempo using different order of the
phases than defined here (e.g., lowering-eccentric / bottom-stop / lifting-concentric
/ top-stop), or only using three numbers (e.g., lowering-eccentric / bottom-stop /
lifting). Nothing wrong with either, just make sure to communicate it clearly.
Exertion – relates to the proximity to failure in a given set. It seems reasonable
that the degree or level of exertion is substantially different when performing, e.g., 8
of 12 possible repetitions (12RM or 12 repetition max) with a given load (the common
nomenclature is 8(12) or 8 of 12) compared with performing maximum number of
repetitions (12(12) or 12 of 12). Exertion is usually expressed as reps in reserve (RIR), or
rate of perceived exertion (RPE) (Tuchscherer, 2008; Zourdos et al., 2016, 2019; Helms
et al., 2016, 2018a,b; Carzoli et al., 2017). Table 4.1 contains hypothetical relationship
between the two.
RIR
0
1
2
3
4
RPE
10 → Failure!
9
8
7
6
Table 4.1. Relationship between Reps In Reserve (RIR) and Rate of Perceived Exertion (RPE). This is
simplification, since relationship is not linear.
Please note that these are subjective ratings. This means that athletes give these
ratings after a given set is finished. Another implementation of these is conceptual which
is useful in planning and progression (as will be covered in Chapter 5). I personally
prefer to use RIR, because it is conceptually simpler, and I will use it in the load-exertion
tables and formulas (see later in this chapter).
Using the previous example, performing 8 reps with 12RM load represents submaximal exertion with 4 RIR. RPE is in this case around 6. Performing 12 reps with
12RM represents maximal exertion with 0 RIR and 10 RPE. Lab coats would probably
complain how these are non-linear and depend on the relative load (%1RM), body part,
exercise, gender, and the alignment of Alpha Centauri A with Proxima Centauri in the
closest galaxy to Milky Way. As stated numerous times already, I am not trying to provide
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MLADEN JOVANOVIĆ
precision, but meaning (forum for action). As you will read in the later in this chapter
and in Chapter 5, RIR represents an actionable concept for planning progressions in
training programs.
Besides RPE and RIR, there is a concept of relative intensity (RI) that express
exertion as percent of maximal reps. Using the same example, performing 8 reps with
12RM represents, 8 / 12 or 66% RI. Although some coaches prefer this approach, I am
not a big fan, since it is biased to reps being performed (e.g. compare 8 reps with 12RM
which is equal to 4RIR and 66% RI to 4 reps with 8RM which is also equal to 4RIR but
50% RI).
Novel ways to estimate exertion involve using velocity-stop and velocity-drop
(Jovanovic & Flanagan, 2014). These refer to how much, usually the concentric mean
velocity, drops compared to the fastest or initial rep. These are just a fancy way of
saying that closer to failure, the slower your movement (assuming maximal intent on
every repetition). These concepts will be explained later in this chapter when discussing
velocity-based training (VBT).
These three components of intensity are important to be differentiated and I will
stick to this terminology from now on.
Load-Max Reps Table
The more weight is on the barbell, the less reps one can perform. This relationship
is expressed with Load-Max Reps relationship. Of course Mr. Lab Coat, this relationship
depends on the age, gender, experience, type of exercise, body part and Einstein’s
Relativity Theory. But, as opposed to you, dear Mr. Lab Coat, we coaches need to take
less than perfect tool in helping us to get oriented and start from somewhere (and
we have athletes to coach; we cannot just claim “more research is needed”). If you
remember, Mr. Lab Coat, for the most part of our history we used geocentric model
of the Solar system (assuming Earth is in the centre and Sun revolves around Earth)
which, although factually wrong, allowed sailors and explorers to orient themselves.
One such simplistic and wrong, but very useful table, is Epley’s table (Epley, 1985;
Wood, Maddalozzo & Harter, 2002) or formula (Table 4.2) popularized by Jim Wendler
5/3/1 books (Wendler & Koss, 2013; Wendler, 2017)
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STRENGTH TRAINING MANUAL Volume One
Max Reps
% 1RM
1
100%
2
94%
3
91%
4
88%
5
86%
6
83%
7
81%
8
79%
9
77%
10
75%
Max Reps
% 1RM
11
73%
12
71%
13
70%
14
68%
15
67%
16
65%
17
64%
18
63%
19
61%
20
60%
Table 4.2. Epley’s Load-Max Reps table
This table can be represented with a simple equation:
%1RM = 1 / (0.0333 x MaxReps + 1)
or
MaxReps = 30.03 / %1RM - 30.03
Does this prediction formula works for everyone and for every exercise? No! But
it is simple enough to be useful. Besides, when we make prediction errors, and we do
make them, we want to make Type I errors (undershooting; see Chapter 1). More about
this later in this chapter.
You can use this table and formula as rough estimates. For example, you can
probably do 5 reps with approximately 85% 1RM.However, it must be noted again that
some individuals differ drastically. For this reason, use this prediction (and everything
else in this manual) as a simple prior that you update (see Bayesian updating in Chapter
1) as you collect more data. If needed, you can also make individualized Load-Max Reps
table by performing at least 3 sets to failure with different loads (e.g., 40, 60 and 80%
1RM) and then use linear or polynomial regression (or trying to find individualized
parameter, which according to Epley’s formula is equal to 0.0333 for the average
athlete). This can be done (or can be estimated from training logs using embedded
testing method from the Agile Periodization, which will be explained in Chapter 5) for
strength specialists, but most of the time, it is not needed for the strength generalists (nor
there is time to do so).
Epley’s table and formula can also be used to predict 1RM. For example, if you
lifted 100kg for 6 reps, according to Table 4.2 this represents 83% 1RM. To estimate
1RM, you need to divide 100kg with 0.83, which is equal to 120kg. Faster way, than
referring to Table 4.2 is using the following equation:
1RM = (Weight x Reps x 0.0333) + Weight
So if we plug in the 100kg and 6 reps we get:
1RM = (100kg x 6 reps x 0.0333) + 100kg
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MLADEN JOVANOVIĆ
1RM = 20 + 100
1RM = 120kg
The beauty of Epley’s equation is in its simplicity. And it is very easy to remember.
There are numerous uses of this simple equation, as you will soon see.
Load-Exertion Table
Combining load-max reps table with RIR as a metric of proximity to failure
(exertion), we get the next very usable table that is helpful in prescribing and analyzing
training programs (Table 4.3). This table represent one of the cornerstones of the
percent-based approach described in this manual.
Exer�on / Reps in Reserve (RIR)
% 1RM
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
Max reps
1 rep short
2 reps short
3 reps short
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Max reps
1 rep short
2 reps short
3 reps short
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
4 reps short 5 reps short
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
6 reps short
7 reps short
8 reps short
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1
2
3
4
5
6
7
8
9
10
11
12
13
1
2
3
4
5
6
7
8
9
10
11
12
9 reps short 10 reps short 11 reps short 12 reps short
1
2
3
4
5
6
7
8
9
10
11
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
1
2
3
4
5
6
7
8
Exer�on / Reps in Reserve (RIR)
# Reps
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
4 reps short 5 reps short
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
6 reps short
7 reps short
8 reps short
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
9 reps short 10 reps short 11 reps short 12 reps short
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
50%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
50%
49%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
50%
49%
48%
Table 4.3. Load-Exertion Table
The above two tables (Table 4.3) are identical, they are just organized in a different
way to help find either a number of reps that needs to be performed, or percentage that
needs to be used. Here are two examples:
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1. Training program calls for using 80% 1RM at 3 RIR. How many reps should be
performed in a set? Using the top table, seek for 80% row in “%1RM” column (or
close to it) and then find the intersect with 3 RIR column. The answer is 4-5 reps.
2. Training program calls for doing 5 reps at 2 RIR. What percentage should you use?
Using the bottom table, look for 5 reps row in the “# Reps” column, and then find
the intersect with 2 RIR column. The answer is around 81% 1RM.
The general rule of thumb (heuristic) would be that the more volume you perform
(be it number of sets in a single workout, or frequency of workouts) then the further
right you should go on the table (selected higher RIR). Later in Chapter 5 you will see
the application of this concept and the extension of the Load-Exertion table used to
planning progressions.
Similar to Load-Max reps table, Load-Exertion table can be represented by the
following equation:
%1RM = 1 / (0.0333 x (Reps + RIR) + 1)
or
Reps = (30.03 / %1RM) - (30.03 + RIR)
Let's apply these equations to a few examples. Training program calls for doing
5 reps at 2 RIR, what %1RM should one be using (given Epley’s equation as a prediction
model)? Let’s plug these into equation:
%1RM = 1 / (0.0333 x (Reps + RIR) + 1)
%1RM = 1 / (0.0333 x (5 + 2) + 1)
%1RM = 1 / (0.0333 x 7 + 1)
%1RM = 1 / (0.2331 + 1)
%1RM = 1 / 1.2331
%1RM = 81%
Let’s do another example. Training program calls for using 80% 1RM at 3 RIR.
How many reps should be performed in a set?
Reps = (30.03 / %1RM) - (30.03 + RIR)
Reps = (30.03 / 0.8) - (30.03 + 3)
Reps = 37.5375 - 33.03
Reps = 4.5
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Similarly to Load-Max Reps equation, we can use known weight, reps and RIR to
predict 1RM. The equation is the following:
1RM = (Weight x (Reps + RIR) x 0.0333) + Weight
This is very useful for ongoing monitoring and prediction of 1RM when athletes
provide RIR after each set. Let’s assume that athlete perform squats with 150kg for 3
reps, and give subjective rating of exertion level of 2RIR. Predicted 1RM is the following:
1RM = (Weight x (Reps + RIR) x 0.0333) + Weight
1RM = (150kg x (3 + 2) x 0.0333) + 150
1RM = (150kg x 5 x 0.0333) + 150
1RM = 24.975 + 150
1RM = 175kg
According to Epley’s model, predicted 1RM is 175kg. Let’s assume that after few
weeks of training similar workout is performed, with 160kg for 2 reps at 1RIR. Did the
athlete improve?
1RM = (Weight x (Reps + RIR) x 0.0333) + Weight
1RM = (160kg x (2 + 1) x 0.0333) + 160
1RM = (160kg x 3 x 0.0333) + 160
1RM = 15.984 + 160
1RM = 176kg
The new estimated 1RM is 176kg. Assuming reliable RIR feedback, it seems that
this individual is maintaining his or her level of strength (as estimated with predicted
1RM). This represent latent (or estimated) strength, since the true changes need to be
demonstrated with a proper test. Anyway, these predictions can be quite useful as a submaximal estimate, and hence can be done all the time (where true demonstrations of
strength can be only done occasionally). This concept represents embedded testing.
When combining training monitoring with embedded testing, through iterations, one
can quickly gain insights if certain type of planning works for a particular individual
(again, assuming there is no planned overreaching, and hence the expected drop in
both latent/estimated and manifested performance).
Please note that these represent Small World models that could be useful, assuming
honest and reliable subjective rating (which is questionable) and reliable equation
for particular individual (which is questionable). But, assuming the errors are stable
across time, and hence assuming error is constant, changes in predicted 1RM using the
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above equation can be insightful and indicative of potential changes in the real 1RM
(or could be indicative of potential change, rather than the exact prediction). Together
with occasional max reps testing, true 1RM testing, and load-velocity profiling, this
variation of embedded testing can be useful in providing insights whether the training
program is working across sprint iterations. These can also go together with the training
load in a more elaborate predictive model, when we want to figure out which training
variables influence changes in predicted 1RM, which will give us more insight for future
experimentations (see Figure 2.13 in Chapter 2). I will expand on these concepts in
Chapters 5 and 6.
There are similar tables to the Load-Exertion table, and one of the most common
is the one that utilize Relative Intensity, but I found that approach to be biased toward
high % 1RM and generally confusing for practitioners. For that reason, Load-Exertion
table is my preferred option, and as you could have witnessed, it is a very handy tool.
Not all training maximums
are created equal
1RM stands for “1 repetition maximum”, or the highest weight that can be
lifted under technical constraints of an exercise. For example, your 1RM in the parallel
back squat is 150kg. If you try to lift more, you either fail, or you modify the technical
execution (i.e. not going as deep, bouncing, etc). This is why the maximums need to be
defined under technical constraints of a given exercise (tempo, depth, and so forth). In
other words 1RM is maximal weight one can lift without technical failure.
Having established exercise 1RMs is of utmost importance for programming and
performing percent-based programs. Pretty much everything revolves around this
performance metric. Although, as you will read later, this doesn’t necessary imply that
you must test 1RM or that your whole strength training program is aimed at improving
1RM.
The overall process of the “traditional” strength training (percent based)
revolves around the following iterative phases:
1. Establish 1RM
2. Plan the training phase
3. Rinse and repeat
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Before getting into methods for establish 1RM, it must be stated that 1RM is
not a single, objective, ontological construct. I like to differentiate between the three
different types of 1RM (see Figure 4.2)
1RM
Compe��on Maximum (CM)
Training Maximum (TM)
Every-Day Maximum (EDM)
Figure 4.2. Three Training Maximums
Competition Maximum (CM) is the level of performance achieved under major
arousal of the competition. For some athletes this arousal might be too much, so the
CM can be lower than the Training Maximum. But generally, CM is the highest level of
performance, in this case 1RM.
Training Maximum (TM) is the level of performance that can be achieved in
training conditions. It still needs some arousal, but not as much as in competition.
This is the level of performance when you put your favorite death metal track, ask for
assistance and cheering of your lifting partners, ask for hot chicks to watch and slap
yourself few times. It is “balls to the wall” as it can be achieved in training conditions.
Every Day Maximum (EDM) is the level of performance that you can achieve
without any major arousal, music or hot girls in the gym. Something you can lift just by
walking to the gym, and listening to Mozart. Hence the name “every day maximum”.
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It can be argued that there might be more “maximums”, but three components
of this model are more than enough to get the message across, and that message is that
there are multiple 1RMs. The question is, which one are we measuring and which one
should we use to program the training?
Purpose of 1RM or EDM
Utilization of 1RM, when prescribing training program in the percent-based
approach to strength training, somehow immediately leads to conclusions that 1RM
must be tested, and that 1RM is the sole objective of the strength training program.
This cannot be further from the truth. My implementation of the 1RM in the percentbased program is not solely as a descriptor and objective, but rather as a prescription
aid tool. Again, the distinction between place of things versus forum for action. Using
1RM for prescription (which can be quite flexible and implemented in other methods
and schools of thought) helps me figuring out (i.e., prior) the weight one should use in
training. Is it perfect? Of course not, but it represents an educated guess, which is way
better than complete guess or pulling the numbers out of my own arse, or even worse,
allowing for certain types of athlete to self-select the weights (yes, soccer athletes, I am
referring to you). It can also help in estimating changes in strength, together with other
methods (e.g., load-velocity profiling and so forth) and ensure long term progressive
overload happens. Thus, just because I use 1RMs to prescribe, doesn’t mean that it is
the sole purpose of the strength training.
Above-mentioned three levels of 1RM can be seen on the substance - form
continuum (see GUT model in Chapter 2). Having high EDM is necessary, but not sufficient
for high TM and CM. Thus, EDM is more latent (potential, or substance), while TM and
CM are more manifest (realization, or form). With higher arousal, technique tweaks,
and gear, one can learn to express strength potential better, without actually developing
that potential (i.e., substance). This can be represented with the complementary pair
develop vs. express, where developing is about raising the potential, while expression
is about manifesting it. I also refer to this as pulling vs. pushing concept. According to
the Push-Pull Model (see next chapter for more details about this Small World model),
most of the training time should be spent pulling the EDM (i.e. raise the floor, develop
the underlying potential) versus pushing the Competition/Training maximum (i.e. push
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the ceiling, forcing the adaptation, expressing what one already has)29. Having said this,
I believe that EDM should be used to program and prescribe the strength training30.
The question that naturally follows, is that if EDM is used to program the
training, how should we approach testing or estimating EDM? Some authors (such
as Jim Wendler) suggest using 80-90% of your Training Maximum (or “reported”
maximum) to base your training cycle or phase. This is very useful heuristic, since
most of the reported training maximums are over-bloated. Hence, it is better to be safe
than sorry (see Chapter 1 on overshooting versus undershooting errors), and base your
training cycles using conservative 1RM (in this case 80-90% of TM, which is pretty
much similar if not equal to EDM).
In this manual, I use EDM and 1RM interchangeably, particularly when I refer
to %1RM. Ideally, these should be percentages of your EDM (particularly during the
pulling-type of programs; see next chapter). If you use your CM or TM, please use 8090% of those when starting a training release. This will make sure that we are wrong in
the undershooting direction, rather than overshooting which can be more costly.
If you plan performing 1RM testing you want to use to prescribe training, I suggest
your testing to be performed in a “calm” environment without pounding your chest
like a gorilla. Otherwise, you better deduct 10-20% just to be safe. As will be explained
soon, there might not be the need to re-test 1RM, but rather use fixed increments in
weights (see Chapter 6). But more on that later.
One of the main characteristics of Agile Periodization is the avoidance of
segregation between testing and training, and the effort to embed testing into training
as much as possible. I have already explained how to estimate 1RM from training,
without actually testing it, using RIR ratings (or reps to failure), but will come back to
this topic later in this chapter and thorough this manual.
To summarize the things said so far: there are three 1RMs: Competition
Maximum, Training Maximum and Every Day Maximum. The objective of training is to
“pull” EDM up, rather than to “push” CM/TM up and to try to “force” the progression
and adaptation (at least most of the time - see next chapter). Use your EDM to prescribe
29 This can be considered one aspect of periodization, or should I call it ‘cycling’ principle or sport form
development. One needs to develop the underlying potential, but to learn to express it when it is needed.
Sometimes, in order to really develop the underlying potential, one needs to ‘disrupt’ the expression, and
vice versa; when one works too much on expression, development stagnates or goes into recession. Thus,
these two represent complementary aspects. Some sports have them more separated (longer prep season
compared to competition season) and some have them more intertwined (shorter prep season and long
competition season). More about this and the concept of the sport form in the next chapter.
30 As you will read in the next chapter, this is the case for the pulling-type of programs (“raise the floor”
or how Dan John calls them - “Park Bench Workouts” (John & Tsatsouline, 2011; John, 2013)). When one
is peaking and really “pushing the ceiling” (pushing-type of workouts, or as Dan John calls them - “Bus
Bench Workouts’) then TM or even CM should be used for prescription.
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training and try to estimate EDM rather than TM. In the case you are not sure what is
your EDM, deduct 10-20% from your TM.
How to estimate 1RM or EDM?
Having covered the important distinctions in 1RMs, there are multiple ways to
establish it:
1. True 1RM test
2. Reps to (technical) failure
3. Velocity based estimates
4. Estimation through iteration
True 1RM test
True 1RM test is about “finding” the weight you can successfully lift for 1
repetition, and it represents “gold standard” in estimating “strength levels” in nonlaboratory environment (and we are not interested in those environments anyway).
1RM testing is a reliable and safe method, although not very time efficient, especially if
done for multiple exercises and with a bunch of athletes.
There are numerous protocols for 1RM testing, and the goal is to find your 1RM
without causing too much fatigue with too many “warm-up” sets and maximum
attempts. The simple protocol might be the following:
1. Use 50% of estimated 1RM and perform 5 reps. Rest 1-3min
2. Use 75% of estimated 1RM and perform 3 reps. Rest 1-3min
3. Use 90% of estimated 1RM and perform 1 rep (if you believe your athletes that
estimated or reported 1RM are honest and not overblown). Rest 2-4min
4. Athletes now increase the weight and begin finding their 1RM. A series of single
attempts should be completed until a 1RM is achieved.
5. Rest periods should remain at 3-5 minutes between each single attempt and load
increments typically range between 2.5-5%.In general, 1RMs should be achieved
within 3-5 attempts. If failing to lift certain weight, athletes can decrease the load
for 2.5-5% and try few more times.
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As explained before, the key is to find 1RM by increasing and decreasing weights
of the single attempts, but not exceeding 5 total tries. If multiple 1RMs are performed
(i.e. for back squat and bench press) then longer rest period is advised (e.g., 5-10min)
between exercises. Here is the hypothetical example of a 1RM test for the bench press:
1. While talking to the athlete, he mentions he could lift approximately 140kg on the
bench press. Since we understand that athletes are irrational lying scumbags, we are
going to test it, but we are going to use athletes reported values for initial weights
and increments.
2. We decided to test the strict bench press with 2-sec hold at the chest. The athletes
complains (well, duh).
3. After a warmup and a few sets with 20 & 40kg, we begin the test
4. Initial weight set to 50% of reported 1RM (140kg), which is 70kg. Athlete performs
5 reps with a 2 sec pause at the chest
5. Take 3min off, complaining he never lifted with pause
6. Second set is done with 75% of reported 1RM (140kg), which is 105kg. Athlete
performs 3 reps with a 2 sec pause at the chest. Last rep was shaky. You decide to
skip the 90% set because he might have been lying about his 1RM.
7. Take 3min off. Athlete asks to play 8 Miles by Eminem, you say “Fuck that shit!” and
go and play Spring by Vivaldi.
8. Athlete decides to increase for 10kg, which is 115kg. Performs one perfect rep
9. Take 3min off. Complains about Vivaldi.
10. Decide to increase for extra 10kg, which is 125kg. Performs one grindy rep.
11. Take 3min off. Asks again to play Eminem. You agree to play “Ride Of The Valkyries”
by Richard Wagner. That gives him little “oomph” while staying within limits of
EDM.
12. Wants to increase for extra 10kg. You roll your eyes (him not seeing it). 135kg. Failed
13. Take 3min off. Athlete blames you and your music choice (and the fucking 2-sec
pause at the chest).
14. Decided to reduce to 130kg. Slow lift but within technical requirements
15. Take 3min off.
16. Decided to go for 132.5kg. Failed.
17. No need to micro-load this stuff with 130.63kg. We accept 130kg to be his 1RM (EDM,
assuming Wagner didn’t cause too much arousal).
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The above example shows the typical 1RM testing. We managed to find 1RM using
5 sets (excluding two warm-ups). Another constraint might be giving time limit (after
warm-up sets) rather than limiting to 3-5 sets. For example, “Lads, you have 20minutes
to find your 1RM. Timer starts.... NOW!”. And accept the highest technically sound rep
as 1RM. It is up to the athletes to select weight and rest periods. This approach might
work better with athletes already familiar with 1RMs, but not so with beginners (or
soccer players) who need more constraints and guidance in 1RM testing.
The key is not finding the perfect protocol, but rather sticking to the same
protocol over time.
Reps to (technical) failure
Another method to assess 1RM is using reps to failure technique. Rather than
trying to find 1RM, we want to find 2-5RM (maximum weight that can be lifted for 2-5
reps ideally) and then use either conversion table or formulas to establish 1RM (see
Table 4.2).
The protocol is much simpler and quicker than 1RM.
1. Use 50% of estimated 1RM and perform 5 reps. Rest 1-3min
2. Use 75% of estimated 1RM and perform 3 reps. Rest 1-3min
3. Use 80-90% of estimated 1RM and perform maximal number of reps (while staying
within technical requirements of the exercise).
4. If an athlete is ‘calm’ then we are estimating EDM, if he wants to hear Eminem,
screams, slaps himself, then TM is estimated. Know the difference.
For example, athlete performed maximum 5 reps with 150kg in the back squat.
1RM = (150kg x 5reps x 0.0333) + 150kg
1RM = 25 + 150
1RM = 175kg
So according to Epley formula, 1RM of our athlete will be around 175kg. Another
option would be to use Load-Max Reps table (see Table 4.2).
The beauty of using reps to technical failure method is that it can be “embedded”
into a workout (which is one of the ideas of the Agile Periodization). Rather than doing
true 1RM test, one can just perform reps to technical failure at the end of the prescribed
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sets. Here is an example:
Set 1: 150kg x 3
Set 2: 150kg x 3
Set 3: 150kg x 3+
During the last prescribed set (denoted as a PLUS set), athlete is trying to perform
as much reps as possible. Usually, these should be capped at around 10 reps. Using this
as “embedded” testing, one can estimate 1RMs (or changes in the same) during the
workout. More on this in Chapter 6.
One can also create individualized rep max tables, but that is feasible only when
working with individual strength athletes (i.e., strength-specialists), rather than team
sport players (i.e., strength-generalists). It comes back to the satisficing concept something that is not perfect, but very usable, or good enough. Besides, individualized
rep max table will hold true only for a single lift, so planning other lifts cannot utilize
that knowledge. This is fine if your sport is powerlifting, so you really want to nail
down three exercises (bench press, squat and deadlift), but if you are team sport athlete
pursuing strength training as a means to an end, then having individualized rep max
tables for a few exercises would not be very practical - one would still need to use
heuristics when prescribing training for other exercises.
Velocity based estimates
Using velocity to estimate 1RM has been a novel technique that still needs
validation (Jovanovic & Flanagan, 2014). To perform this method, one needs LPT
(linear position transducer) such as GymAware or PUSH2. The LPT device connects to
a barbell via retractable cable and measures velocity of movements. If we plot velocity
of the reps versus load we get straight line that we can use to estimate 1RM. Figure 4.3
depicts concentric mean velocity (MV) across loads during 1RM deadlift testing for three
athletes. Each rep is done with the maximal intent to lift as fast as possible (which is
crucial assumption and requirement).
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Athlete 02
Athlete 03
Mean Velocity (m/s)
Athlete 01
1.0
0.8
0.6
0.4
0.2
100
150
200
100
150
200
100
150
200
Weight (kg)
Figure 4.3. Concentric mean velocity across loads during 1RM deadlift testing for three athletes.
Dashed horizontal line represents (group average) velocity at 1RM (v1RM), in this case 0.25 m/s
As can be seen from Figure 4.3, the higher the load, the slower the lift. This
relationship can be represented with the simple linear regression line. The point where
this line crosses the x-axis is termed L0, which can be conceptually understood as
some type of the isometric strength since the velocity is zero. But 1RM attempt doesn’t
happen at zero velocity, but rather at velocity of 1RM (v1RM). On Figure 4.3. this velocity
is represented with the horizontal dashed line. Every exercises has a specific v1RM (e.g.
bench press is around 0.15 m/s, back squat around 0.3 m/s and deadlift around 0.25
m/s, although this varies across individuals). Athletes also demonstrate variation of
the v1RM, so it is important to know one’s individual v1RM, although group mean is
a decent heuristic that could be used before individual v1RM is known (see Bayesian
updating in Chapter 1). The interesting thing is, is that individual v1RM seems to be
stable across training intervention. In plain English, this means that if your 1RM
improves or declines, velocity at 1RM attempt will tend to stay quite similar (this might
be more speculative statement, since research on this topic is ongoing). This allows one
to “predict” 1RM from sub-maximal attempts.
The reliability and predictive validity of this method is still being researched
and it is also topic of my PhD. Estimating 1RM using Load-Velocity profile is only
one potential use of the Velocity Based Training (VBT) (you can read more about it in
(Jovanovic & Flanagan, 2014)). The main application of VBT is using velocity to prescribe
training, rather than using %1RM and number of reps (I will expand on this topic later
in this chapter). For example, one might prescribe finding and lifting a weight with
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MLADEN JOVANOVIĆ
initial velocity of 0.5m/s and stopping the set once velocity reaches 0.4m/s. This could
be very useful when performing main exercises (e.g. squat, bench press, deadlift) with
individual strength athletes (i.e. strength specialists), but not very useful for team sport
athletes (i.e., strength generalists).
Another interesting use, as mentioned above, it to use warm-up sets as
“embedded” testing to estimate daily 1RM. All of this of course assumes maximal
concentric velocity possible while performing reps (i.e., intent). Due to changes in
exercise technique (i.e. depth, bounce, pause, intent) during sets, the estimates might
be completely off - so this method of 1RM estimation should be reserved only for
experienced lifters with “stable” technique and for exercises that have well constrained
start and stop position. Those include, but are not limited to deadlift, hex bar squat,
bench press, bench pull, and box squat. Figure 4.4. demonstrate will happen to 1RM
estimation (point where regression line crosses dashed v1RM line) when intent is not
Mean Velocity (m/s)
maximal.
1.2
0.8
Intent
Max intent
Sub−max intent
0.4
0.0
50
100
150
200
Weight (kg)
Figure 4.4. Not performing sub-maximal weights with maximal intent will over-estimate 1RM. It is of
utmost importance that all reps as done with maximal intent to lift as fast as possible
I find velocity based estimates and Load-Velocity profiling useful supplementary
source of information during normal 1RM testing with the strength-specialists,
particularly with powerlifters using grinding movements. These can be used later as
“embedded testing” during the training cycle to check what might be happening to
1RM using warm-up sets. This way, one still uses percent-based approach to prescribe,
but collects velocity data to have more informed decisions. Even if someone decided to
use VBT and prescribe set using velocity, percent-based approach can still be helpful in
providing approximate weight that needs to be used.
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STRENGTH TRAINING MANUAL Volume One
Although VBT is the topic of my PhD, I would not personally bother with it,
particularly with strength-generalists performing grinding movements. Where I see
the use of VBT and velocity measures is during ballistic movements (e.g., by creating
competition and hence increase motivation and intent) and ballistic Load-Velocity
profiling, as well as additional source of information and embedded testing for strength
specialist during selected grinding movements.
Strength
Specialist
Strength
Generalist
Grinding Movements
Instant Feedback
Load-Velocity Profiling
Embedded Tes�ng
Predic�ng 1RM
Prescribing Load
Ballis�c Movements*
Instant Feedback
Load-Velocity Profiling
Embedded Tes�ng
Predic�ng 1RM
Prescribing Load
✓
✓
✓
✓
✓
✓
✗
✗
✗
✗
✓
✓
✓
???
✓
✓
✓
✓
???
✓
* Not Olympic lifts
Table 4.4. Uses of velocity based estimates
Even if you decided to use velocity based 1RM prediction, use it as only one source
of information and combine with other sources during review and retrospective.
Estimation through iteration
The forth method advises against direct testing 1RM and represents embedded
way of estimating it using iterations (which is aligned with the Agile Periodization
framework). Why do we need 1RM in the first place? As explained already, we need 1RM
to prescribe workloads using “traditional” percent based program. But as you will read
later in this chapter there are other alternative methods, although knowing 1RMs is
always beneficial in providing ballpark weights.
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MLADEN JOVANOVIĆ
One particular problem with having 1RM for exercises, is that there are a lot
of exercises, particularly for strength generalist. Testing all these exercises can be
overkill and exercise in futility. One shortcut is to use conversion tables described in the
previous chapter. This brings me to an important realization - all 1RMs are estimates,
even if we test them (since they will vary from day to day, based on individual readiness,
motivation and rate of adaptation). Since they are estimates, why do we need to know
exact 1RM by testing it? Why can’t we estimate it and update it as we go through training
iterations?
For example, we could assume (or guess) 1RM using athlete’s bodyweight, training
experience, training log or individual reported values. Let’s assume that athlete’s BW
is 85kg. With his training experience we can assume he can lift 1,25xBW in the back
squat (it is better to be “conservative” than overly optimistic; see overshooting vs.
undershooting errors in Chapter 1). Therefore, his estimated 1RM is 1,25 x 85, which is
around 105kg. Yeah, we are most likely wrong, but wait...
This is just a very simple estimate that allows us some prescription in terms of
numbers (see the MVP concept). We can use this to write the first few workouts when
dealing with the unknown athlete:
Workout 1: 3x5 @75% 1RM
Workout 2: 3x5 @80% 1RM
Workout 3: 2x5+ @85%, 1x5+ @85% 1RM
On the last workout, we have a “plus” set (done after 2 sets of 5), where athlete
tries to lift as many technically sound reps as possible. This is our 1RM test, which is
embedded. The number of reps should be capped to 10 - no need to perform more than
that. If athlete is able to perform more reps, then estimate will probably be off. More
about this in the Chapter 6.
Now the coach has a few options (which we will cover in more details in Chapter
6). The first option is to calculate the 1RM from reps to failure, and take say 10% off
of that to get EDM 1RM that is used in prescribing training (if there was high arousal,
although it is never too bad to start too low rather than a bit too high).
Second option would be to increase estimated 1RM for a few kilos (e.g. 2.5kg for
upper body and 5kg for lower body) and slowly reach true EDM/TM through iterations
of this process. This depends weather you are doing pulling the floor workouts or pushing
the ceiling workouts. If you are in no particular rush, there is nothing wrong with slowly
cooking the athlete with slow progression and jumps in 1RM estimates used for cycle
planning and load prescription.
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STRENGTH TRAINING MANUAL Volume One
This second option is similar to the simple rule (heuristic) of not increasing more
than 10-20% from week to week in training dosage to avoid unnecessary downsides
(e.g., extreme soreness, fatigue, injury). But similar to that rules, this rule can be broken
if someone is trying to get back to his normal levels of volume, versus someone who is
trying to push the adaptation by increasing volume. Suppose athlete who was running
100km/week as a normal thing, dropped to 50km/week due illness. During his return,
he can break this rule and use bigger increments in running volume. On the flip side, if
someone is running 80km/week regularly and want to increase that number, then he
should not do training load jump bigger than 10-20%. This is precautionary principle
and it could be applied in 1RM updates as well as in estimation through iteration concept.
Having said that, if we are in the phase of estimating one’s 1RM (i.e., having a
new team or new athletes), then first method could be used once or twice, after which
we switch to second method (using small increments in 1RM).
Once we have estimated 1RM for major lifts we can use conversion tables from
previous chapter to get 1RMs for all exercises. Other method might involve estimating
1RMs for assistance exercise using either reps to failure method as well, or using Epley
formula using RIR estimate. This is useful in the situation where, say Romanian Deadlift
is estimated using 75% of 1RM of the back squat. But for some athletes this might be
too much or too little. This is a good starting point, but later in the phase, athletes can
perform either reps to failure or estimate 1RM using modified Epley formula using RIR.
Let’s assume we have a new athlete who might not have much under his belt
when it comes to strength training. His body weight is 75kg. I assume he can probably
lift 1xBW in the back squat. For this cycle we have planned back squats and Romanian
deadlifts (RDLs). For RDLs we use 75% of back squat 1RM, which is 75% of 75kg, or
55kg. So we start from there.
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MLADEN JOVANOVIĆ
Romanian Deadli�
est1RM
55
5
5
5
75%
75%
75%
56.25
56.25
56.25
5
5
5
80%
80%
80+%
60
60
60
Reps Done
new 1RM
Session
#1
Weight
52.5
52.5
52.5
Reps
5
5
5
%1RM
70%
70%
70%
Weight
38.5
38.5
38.5
Session
#2
%1RM
70%
70%
70%
5
5
5
75%
75%
75%
41.25
41.25
41.25
Session
#3
Session
#1
Reps
5
5
5
Session
#2
75
Session
#3
Back squat
est1RM
5
5
5
80%
80%
80+%
44
44
44
10
80.0
Reps Done
new 1RM
8
55.7
Table 4.5. 1RM estimation using iterations for back squat and Romanian deadlift
As can be seen in Table 4.5, 1RM of the squat was a bit underestimated, but for
RDL was about right. For both exercises I would use increment in 1RM: 5kg for the back
squat and probably 2.5 for the RDL or leave it as it is.
Using this simple method, we didn’t waste time of 1RM testing, we had numbers
to start with and using iterations and plus sets we “converged” to a real 1RM (EDM)
over few short iteration of the training program. Estimate through iteration is hence
very helpful in devising MVP when you start working with new athletes and you do
not have any info about them. I think the common contemporary planning strategy of
testing first before planning is not needed, and maybe even harmful. Imagine having a
new soccer team, and you want to test their 1RM in the back squat, so you know how to
prescribe their training. How do you know if they ever lifted in their life? Therefore, I
think this testing period is pretty much stupid - the better approach is to conservatively
guess, and collect data through action and implementation and then use it to update
the information you have (see Bayesian updating in Chapter 1).
Table 4.6. contains some suggestions as where you can start using athletes’
bodyweight when estimating 1RM. These are VERY conservative and allow you to devise
MVP and collect and update data through iterations. Using exercise conversion tables
from the previous chapter you can quickly estimate 1RMs for a lot of exercises.
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STRENGTH TRAINING MANUAL Volume One
Squat
Bench Press
Pull-Ups
Male
1.2 x BW
0.75 x BW
1 x BW
Female
1 x BW
0.5 x BW
0.8 x BW
Table 4.6. Rough conservative estimates for a starting 1RM using athlete bodyweight.
The whole point is that YOU DO NOT NEED TO TEST 1RM to use it for helping you
with the prescription, particularly with the new athlete. You can use you best guess (i.e.,
prior) which should be conservative (undershooting) and should be updated through
short training cycles.
Total System Load vs. External Load?
Imagine we have two athletes with bodyweight of 75kg and 100kg and they both
perform 5 pull-ups with extra 20kg attached using dip belt. What is their 1RM?
Athlete 1
Athlete 2
Bodyweight
75
100
Weight
20
20
Reps
5
5
1RM
23
23
Table 4.7. Using external load to estimate 1RM. This is wrong for movements when one also lifts
bodyweight
If we use only external load (in this case 20kg) and we use Epley’s formula, both
athletes will have 23kg 1RM in the pull-ups (see Table 4.7). You might ask: “Yeah, but
they are lifting their own bodyweight”. And you would be correct. For this reason we
need to utilize ‘total system load’, which is in this case bodyweight plus external load
(see Table 4.8)
Athlete 1
Athlete 2
Bodyweight
75
100
Weight
20
20
Total Load
95
120
Reps
5
5
1RM
111
140
Table 4.8. Using total system load to estimate 1RM.
As can be seen from the Table 4.8, Athlete 2 have much higher 1RM since he is
heavier.
Now that we have 1RMs, how do we calculate the weights that needs to be lifted
using percent-based approach? For example, if program calls for doing 3x5 with 75%
1RM?
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MLADEN JOVANOVIĆ
Athlete 1
Athlete 2
Bodyweight
75
100
1RM
111
140
Load (%)
75%
75%
Load (kg)
83
105
Table 4.9. Percent-based approach to load calculation using total system load
But multiplying 75% with 1RM, we got 83kg for Athlete 1 and 105kg for Athlete
2 (see Table 4.9). That is also total system load that needs to be lifted for 8 reps. To get
external load, we need to deduct bodyweight (see Table 4.10).
Bodyweight
1RM
Load (%)
Load (kg)
75
100
111
140
75%
75%
83
105
Athlete 1
Athlete 2
External
Load (kg)
8
5
Table 4.10. To calculate external load using percent-based approach, bodyweight needs to be
deducted from estimate total system load
To perform 3x5 pull-ups with 75% 1RM, Athlete 1 needs to add extra 8kg and
Athlete 2 needs to add extra 5 kg.
If you use even lower percentages, there would be a point where you would need
to deduct the load, either using elastic bands, or using special equipment (or moving to
pull-down machine).
To estimate 1RMs for the assistance movements, for example DB Rows, one
would use body weight corrected (total system load) 1RM in the pull-ups and check the
conversion tables in the previous chapter. Since 1RM for single arm DB Row is 35% of
1RM of the pull-ups, for Athlete 1 that would be 35% x 111kg, or around 38kg.
The above example using pull-ups is quite intuitive, but now let’s compare bench
press and back squat. Using basic wooden dowel (assuming 0kg external load), would
you be able to do more reps on the bench press or on the back squat? You will be able
to do many more reps on the bench press with wooden dowel than you would be able
to do in the back squat. Why is that? Because, when you do squats, you are also lifting
your bodyweight. The same relationship should hold true if we compare, say maximum
number of reps with 50% of 1RM between back squat and bench press. You are more
likely to do more reps on the bench press.
According to biomechanics research, the load you are lifting in the squat, besides
external load, is approximately 90% of your bodyweight. This is pretty much your body
without the lower legs (which are around 10% of your bodyweight).
Should we then take into account 90% of bodyweight when we calculate 1RMs
and estimate loads for lower body lifts? Let’s use the same two athletes and compare
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STRENGTH TRAINING MANUAL Volume One
1RMs with and without BW correction (in this case 90% of BW). Both athletes lifted
120kg for 5 reps in the back squat:
Athlete 1
Athlete 2
Bodyweight
90% BW
Load
75
100
68
90
120
120
Total
Load
188
210
140
140
Squat 1RM
Total System
219
245
Squat 1RM
External
151
155
=(Load * Reps * 0.0333) + Load
=(Total Load * Reps * 0.0333) + Total Load
=Total System 1RM - 90% BW
Reps
Squat 1RM
5
5
Table 4.11. Estimating 1RM from reps to failure using only external load (Squat 1RM), total system load
(Squat 1RM Total System) and external 1RM (Squat 1RM External)
The usual approach is to estimate 1RM using barbell load, which is 120kg. If we
plug this into Epley’s equation, we get 140kg as 1RM. If we utilize total system load
into account, taking Athlete 1 as an example, total system load would be 120kg + 90%
of 75kg, which is 120 + 67.5, or 187.5kg. Using Epley’s equation to estimate 1RM, we
get (187.5 x 5 x 0.0333) + 187.5, which equals 219kg (see Table 4.11). Using total system
1RM, we need to deduct 90% of BW to estimate external load, which is 219 - 90% BW,
or 219 - 68, or 151kg.
On this simple example, it is easy to see how these models represent Small Worlds
(see Chapter 1). Also, Epley’s formula is estimated using only external barbell load, not
total system load. Thus, it is tricky to use the same formula across different scenarios.
But let’s continue with the current example and see where it will take us (and keep in
mind that one cannot use same equation across different conditions).
Let’s assume that we prescribe 3 sets of 5 reps with 75%. Let’s compare two
methods of estimating the load:
Es�ma�on using external 1RM
Es�ma�on using total system 1RM
Bodyweight
Load (%)
Reps
1RM
Load (kg)
75
100
75%
75%
5
5
140
140
105
105
Athlete 1
Athlete 2
Total System
1RM
219
245
Load (kg)
97
94
Table 4.12. Calculating barbell weight using external 1RM and total system 1RM.
As can be seen in Table 4.12, load estimated using 1RM without BW correction is
the same for both athletes (105kg), but different when we use BW corrected 1RM (97kg
for Athlete 1 and 94kg for Athlete 2). Hopefully, this example showcase the pluralism of
models and lack of single “objective” truth.
Let’s estimate how these estimates differ across continuum of loads (from 100%
to 50% of 1RM).
126
MLADEN JOVANOVIĆ
%1RM
100
95
90
85
80
75
70
65
60
55
50
Athlete 1
1RM (kg)
1RM w/90% BW (kg)
140
219
140
219
140
219
140
219
140
219
140
219
140
219
140
219
140
219
140
219
140
219
Bodyweight
75
75
75
75
75
75
75
75
75
75
75
Load (kg)
151
140
129
118
107
97
86
75
64
53
42
Bodyweight
100
100
100
100
100
100
100
100
100
100
100
Athlete 2
1RM (kg)
1RM w/90% BW (kg)
140
245
140
245
140
245
140
245
140
245
140
245
140
245
140
245
140
245
140
245
140
245
Load (kg)
155
143
130
118
106
94
81
69
57
45
32
Without BW correc�on
1RM (kg)
Load (kg)
140
140
140
133
140
126
140
119
140
112
140
105
140
98
140
91
140
84
140
77
140
70
Table 4.13. Different barbell load estimates across 50-100 %1RM using external load 1RM and total
system load 1RM
Things look much clearer when plotted (see Figure 4.5):
180
160
140
Load (kg)
120
100
80
60
40
20
0
50
55
60
65
70
75
80
85
90
95
100
%1RM
Athlete 1
Athlete 2
Without BW Correc�on
Figure 4.5. Plot of estimated barbell loads across 50-100 %1RM using external load 1RM and total
system load 1RM. This plot represent graphical representation of the Table 4.13
As can be seen on Table 4.13 and Figure 4.5, there are discrepancies between load
estimation using bodyweight correction (total system load) and load estimation without
bodyweight correction (using only external load), given Epley’s equation as a model in
both scenarios. It can be seen that as percentages decrease, total system load approach
estimates lowered barbell loads, especially for the heavier athlete. From the Figure 4.5,
it can also be seen that 1RM estimated with reps-to-failure using total system load is
higher than 1RM estimated using external load. That is most likely due the fact that
original Epley formula doesn’t take into account bodyweight, but only external load.
Let’s assume that the true 1RM test is being done, thus we know with certainty
what is the external 1RM (since athletes lifted it as 1RM). In that case, we can just add
90% of bodyweight to external load 1RM (140kg for both athletes) to get the total system
127
STRENGTH TRAINING MANUAL Volume One
1RM (see Table 4.14):
%1RM
100
95
90
85
80
75
70
65
60
55
50
Athlete 1
1RM (kg)
1RM w/90% BW (kg)
140
207
140
207
140
207
140
207
140
207
140
207
140
207
140
207
140
207
140
207
140
207
Bodyweight
75
75
75
75
75
75
75
75
75
75
75
Load (kg)
140
129
119
109
98
88
78
67
57
47
36
Bodyweight
100
100
100
100
100
100
100
100
100
100
100
Athlete 2
1RM (kg)
1RM w/90% BW (kg)
140
230
140
230
140
230
140
230
140
230
140
230
140
230
140
230
140
230
140
230
140
230
Load (kg)
140
128
117
105
94
82
71
59
48
36
25
Without BW correc�on
1RM (kg)
Load (kg)
140
140
140
133
140
126
140
119
140
112
140
105
140
98
140
91
140
84
140
77
140
70
Table 4.14. Different barbell load estimates across 50-100 %1RM using external load 1RM and total
system load 1RM. This time, as opposed to reps-to-failure done in Table 4.13, true 1RM is being done. This
way we know for sure what is external 1RM, since we tested it.
And now when the numbers get plotted, we get the following graph (see Figure
4.6):
160
140
120
Load (kg)
100
80
60
40
20
0
50
55
60
65
70
75
80
85
90
95
100
%1RM
Athlete 1
Athlete 2
Without BW Correc�on
Figure 4.6. Plot of estimated barbell loads across 50-100 %1RM using external load 1RM and total
system load 1RM when known external 1RM is known due true 1RM test. This plot represent graphical
representation of the Table 4.14.
It is logical to conclude that two athletes with the same 1RM (in this case 140kg),
but with different body weights should be using different loads in training. This should
hold true both with pull-ups and with squats. But things are not that straight forward
and it is very easy to slip into the rabbit hole (if this doesn’t remind you of the Figure
1.1, I am not sure what does). When it comes to back squat example, I am not sure there
is any research on reliability of Epley’s formula (or any other estimate of 1RM using
reps-to-failure) when one uses total system load as opposed to using external load
128
MLADEN JOVANOVIĆ
only. So in this case our 1RM estimation can be unreliable to begin with (especially
if we haven’t performed true 1RM test as seen in the two examples above), as well
as number of reps performed at certain percentage of it. Second, the load estimation
for assistance exercises becomes cumbersome using total system load method. For
example, according to conversion tables from previous chapter, 1RM of Romanian
Deadlift (RDL) is approximately 75% of the back squat 1RM. This is straightforward
when we use external load method, but when using total system load the calculus
become much more complex, since we are not lifting 90% of body weight in the RDL.
So we are back to “precision vs importance” dichotomy (Figure 1.1). My approach is to
utilize the simplest approach possible that gives me enough of actionable insights that
I can start using right away and be able to update as I go. And I will be wrong - I just
want to make sure that I am conservative and having Type I errors (undershooting).
Besides, we are always dealing with ‘estimates’ and hence there is a lot of uncertainty
involved already. And making things more complex on top of uncertain metrics is not
my cup of tea (although it is a good exercise in futility).
But before I wrap up total system vs external load approaches, let’s take one more
example. If we know athlete’s 1RM in the bench press, we might want to estimate how
much external load that athlete needs to use in the push-up movement (for example
putting weight vest, plate on the back or using dip belt when elevated). If you put your
arms on the scale in the push-up position you can estimate that around 70% of your
weight is supported on your arms (this of course depends on the body type, but 70%
will be ‘good enough’ estimate). Taking our two athletes as an example, both with
120kg 1RM in the bench press, we want to estimate external load for the push-up when
we prescribe sets of 5 with 75% 1RM (Table 4.15).
Bodyweight
Athlete 1
Athlete 2
75
100
Bench Pres
1RM (kg)
120
120
= 0.7 * BW
= BP - PU Load
Push-Up
BW Load (kg)
53
70
Push-Up
External 1RM (kg)
68
50
Load (%)
75%
75%
Bench Press
Load (kg)
90
90
Push Up
External Load (kg)
15
-2.5
Table 4.15. Estimation of push-up load, assuming 70% of BW is supported and total system load is
equal to bench press 1RM
As can be seen from the Table 4.15, knowing athletes’ bench press 1RM and
assuming 70% of bodyweight is supported in the push-up, calculated external load
for sets of 5 reps with 75% 1RM are 15kg for Athlete 1 and -2.5kg for Athlete 2 (which
means he need to ‘deduct’ some weight, or do less reps). The reverse process can also be
utilized - we can estimate bench press 1RM from push-up reps-to-failure performance
(Table 4.16):
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STRENGTH TRAINING MANUAL Volume One
Athlete 1
Athlete 2
Bodyweight
75
100
Push Up
External (kg)
20
10
Total Load (kg)
72.5
80
Bench Press
1RM (kg)
97
107
Reps
10
10
=(Total * Reps * 0.0333) + Total
Table 4.16. Estimating bench press 1RM using externally loaded push-ups for reps
Let’s wrap up the issue of total system load vs. external load approaches. First
of all, we are dealing with estimates that are inherently uncertain (except when
performing true 1RM test, but even with that we are uncertain about assistance exercise
1RMs) - type of movement, experience, gender, motivation, body built and others all
affect reps-to-failure method reliability of estimating 1RM, and especially estimating
assistance movements 1RMs and later training prescription loads (e.g. what %1RM we
should use for 3 sets of 10 for upper vs. lower body movement). The question is why? Why
do we need 1RMs for? In my opinion, besides being an evaluation of performance, we
need it to prescribe loads. And for that we need to lean more toward ‘significance’ in the
‘precision-significance’ continuum (Figure 1.1), and to utilize ‘satisficing’ philosophy.
In other words, we need ‘something’ to work from without killing the athletes. So, it is
a form of heuristic that we use to prescribe training.
It seems logical that total system load approach can be used with say pull-up
movements and push-up movements (essentially bodyweight), in which external
load is not close to bodyweight. With lower body movements, such as squats and
deadlifts, using external load approach will suffice. It might not be the most precise,
but it is good enough to prescribe training. There will always be individual differences,
exercise differences, estimation formula differences, but it is up to us to deal with all
these uncertainties using simple rules, but also realizing and understanding all the
assumptions involved. Plan, Do, Check, Adjust (see Figure 2.13).
Some coaches, such as great Dan Baker, utilize very simple heuristic when doing
higher reps training for upper vs. lower body movements:
Week
Bench
1
3x10
60%
2
3x10
64%
3
3x10
68%
4
3x10
70%
Back Squat
3x10
45%
3x10
50%
3x10
55%
3x10
60%
Table 4.17. Example of Dan Baker’s bench press and squat training cycle for rugby athletes
(Season 2006). Notice that %s for Bench Press vs Back Squat differ
130
MLADEN JOVANOVIĆ
Dan Baker takes into account differences in performing higher rep squats versus
higher rep bench press and adjust prescription percentages rather than splitting hair
with 1RM estimation and bodyweight utilized in main movements and assistant lifts.
Table 4.18 contains mathematical exercise, assuming athlete weights 100kg,
squats 150kg and bench press 150 kg. Load-Rep max table calculates external load that
needs to be lifted, comparing bench press to back squat (when total system load is used
for squat).
Bodyweight
100
Bench Press
Back Squat
External 1RM
150
150
Total 1RM
150
240
%1RM
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
Total
Load
150
141
136
132
129
125
122
118
115
113
110
107
105
102
100
98
96
94
92
90
Max Reps
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Bench Press
External
Load
150
141
136
132
129
125
122
118
115
113
110
107
105
102
100
98
96
94
92
90
% External
1RM
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
Total
Load
240
225
218
212
206
200
195
190
185
180
176
171
167
164
160
157
153
150
147
144
Back Squat
External
Load
150
135
128
122
116
110
105
100
95
90
86
81
77
74
70
67
63
60
57
54
% External
1RM
100%
90%
85%
81%
77%
73%
70%
66%
63%
60%
57%
54%
52%
49%
47%
44%
42%
40%
38%
36%
% Eternal 1RM Difference
Diff
0%
4%
5%
7%
9%
10%
11%
13%
14%
15%
16%
17%
18%
19%
20%
21%
22%
22%
23%
24%
Ra�o
1.00
1.04
1.06
1.09
1.11
1.14
1.16
1.19
1.22
1.25
1.28
1.32
1.35
1.39
1.43
1.47
1.51
1.56
1.61
1.67
Table 4.18. Load-Rep max table of an 100kg athlete for 150kg bench press and 150kg back squat. Table
showcases how percentages of the external load 1RM differ when loads are calculated using total
system load for bench press (where there is no BW lifted) and for squat (where there is 90% of BW
lifted).
As already demonstrated, the higher the number of reps, the lower the external
load when calculated using total system load as opposed to external load method. But
what Table 4.18 does is to recalculate (let’s call it adjust) %1RM by comparing estimated
external load (using total system load approach) to external 1RM. It can be seen that the
difference between bench press and back squat increases with number of reps. Figure
4.7 contains graphical representation of ordinary Load-Max reps table and adjusted
one (for this particular athlete):
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% 1RM 100%
90%
80%
70%
Generic Rep Max Table
60%
50%
40%
30%
Adjusted Rep Max Table
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Max Reps
Figure 4.7. Adjusted Load-Rep Max table using a hypothetical athlete with 100kg bodyweight and
150kg bench press and squat
As alluded multiple times, we assume Epley’s formula is the same for using
external and total system load, and to my knowledge this probably is not the case. Thus,
all the above represents exercise in futility - or how we can make something uncertain
to begin with (for example, parameter 0.0333 might, and probably does, differ between
bench press and squat for example, or when one uses total system load versus external
load) more complex and more scientific. Ideally, one would want to create personalized
(athlete x exercise x total vs. external load) tables, but again, that would be an overkill.
Acting like a wise ass with the uncertain equation to begin with is not a sign of scientific
method, but pseudo-science. It looks like science (since there is some math involved),
but it is actually a merda.
But this doesn’t negate phenomenological insight that lifting, say 3x10 at 65%
1RM for bench press and back squat creates different effects, both acute (in terms of
exertion during the set) and chronic (how long it takes to recover from a session). A
simple heuristic one could use here, is 1.5% drop per rep. For example, if bench press
calls for 5 reps at 75%, then squats can be 75% - 5 x 1.5%, or around 67.5%. Simple
heuristic you can use, particularly for high rep phases.
With these simple examples, you can see the uncertainty involved in estimation
and the pluralism of models, as well as our automatic jumping over Is/Ought gap (just
because the testing indicate certain Load-Rep Max table, it doesn’t mean we should do
multiple sets at the same intensity for different exercises). Just remember that these
are all Small World models, and don’t try to be a precision obsessed lab coat. Think
“satisficing” (good enough), MVP, forum for action and take a stance “I will start with
conservative estimation, and will correct it over iterations of the training cycles”.
The exercise list in the Chapter 7 (also see Figure 3.31) contains %BW column,
which indicates percent of BW used in a particular exercise. As stated already, this is
useful for dips and pull-ups, and if you want to be a wise ass when estimating external
load for push ups based on bench press 1RM. When it comes to planning high reps phases,
utilization of the simple heuristic of “1.5% per rep drop” for lower body movements
can be implemented if deem appropriate.
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Comparing individuals
“Hey bro, how much you bench?”
How do we decide who is stronger? Person who lifts the most for 1 rep (1RM), who
lifts more reps (e.g. pull-ups), or who lifts the fastest (e.g. clean)? As you will see, the
answer is not clear cut (again pluralism).
Let’s compare four athletes in the back squat (Table 4.19):
Athlete 1
Athlete 2
Athlete 3
Athlete 4
Bodyweight (kg)
75
100
80
90
1RM (kg)
140
170
120
135
Table 4.19. Four athletes with different bodyweight
and 1RMs in the back squat. Who is the strongest?
Which one of the four athletes is the strongest? Athlete 2 lifts biggest weight in
the back squat - 170kg, but he is also the heaviest. So we need to take into account
bodyweight31.
Comparing individuals is very complex topic and there is no clear cut solution to
it. For the sake of example, I will compare a few techniques that you might use when
comparing individuals.
Simple ratio (relative strength)
The simplest approach we can do is to divide 1RM with the bodyweight. Similar
to pull-up vs. squat example, we can use only external 1RM or total system 1RM (Table
4.20)
Athlete 1
Athlete 2
Athlete 3
Athlete 4
Bodyweight (kg)
75
100
80
90
1RM (kg)
140
170
120
135
Total System
1RM (kg)
208
260
192
216
Rela�ve
External
1.87
1.70
1.50
1.50
Total
2.77
2.60
2.40
2.40
Table 4.20. Using external and total body simple ratio (dividing with bodyweight)
31 We could also take into account height, limb lengths, experience, drug use and so forth with the aim of
creating “equal playing” field. Essentially the number of variables we need to control for is pretty much
unlimited, so I leave this pipe dream for the “progressives” and SJWs
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Using relative strength approach, we can clearly see that the Athlete 1 has the
highest level of relative strength. As with the conclusion of using total vs. external in
estimating 1RM, I suggest here as well to use total system when comparing bodyweight
movements (e.g. pull-ups, push-ups, etc) and external load when comparing barbell
movements (e.g. bench press, back squat).
This is a very common approach when comparing individuals, unfortunately it
is biased towards lighter weight individuals, because strength doesn’t increase linearly
with bodyweight (all things being equal). For that reason we need to use allometric
scaling (Folland, Mccauley & Williams, 2008).
Allometric scaling
Let’s represent a muscle (or the force generator) with a cube with the side
length L
Length
1
2
3
4
Surface
1
4
9
16
Volume
1
8
27
64
Surface / Volume
1
0.50
0.33
0.25
Figure 4.8. Small World model of the muscle using cube with side lengths L.
The surface of the cube (one side surface) is proportional to the cross-sectional
area of the muscle, and hence directly proportional to the maximal strength. The
volume of the cube is proportional to the weight of the muscle.
As can be seen, the ratio of surface to volume, or strength to weight, is not linear,
because weight increase much quicker than surface area. That’s why simple strength
ratio is biased against heavier individuals.
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The way to deal with this is simple (although the nuances are complex and
researchers split hair discussing them). Since we know the weight of the individual, we
can write the equation for the strength to be proportional to weight:
So, to compare who is the strongest, we need to compare one’s 1RM to what is
‘expected’ based on his bodyweight. Let’s call this the allometric strength score:
Let’s use this formula and compare our four athletes, using both total system
load and external load
Athlete 1
Athlete 2
Athlete 3
Athlete 4
Bodyweight (kg)
75
100
80
90
1RM (kg)
140
170
120
135
Total System
1RM (kg)
208
260
192
216
Rela�ve
External
1.87
1.70
1.50
1.50
Allometric Scaling
Total
2.77
2.60
2.40
2.40
External
7.87
7.89
6.46
6.72
Total
3.99
4.17
3.61
3.75
Table 4.21. Using external and total body allometric scaling
It can be seen from the table above, using allometric scaling to estimate strength
score, that Athlete 1 is not the best anymore, but rather Athlete 2. It is also important
to compare Athlete 3 and Athlete 4 who had same relative strength (1.5 x BW), but with
allometric scaling Athlete 4 has slightly higher strength score.
There is much more to the allometric scaling and comparing individuals (such as
Wilks score used in weightlifting, or using lean body mass rather than full bodyweight)
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STRENGTH TRAINING MANUAL Volume One
(Folland, Mccauley & Williams, 2008), but understanding simple relative strength and
allometric strength score is more than enough to get you up and running. As can be
seen here, a simple question “Who is the strongest” cannot be answered with the single
“objective” answer, but rather with pluralistic answers. This is because we always
represent Large World with Small World models.
Percent-based approach to prescribing
training loads
It should be clear by now that for planning a strength training cycle we are using
1RMs as something that helps us with prescription, and not something to argue about
until cows come home. It is a concept of “satisficing” that applies here - “something
that is good enough to get the job done”. This is indeed philosophy of pragmatism.
Besides, we are using multiple 1RMs for assistance exercises that are estimated
from 1RMs of the main lifts. Hence, they are not very precise, but are meaningful in
prescribing the training.
What is important to remember is that it is better to under-estimate 1RM a lot,
than to over-estimate 1RM a little bit. It is better to be conservative and start light,
since through iterations and short planning cycles and quick feedback we are going to
converge to the true ‘1RM quickly. And by true I refer to EDM (every day maximum).
It is my opinion that we need to use EDM in planning strength training cycle. So,
when we do training max (TM) estimate, some authors suggest stripping off 10-15%
of it and using that as EDM, which is a good heuristic. If we used estimation through
iteration, then we are starting with conservative estimate anyway.
For example, if an athlete did 5 reps with 100kg on the bench press in the testing
session, which equals to (5 x 100 x 0.0333) + 100 = 115kg 1RM, we can use 90% of that
number to start the next big/new cycle of training. This would represent EDM and it
is equal to 0.9 x 115 = 103kg (100-105kg could be used). I know we get emotional when
we strip off kilograms from our 1RMs, so we need to keep in mind that we are going to
quickly converge to real/true EDM in training. So no need to cry here. Do not make a leap
over Is/Ought gap thinking that TM or EDM estimated in a specific testing session is the
same TM or EDM in normal training, in which multiple exercises are done over multiple
sets, you might come to session a bit tired and so forth.
Once we have estimated EDMs for lifts (and sometimes we do not even need it),
we can utilize numerous methods of prescription. Let’s cover the most common ones
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Prescribing using open sets
Rather than prescribing exact weight than needs to be on the barbell using
percentages of individual 1RM, some coaches prefer to only prescribe open sets. Open
sets represent prescribing only number of sets and reps, i.e. perform 3 sets of 5 at the
same load. It is up to the individual to select the weight, usually based on the idea of
progressive overload by increasing weight over time by keeping the training log. One
example would be the following:
Workout 1: 3x8
Workout 2: 3x6
Workout 3: 3x4
Next Phase
Workout 1: 3x8 +2.5 to 5kg
Workout 2: 3x6 +2.5 to 5kg
Workout 3: 3x4 +2.5 to 5kg
I am not a big fan of this approach, unless athletes are just starting to lift and
are progressing every workout (i.e. using 2.5-5kg more) and are responsible enough
to apply progressive overload themselves. Programs such as Mark Rippetoe’s Starting
Strength (see Table 4.22) are example of using open sets (particularly his novice program
(Rippetoe & Kilgore, 2011; Rippetoe, Baker & Bradford, 2013)). In this very simple
program, athletes start with the bar only (pretty much) and performing squats three
times per week, using 3 sets of 5 reps (3x5). Athletes should increase the weight every
training session for 2.5-5kg until they are unable to perform 3x5 with same weight. In
that case athletes can recycle the weight (e.g. drop from 10-20%) and start over.
Monday
Squat 3x5
Bench Press/Press 3x5
Chin-Ups 3x5
Wednesday
Squat 3x5
Bench Press/Press 3x5
Deadli� 1x5
Friday
Squat 3x5
Bench Press/Press 3x5
Chin-Ups 3x5
Table 4.22. Starting Strength program for novice lifters (Rippetoe & Kilgore, 2011; Rippetoe, Baker &
Bradford, 2013)
This is a wonderful program for beginners, and something that I have tried to
apply in team settings and failed miserably. This approach demanded for each athlete
to have a training log where they enter last weights used and the try to increase the load
every session for a few kilograms. The athletes I was working with were not responsible
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enough to perform such a workout - they kept forgetting logs, not following progression,
going too easy and so forth. On the opposite extreme, there might be athletes that after
first initial workouts start to “push” it too much, which is not the goal of strength
training in team sports. For example, athlete did 2x5 with 140kg, and on 3rd set he
did 1x3 reps. Next time, this athlete would need to try and “push” to 3x5. Great for the
off-season in college sports, but not for 10-months in-season model of professional
sports, such as soccer.
In a way, every program/methodology has a target audience. This approach was
not working for team sport athletes performing a team workout in the gym.
Prescribing using %1RM approach
(percent-based bread and
butter method)
More strict prescription involve using exact number of reps and %1RM that needs
to be lifted, usually with the help of Load-Exertion Table 4.3 (see next chapter for more
details). For example:
Workout 1: 3x8 @ 70% 1RM
Workout 2: 3x6 @75% 1RM
Workout 3: 3x4 @80% 1RM
This approach demands very strict prescription. This means that exact number
of reps, number of sets and load (in terms of %1RM) is prescribed. Sometimes even
rest periods and tempo of exercise is prescribed. But what if we are wrong? What if we
are not very good at judging those numbers, what if we were too optimistic with the
1RM, or the numbers are off for certain individuals based on their day to day readiness
and improvement rate? What if some individuals emotionally don’t like (or respond to)
very strict programming (there might be those who prefer exactly what and how much
should be done; so we need to take that individual difference as well; more about this in
the next chapter). One simple solution to those issues is starting light, or as we mentioned
before, using EDM and a bit of buffer (being conservative and undershooting 1RM), so in
the case we are off with numbers, we still have MVP (minimum viable program) that we
can tweak through iterations and feedback. Prescribing training loads using %1RM is
the bread and butter of the percent-based approach, and the one that is the topic of this
manual since it can be implemented in other methods easily. Although very versatile,
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this approach needs some modification. These modifications will be explained after
other major prescription approaches are described.
Prescribing using subjective
indicators of exertion levels (RPE, RIR)
Another approach involves using subjective indicators of proximity to failure
(exhaustion) expressed as Reps-In-Reserve (RIR) or Rate-of-Perceived-Exertion
(RPE) (Tuchscherer, 2008; Zourdos et al., 2016, 2019; Helms et al., 2016, 2018a,b;
Carzoli et al., 2017). To my knowledge, Mike Tuchscherer (Tuchscherer, 2008) is the
first to outline sound training system using RPE approach for resistance training. I
personally favor RIR approach over RPE, because I believe it is easier to explain to the
athletes, but that is a personal choice (I have expanded on this topic in the Chapter 5).
For example, I might prescribe 3 sets of 5 with 2RIR (3x5 w/2RIR). Which reads:
3 sets of 5 with 2 reps left in reserve. Another nomenclature might be 3 sets of 5 with
7RM, which is equivalent of the above. This means: perform 3 sets of 5 with a weight
you can lift for 7 reps (5 + 2RIR = 7). Example program might be the following:
Workout 1: 3x8 w/3RIR
Workout 2: 3x6 w/2RIR
Workout 3: 3x4 w/1RIR
This method demands a lot of experience and honesty from lifters, which we all
know, lacks in team sport athletes. It is a great method to be used, since it allows built
in auto-regulation, which in other words, allows for taking into account changes in
readiness of the athletes (in plain English taking into account good and bad days) and
differences in adaptation speeds (one’s strength might improve faster than someone
else’s).
Using RIR is a major improvement of the methodology of the open sets, since
it takes into account exhaustion level (expressed as RIR) and avoids making athlete
“chase” (or “push”) the numbers (“Damn, I need to break last workout weights”).
Using Load-Exertion table, one can get the exact %1RM that needs to be lifted for a
certain number of reps and RIR, but again, this relies on the assumption of predictability
and stability. But even if you prescribe using subjective approach by rating RIR or RPE,
you can still provide approximate weight that needs to be lifted, which can speed up
the search of the weight that gives you number of reps at certain RIR. As already stated,
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Mike Tuchscherer made very elaborate planning system off RPE approach, and I highly
recommend checking his material.
In my opinion, this prescription approach might work for the responsible
athletes, such as strength-specialists, while it might be tricky to implement in with
certain groups of strength-generalist. Some modifications that could be implemented
in the %1RM approach will be explained later in the chapter.
Prescribing using Velocity
Based Training (VBT)
Using velocity to prescribe training is indeed a novel idea. There seems to be
relationship between velocity and proximity to failure (or Load-RIR relationship),
but it is still not very well researched (it is one of the topics of my PhD). If found to
be reliable and predictively valid, then rather than prescribing load using %1RM and
reps to be performed, one can prescribe Start Velocity and Stop Velocity of a set, e.g.
find a weight that initial rep yields 0.55-0.6m/s (Start Velocity) and do reps until you
hit 0.45m/s (Stop Velocity). Some coaches and researchers prefer to use velocity drop
(e.g. perform reps in a set until velocity drops below 10-20%). While utilizing VBT, an
athlete’s day-to-day readiness will be intrinsically taken into account (e.g. someone
having a really good or bad day) , as well as different speeds of adaptation (Jovanovic &
Flanagan, 2014).
However, as with any other method there are some assumptions that have to
be met. The major assumption of all VBT (Velocity Based Training) methodologies is
that concentric phase of a lift is done with the highest speed or intent to lift as fast as
possible. There also shouldn’t be any changes in exercise technique during the set, or
between sets. Otherwise, the velocity estimates will be completely off.
As it is, this method is reserved for individual strength athletes only (strength
specialists), particularly for grinding movements (see Table 4.4) and only few main
exercises. Team sport athletes (strength generalists) can still utilize external feedback
in term of speed, which can be great and useful addition to training (also yielding better
results in the ballistic movements), but utilizing some fancy VBT techniques with team
sport athletes can be unnecessary, or maybe even harmful, thing to do.
Some coaches believe that VBT is a panacea, but it still doesn’t answer major
questions that all coaches ask: “how should one train and how much” (in other words,
there is still Is/Ought gap)? VBT doesn’t answer these questions. In addition,there
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are a few basic “heuristics” (covered in this manual) that are more than enough in
helping with training decisions, without the need to buy the expensive equipment. Still,
objective immediate feedback is still a very useful feature in the ballistic movements for
both strength generalist and strength specialists.
Other prescription methods
It is important to mention that certain methods, such as isoPush (overcoming
isometrics) and isoinertial training (e.g. k-box, Versapulley) don’t utilize 1RM in
prescription, since the athletes are generating maximal amount of force against
the immovable or inertial load and get back as much as they put in. For this reason
their prescription will be a bit different compared to exercises with 1RM. It is worth
mentioning that these methods suffer from the same problems as VBT approach and
that is over-relying on the assumption that athletes are providing maximal intent all
the time (which is not always true and therefore might skew the data we collect).
Another example might be the use of body weight to prescribe (e.g. squat jumps
with 10% BW, or sled pushes with 40% of BW), but they still implement percent-based
approach. This also includes using max reps, as in “perform 3 sets of pull-up using
70% of you max pull-ups”. There are probably more approaches that involve some
fancy technology, but they are beyond simplicity, which is the goal of this manual.
Discussed so far are the major methods in prescribing strength training load.
The topic of this manual is the use of percent-based approach, not only as 'satisficing'
approach to prescription, but also as source of useful info for other approaches. For
example, using percent-based approach can give you a range of weight you can use
with the RIR prescription and VBT prescription. Sometimes we can combine the three,
which is the topic of the modifications of the percent-based approach.
Modifications of the percent-based
approach
Rep Zones
The first modification of the percent-based prescription that takes into account
uncertainties (of day-to-day readiness to perform or rate-of change/adaptation) are
Rep Zones. Let’s assume our main prescription is 3 x 5 @70% (3 sets of 5 reps with 70%
of 1RM). The rep zone approach would use the following modification:
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STRENGTH TRAINING MANUAL Volume One
3 x 4-6 @70%
Rather than prescribing exact number of reps, we prescribe a rep zone that fits
our objectives and takes uncertainty into account. We also give some sense of control to
the athletes (which is very motivating, at least for most athletes) by letting them choose
number of reps to perform32. This way we have locked in load and allowed for the reps to
vary. Rep zones can then be used in training cycles, or exercises where the objective is to
keep predictable load - for example when maximum strength (i.e., anaconda strength)
is the objective and we aim to work at certain percentage of 1RM. But to allow for some
wiggle room, we let athletes decide on the number of reps. We can also lock-in the RIR
(see modifications using RIR) if we prefer the subjective approach (for example 3 x 4-6
@70% w/4RIR; so the athlete decides to use 4-6 reps as long as the RIR is around 4).
On the flip side, rep zones are not the best option if the aim is to accumulate certain
number of lifts (e.g., in hypertrophy or armor building exercises or cycles).
The width of the Rep Zone can depend on various factors. For example, if we know
that athletes are tired (e.g. working out on first or second day after a match) we can
allow for a bigger buffer (especially in the direction of decreasing load): 3 x 3-5 @70%
. On the flip side, if we assume, with some certainty, that they might be feeling much
better, then we can increase the buffer (in the positive direction) and allow more reps
to be performed: 3 x 5-7 x 70%. The buffer can grow in both direction, e.g. 3 x 4-6 @70%
vs. 3 x 3-7 @70% and the use might depend on how much wiggle room you want to give
to the athletes or how much are you confident in the precision of your prescription
(to avoid ‘pushing’ too much). The extreme example of rep zone approach would be
prescribing %1RM and letting the athlete to chose number of reps (e.g. 3 x N @70%).
The selection of reps could be done based on the training diary (“What have I done
last time?”) and this is useful when we want to ‘accumulate’ reps (or to progress from
workout to workout using rep accumulation; see Vertical Planning in the next chapter).
Load Zones
Next modification are Load Zones. Similar to rep zones, load zones utilize a buffer
in %1RM used. Taking the same basic scheme of 3 x 5 @70%, the load zone approach
would use, for example:
3 x 5 @65-75%
32 As you will read in Chapter 5, this might be related to the feeling of pleasure/displeasure. Self-selection
of load or repetition creates a sense of autonomy and control, allowing athletes cognitively ‘reframe’ the
exercise experience (i.e., it is not something I must do, it is something I choose to do) (Ekkekakis, Parfitt &
Petruzzello, 2011). This can mean that this type of looser prescription might reduce displeasure and maybe
stress associated with strength training. In sports where there is higher frequency of competition, this
might mean a lot and can reduce unnecessary stress. This can be expanded to exercise selection within slot
(depending on the logistical constraints such as equipment) and can differ from athlete to athlete in terms
of preferences. Some athletes prefer more strict prescription, and some prefer more control. More about
these topics will be covered in Chapter 5.
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This approach allows the athlete to select appropriate load, based on his current
day-to-day readiness and rate of improvement. Load Zones approach is useful when
we want a stricter number of lifts (e.g., in hypertrophy or armor building phases or
exercises) and we are not much concerned with average %1RM (actually we are, but
if that is the objective we would be more inclined to ‘clamp’ %1RM using rep zones
modification). Similar to Rep Zones modification, the width and direction of the buffer
in %1RM used can depend on multiple factors. For example, in ‘pull the floor’ programs
we might give more wiggle room, and in ‘push the ceiling’ programs we want stricter
zones. The extreme example of Load zones would be to prescribe the number of sets
and reps and let the athlete choose the load (e.g. 3 x 5). And, you guessed correctly - this
is the open sets method of load prescription. The selection of the loads with the open
set approach will most likely be made based on training diary history (“What have I
done last time?”). Same to Rep Zones example of 3 x N @70%, the usage of this method
depends on how much we trust the athletes.
When I started working as S&C coach in soccer, I believed in “give them a fish and
feed them for a day, teach them how to fish and feed them for a lifetime” maxim, so I
gave my athletes training diaries, explained to them the concept of progressive overload
and gave them open sets. Disaster was an understatement. They have forgotten their
logs, lost them under treadmill, or just didn’t give a shit. There was nothing close to a
progressive overload. So, I decided to keep a log for them. I went around the gym like
a turkey trying to collect the numbers. That way I couldn’t coach and observe the lifts.
Disaster was an understatement here as well. However, I got smarter - I wrote the exact
set, reps and loads on a common sheet (actually multiple copies that were posted in the
gym so they can see it easily) and told them to do exactly as written. Of course they could
still cheat (I could easily check), but at least I could coach and progressive overload was
being implemented. But then again, on some exercises I was completely off (because I
had to estimate 1RMs for assistant moves), so the strict approach failed in that regard.
The solution was to allow for a stricter planning, while still allowing for some wiggle
room due to errors and individual differences. For that reason I started using the above
modifications. The long term progression is being followed (i.e., military’s commander
intent), while I allowed for local implementations (gave them freedom to wiggle if
needed).
One thing to keep in mind is that you can use different modifications for different
exercises, objectives and even individuals (since some individuals prefer more freedom,
and some don’t want to think much and just want to do what they have been told, or
depending how much you trust them). For example, main lifts can be programmed
more strictly, and you can give much more wiggle room for assistance exercises:
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Back Squat 3 x 4-6 @70%
Lunges 3 x 5 per side (open set)
We can also combine both rep zone and load zone approach to get something that
is really flexible:
3 x 4-6 @65-75%
This is also a viable option, especially when we are not much concerned with
hitting certain number of lifts or average load. We are interested in long term progression
(which will happen as long as we increase 1RM in our programs - see Rinse and Repeat
in Chapter 6, but allow great flexibility for athletes on the local or implementation
level). For some athletes this could be too much flexibility, so it is up to us to decide
regarding the appropriate modification.
Subjective Indicators
The third modification option would be to use subjective indicators, and in our
case that is RIR. So our main set and rep scheme of 3 x 5 @70% can become:
3 x 5 w/3RIR (reps prescribed, athlete finds load)
3 sets @70% w/3RIR (load prescribed, athlete selects reps)
This is very usable with more experienced lifters that are able to estimate RIR
with better precision. We can combine the subjective approach with both rep and load
zones as well:
3 x 5 @65-75% w/3RIR (reps prescribed, athlete selects load)
3 x 4-6 @70% w/3RIR (load prescribed, athlete selects reps)
3 x 4-6 @65-75% w/3RIR (athlete selects both reps and load,
as long as there are 3 RIR)
In the above cases, load or reps provide only guidelines (“Well what should I
lift?”), but ultimately, it is RIR that athlete should pay attention to.
When it comes to team sport athletes, using subjective indicators in prescribing
training can be a double edge sword. They provide huge flexibility and take into account
individual differences, but that flexibility can also be problematic. As mentioned before,
athletes can start screwing around, or they might not understand what is being asked
of them. Some might even think that you have no clue what are you doing, so you are
giving them loose prescriptions. Some don’t give a damn and don’t want to think too
much about lifting weights and they prefer to get it over with and play/practice their
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sport. Therefore,as a coach, you have to be smart and decide what is the best approach
with regards to your current situation that you have to work with.
Velocity Based Training
Fourth modification is using Velocity Based Training (VBT). As already outlined, one
implementation of VBT to training load prescription involves using some combination
of Start Velocity and Stop Velocity. Using velocity, instead of %1RM and number of reps,
takes into account day-to-day variability and different rate-of-change (adaptation)
of the individual and it deals with them intrinsically. But it has a lot of assumptions and
measuring to be done.
To be done precisely, VBT profiling needs to be done for both individual and
exercise of interest (although some generalized numbers could be use as a starting
point, or MVP). One example of VBT prescription might involve prescribing load and
stop velocity:
3 sets @75% until you hit 0.3 m/s
It is very important to emphasize that VBT assumes maximal effort (intent
to lift fast) during the concentric phase of the lift, as well as the same depth of the
exercise, otherwise it is not very usable. Even more complex prescription might involve
prescribing start velocity:
3 sets from 0.5 to 0.3 m/s
In this case athlete selects the weight that gives her initial velocity of around
0.5m/s and performs reps until that velocity reaches 0.3 m/s. To make this search
quicker, we might provide some initial values for the weight:
3 sets from 0.5 to 0.3 m/s (@70-75% 1RM)
But similar to the subjective approach, this load prescription is only a guideline
and the athlete should focus on speed.
VBT is mostly applicable with ballistic movements, since velocity represent
instant (after each rep) feedback that could be motivating. Sometimes, this feedback
can be also tricky (for example trying to increase peak velocity during power clean,
athlete might alter technique and lose the objective of the exercise). Another use of VBT
is in quality control - or using Velocity Stop or % drop (how much % loss in velocity we
allow before stopping the set).
Yet another use of VBT involves estimating daily 1RM from warm-up sets, and
using that number to prescribe training rather than using pre-phase 1RM. To make this
estimate reliable and usable for prescription, strict technique (especially using same
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depth and pause at the bottom of the lift or avoid using SSC) and intent to lift as fast
as possible must be followed. Jury is still out on how useful this approach is and the
research on this topic is underway (at the time of this writing, your author is preparing
his PhD on this very topic).
In my opinion, when it comes to team sports, VBT should be used sparingly for
a few major lifts (mostly ballistic) because it is major pain in the arse to explain and
torture athletes with measurement. Just keep it as a viable option
Time and Reps Constraints
Fifth and the last modification is Time and Reps Constraints. This is the most
flexible of the approaches and it gives athletes certain time frame (e.g. 10-20min) to
finish certain total number of reps (with certain limitations/constraints). For example,
our 3 x 5 @70% might be prescribed as: In 10min perform 15 reps @70%. It is up to athlete
to decide how many sets to perform, how many reps to perform and with how long
pause. We can make few variants of this using the above modifications:
In 10min perform 15-20 reps @70%
In 10min perform 15 reps @65-75%
In 10min perform 15-20 reps @65-70%
In 10min perform 15-20 reps @65-70% w/not less than 3RIR per set
In 10min perform AMRAP @65-70% w/not less than 3RIR per set,
(AMRAP - as many reps as possible)
In 10min perform AMRAP @65-70% using 3-5 reps per set
In 10min perform AMRAP with 4-6 reps per set @65-70%
In 10min perform 15-20 reps @65-70% with no less than 3 reps per set
In 10min perform AMRAP reps @65-70% with no less than 3 reps per set
In 10min perform AMRAP reps @65-70% with no less than 2min break
In 10min perform AMRAP reps @65-70% with no longer than 3min break
Variations are endless and it is up to your coaching creativity to create a constraints
that let the aimed objectives emerge (be it certain number of total reps at certain %1RM
being performed, and so forth). This is viable option with some exercises and objectives.
For example, you might say “You have 10min to do 100 push-ups”, or “10min to do sets
of 1 of hang clean with 85%, AMRAP”, or even use Crossfit prescription of EMOM (every
minute on the minute): “In 10min, EMOM 2 reps with 75% hang clean” to be certain
they don’t kill themselves with short breaks or forcing reps.
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Even if you do not plan using this approach, providing time constraints (and
making it transparent by using a big timer on the wall) can get team athletes more
productive. For example, you might have a super set (A1. Back Squat, A2. Pull-Ups, A3.
Abs Roll-out, A4. Hip stretch) and to keep a group of athletes punctual (especially if the
next group is coming in), you might also state that they have 15-20minutes to finish
the prescribed sets. This works like a charm. Just put the timer on the wall and let them
see it.
In the following Table there are all modifications listed for the easier summary
(simplified).
Original prescrip�on
Open Sets
Rep Zone
Load Zone
Combined
Subjec�ve
VBT
Time & Rep constraints
3 x 5 @70%
3x5
3 x 4-6 @70%
3 x 5 @65-75%
3 x 4-6 @65-75%
3 x 4-6 @70% w/3RIR
3 sets @75% u/0.3m/s
In 10min perform 15-20reps @70%
Table 4.23. Set and rep scheme modifications. See text for further examples
Prediction and monitoring
Before jumping to the strength training planning in Chapter 5, it is important to
introduce few load (dose)33 monitoring metrics that are commonly used, as well as to
introduce few novel ones. As you will soon see, all these represent Small Worlds - or a
models with assumptions that attempt to represent Large World with a simple number.
Nothing wrong with this of course. What is problematic is forgetting the distinction and
trying to optimize the whole training based on few numerical aggregates. If you check the
Figure 2.13 in Chapter 2, you can see that these data represent only one source of insight
when making decision. Thus, they are needed and important, but just don’t forget that
they represent aggregated summary of simplified Large World. It is very easy to fall
for the Small World narrative of trying to optimize one metric to maximize training
effects. The true story is that we do not know what variable drives (is associated or is
causal) the training effects. Similarly, in a Kuhnian sense (Dienes, 2008), we do need to
33 Here, the term ‘load’ differs from the term load as part of intensity trinity (weight on the bar, %1RM).
Here the load is the “the dose” or “stress” and it is also multicomponent, consisting of volume, intensity
and density components.
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STRENGTH TRAINING MANUAL Volume One
collect these studies and various models to push the scientific revolution forward, but
the goal is not to become Intellectual Yet Idiot (IYI, to paraphrase Nassim Taleb) that
sells this as objective ‘evidence-based’ approach. There is much more we do not know
and that we do not capture with simple metrics.
Chapter 5 will expand more on the topic and the concept of load from a conceptual
perspective, but in this chapter I will cover the most common metrics used to track the
strength training load.
Table 4.24 contains 3 sets (8 reps at 73%, 6 reps at 79%, and 4 reps at 86%) with
athlete subjective rating of exertion (RIR). I have provided few summary metrics that I
will explain below.
Set
1
2
3
Reps
8
6
4
1RM
150
150
150
%1RM
73%
79%
86%
Load
110
119
129
RIR
4
2
0
NL
8
6
4
18
aRI Tonnage
73%
876
79%
711
86%
516
79%
2103
78%
Impulse
5.84
4.74
3.44
14.02
INOL pred1RM prox1RM
0.30
153
92%
0.29
150
95%
0.29
146
97%
0.87
153
95%
Table 4.24. Common training load summary metrics
Each set is summarized, and then at the bottom the workout summary is provided.
Here are the columns
Set - Indicate the order of the set.
Reps - Indicate how many reps has been planned/performed (here the assumption
is that number of reps planned is equal to number of reps performed).
1RM - Represents athletes 1RM of the exercise (or EDM) used to estimate load.
%1RM - Percentage of the 1RM used.
Load - Calculated weight that needs to be lifted using athlete 1RM and %1RM of
the program (Load = 1RM x %1RM).
RIR - Reps-In-Reserve. This is a subjective rating that athlete gives after the
completion of the set.
The above variables represent the usual planning parameters (with the exception
of RIR, that can be planned in advance and that can help in selecting the %1RM and
reps, but it can also be subjective rating given by the athlete at the end of each set). The
variable below are the aggregates or the summaries of each set.
NL- represent number of lifts (or reps). The summary at the bottom of the table
represents simple sum
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MLADEN JOVANOVIĆ
aRI- represents average relative intensity (%1RM) of the set. The summary at the
bottom of the table can be calculated in two ways. First option (first number; 79%) is
the simple average of three sets ((73% + 79% + 86%) / 3 = 79%). But we can also calculate
it using reps, since each set contributed different number of reps to a grand summary.
This is done using the weighted average where set percentage is multiplied by number
of reps, and finally divided by NL. This is indicated by the second number (78%) and it
is calculated the following way: (8 x 73% + 6 x 79% + 4 x 86%) / (8 + 6 + 4). As you will
soon see, and I suggest you create an Excel workbook and play with the numbers, this
is equal to Impulse / NL. With this very simple example, one can see the “Small World”
model at hand - we immediately have the assumptions in the simple aggregate. You can
also use average load metric, where instead of %1RM you use average weight.
Tonnage- Tonnage is a very common metric and it represents Reps x Load. The
summary at the bottom of the table is a simple sum of tonnage of each set. Tonnage
corresponds to mechanical work, but without the distance component.
Impulse- Impulse is relative tonnage. Imagine doing 3x5 @75% for bench press
(1RM = 100kg) and deadlift (1RM = 200kg). Tonnage will be double for the deadlift since
the higher absolute load used. Impulse is there to fix this issue and allow comparison
between different exercises and individuals possible. Impulse is calculated by
multiplying Reps x %1RM for each set, and the summary at the bottom of the table is the
simple sum. A simpler way to calculate impulse is to use Tonnage / 1RM. Thus, impulse
also tells you how many times you lifted your 1RM.
INOL- Intensity of Lift, is the metric created by Hristo Hristov (Hristov, 2005)
to improve training prescription using the Prilepin Table. INOL is calculated by the
following equation for every set: NL / (100 - 100 x %1RM). For example, set one (8 reps
@73%) has INOL equal to 8 / (100 - 73), or 8 / 27, which is equal to 0.3. The summary
at the bottom of the table is the simple sum of each set INOL. Hristov suggested the
following training guidelines using INOL metric:
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STRENGTH TRAINING MANUAL Volume One
Workout INOL Guidelines (per exercise)
INOL
Sugges�on
< 0.4
Too few reps, not enough s�mulus?
0.4 - 1
Fresh, quite doable and op�mal if you are not accumula�ng fa�gue
1-2
Tough, but good for loading phases
>2
Brutal
Weekly INOL Guidelines (per exercise)
INOL
Sugges�on
<2
Easy, doable, good to do a�er more �ring weeks and prepeaking
2-3
Tough but doable, good for loading phases between
3-4
Brutal, lots of fa�gue, good for a limited �me and shock microcycles
>4
Are you out of your mind?
Table 4.25. Hristo Hristov guidelines for using INOL metric (Hristov, 2005)
All the above load metrics can be reported per intensity (%1RM) bracket rather
than solely with the grand total. For example, one might be interested how many reps
are done in the 80-90% range, what is the impulse in that range and so forth. It is
always easy to get fancier with load metrics (for example you might calculate the work
done using distances that barbell travel, or density using time to complete, which
can be useful metric for some type of training, such as Mongoose Persistence or EDT
- Escalatory Density Training (Staley, 2005)), but the objective is to be as simple as
possible and get few actionable metrics. Having said this, I will contradict myself and
introduce some novel metrics in a few paragraphs. To further understand why is this
needed, consider the following examples.
The two metrics that are left are my invention and are more related to 1RM
prediction and the estimate of proximity to 1RM than load:
pred1RM-Predicted 1RM is the equation already introduced. It is used to predict
1RM from load used, number of reps done and athlete RIR subjective rating:
1RM = (Weight x (Reps + RIR) x 0.0333) + Weight
This is a tool to track (embedded testing) effects - what is potentially happening
to 1RM, without directly testing it (either with a true test, or with reps-to-failure).
Please note that this prediction is based on Epley’s formula and subjective rating
given by the athlete. For this reason it should be supplemented with something more
demonstrable, such as plus set. Other options might involve predicted 1RM from loadvelocity relationship (using 2-3 warm-up sets, e.g., 40-60-80%) and the known v1RM
(velocity at 1RM) which can be personalized or group averaged. The goal here is not
perfect prediction, but a gauge into trends over time that can supplement decision
making after a training sprint or a phase.
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MLADEN JOVANOVIĆ
prox1RM- Proximity to 1RM represent metric that estimates how close to 1RM
a given set is. For example, if you do 5 reps with 100kg (regardless of RIR, since we are
interested only in what is manifested), that would correspond to 1RM of (5 x 100 x 0.033)
+ 100, or 116.5kg. If your 1RM is equal to 130kg, then the ratio, or prox1RM is equal to
116.15 / 130, or 89%. This metric is useful to estimate how aggressive your are with
your progressions (assuming no change in the pre-phase 1RM that we use to estimate
loads). The higher the prox1RM, the more you are pushing it (will come back to this
metric in Chapter 5 when discussing push the ceiling versus pull the floor approaches to
planning strength training). Prox1RM is thus calculated:
prox1RM = ((Weight x Reps x 0.0333) + Weight) / 1RM
or using known %1RM
prox1RM = (%1RM x Reps x 0.0333) + %1RM
When you use known %1RM, rather than load, you can check the aggressiveness
of your planning (given Epley’s formula). Thus, prox1RM is more of a planning tool,
than monitoring tool. Table 4.26 contains calculated prox1RM using Load-Exertion
table. The take home message is that lower the RIR, higher the prox1RM.
Exer�on / Reps in Reserve (RIR)
% EDM
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
0 RIR
1 RIR
2 RIR
3 RIR
4 RIR
5 RIR
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
0 RIR
1 RIR
2 RIR
3 RIR
4 RIR
5 RIR
6 RIR
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
6 RIR
1
2
3
4
5
6
7
8
9
10
11
12
13
14
7 RIR
1
2
3
4
5
6
7
8
9
10
11
12
13
Exer�on / Reps in Reserve (RIR)
8 RIR
9 RIR
10 RIR
11 RIR
12 RIR
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
1
2
3
4
5
6
7
8
7 RIR
8 RIR
9 RIR
10 RIR
11 RIR
12 RIR
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
50%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
50%
49%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
50%
49%
48%
% EDM
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
0 RIR
1 RIR
2 RIR
3 RIR
4 RIR
5 RIR
6 RIR
7 RIR
8 RIR
9 RIR
10 RIR
11 RIR
12 RIR
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
97%
97%
97%
97%
97%
97%
97%
97%
98%
98%
98%
98%
98%
98%
98%
98%
98%
98%
98%
94%
94%
94%
94%
95%
95%
95%
95%
95%
95%
95%
95%
96%
96%
96%
96%
96%
96%
91%
91%
92%
92%
92%
92%
93%
93%
93%
93%
93%
93%
93%
94%
94%
94%
94%
89%
89%
89%
89%
90%
90%
90%
90%
91%
91%
91%
91%
91%
92%
92%
92%
86%
86%
87%
87%
88%
88%
88%
88%
89%
89%
89%
89%
90%
90%
90%
84%
84%
85%
85%
85%
86%
86%
86%
87%
87%
87%
88%
88%
88%
82%
82%
83%
83%
83%
84%
84%
84%
85%
85%
85%
86%
86%
80%
80%
81%
81%
81%
82%
82%
83%
83%
83%
84%
84%
78%
78%
79%
79%
80%
80%
80%
81%
81%
82%
82%
76%
76%
77%
77%
78%
78%
79%
79%
80%
80%
74%
74%
75%
76%
76%
77%
77%
78%
78%
72%
73%
73%
74%
74%
75%
76%
76%
0 RIR
1 RIR
2 RIR
3 RIR
4 RIR
5 RIR
6 RIR
7 RIR
8 RIR
9 RIR
10 RIR
11 RIR
12 RIR
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
97%
97%
97%
97%
97%
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96%
91%
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94%
94%
94%
94%
94%
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94%
89%
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90%
90%
90%
90%
91%
91%
91%
91%
91%
92%
92%
92%
92%
92%
92%
93%
86%
86%
87%
87%
88%
88%
88%
88%
89%
89%
89%
89%
90%
90%
90%
90%
90%
91%
91%
91%
84%
84%
85%
85%
85%
86%
86%
86%
87%
87%
87%
88%
88%
88%
88%
88%
89%
89%
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89%
82%
82%
83%
83%
83%
84%
84%
84%
85%
85%
85%
86%
86%
86%
87%
87%
87%
87%
88%
88%
80%
80%
81%
81%
81%
82%
82%
83%
83%
83%
84%
84%
84%
85%
85%
85%
85%
86%
86%
86%
78%
78%
79%
79%
80%
80%
80%
81%
81%
82%
82%
82%
83%
83%
83%
84%
84%
84%
84%
85%
76%
76%
77%
77%
78%
78%
79%
79%
80%
80%
80%
81%
81%
81%
82%
82%
82%
83%
83%
83%
74%
74%
75%
76%
76%
77%
77%
78%
78%
78%
79%
79%
80%
80%
80%
81%
81%
81%
82%
82%
72%
73%
73%
74%
74%
75%
76%
76%
76%
77%
77%
78%
78%
79%
79%
79%
80%
80%
80%
81%
Exer�on / Reps in Reserve (RIR)
# Reps
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Exer�on / Reps in Reserve (RIR)
# Reps
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Table 4.26. Proximity to 1RM (prox1RM) calculated using Load-Exertion table
It is important to understand that all the metrics mentioned can be considered
both as planning tools, as well as monitoring tools. This is pretty much related to before
vs. after, and for this reason it might be interested to collect both, as planned vs. realized.
This type of analysis can be done during the research and review phase and it can be quite
insightful to figure out what works and what needs adjustment. When it comes to 1RM
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STRENGTH TRAINING MANUAL Volume One
and all the metrics based on it, one can use pre-cycle 1RM (used to estimate the weight
to be lifted), as well as to use pred1RM (either using the RIR or using velocity-based
predictions) to adjust the metrics. For example, if you plan doing 3x5 with 80% and
you use your 1RM which is 150kg, then the load you plan lifting is 120kg. Training load
metrics, such as aRI, INOL, Impulse and all other, if bracketing technique is used (i.e. per
intensity zone), use this 80% estimate. This is great for planning ahead and assuming
pre-cycle 1RM (the one we used to establish weights) doesn’t change. But what if you
feel really well on a particular day (which is normal variability in performance and thus
1RM) and your pred1RM shows 160kg? Then all the realized relative metrics will be off.
Thus, it could be useful to use adjusted as well as as-planned load metrics (see Table
4.27). This can of course become major pain in the ass, so I recommend collecting the
basic metrics, but reviewing and adjusting more frequently.
Set
1
2
3
Reps
8
6
4
1RM
150
150
150
%1RM
73%
79%
86%
Load
110
119
129
RIR
4
2
0
NL
8
6
4
18
aRI Tonnage
73%
876
79%
711
86%
516
79%
2103
78%
Impulse
5.84
4.74
3.44
14.02
INOL pred1RM prox1RM
0.30
153
92%
0.29
150
95%
0.29
146
97%
0.87
153
95%
aRI_adj
71%
79%
88%
80%
78%
Impulse_adj
5.72
4.74
3.53
13.98
INOL_adj prox1RM_adj
0.28
90%
0.29
95%
0.34
100%
0.91
95%
Table 4.27. Adding adjusted metrics based on realized performance (using pred1RM)
The long story short is that we need to differentiate between planned vs. realized
load metrics. They can be adjusted based on performed training and using pred1RM,
or it could be simpler than that using actually reps done by the athlete, and so forth.
To make it simpler, I will assume they are equal from now on. Now let’s look at the
following two examples in Table 4.28 Try to spot the issues with contemporary load
metrics:
Sets
3
3
1
10
Reps
5
5
10
1
1RM
150
150
150
150
%1RM
80%
80%
75%
75%
Load
120
120
113
113
RIR
3
1
0
9
NL
15
15
10
10
aRI Tonnage
80%
1800
80%
1800
75%
1125
75%
1125
Impulse
12.00
12.00
7.50
7.50
INOL pred1RM prox1RM
0.75
152
93%
0.75
144
93%
0.40
150
100%
0.40
150
77%
Table 4.28. Two examples of set and rep schemes and contemporary load metrics.
Can you spot the issues?
Table 4.28 gives two examples (1) 3 sets of 5 with 120kg but done at RIR 3 vs 1,
and (2) 10x1 vs 1x10 with 150kg. With the exception of pred1RM and prox1RM, other load
metrics give equal results for two different workouts in the two examples. Doing 3x5
with 150kg with 3RIR or 1RIR gives the same load metrics, which implies that proximity
to failure is not taken into consideration with the current metrics. But we all bloody
know that these two sets will create different stress on the lifter. Same thing with the
second example: doing 1 set of 10, versus 10 sets of 1 gives equal load metrics results.
Which brings me back to the “Small World” problem - these metrics are simplified
and imperfect representations of the “Large World” complexities. Hence my pluralistic
stance towards philosophy of science (see Chapter 1). Again, the problem is not using
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MLADEN JOVANOVIĆ
Small Worlds, but assuming they are objective truth and publishing using “EvidenceBased Approach”. Imagine (well you do not need to imagine) a bunch of lab coats trying
to figure out the ‘optimal’ distribution of Small World metrics to minimize/maximize
training effect and calling it ‘objective’ or ‘evidence-based approach’.
Well, enough of my rant on lab coats. The potential addition to the above metrics
is to somehow rate reps differently based on how close to failure they are. Reps closer to
failure (lower RIR) get more weight than reps done away(higher RIR) from failure. One
such metric is called exertion load (XL), and it is being developed by Robert Frederick
(Frederick, 2017, 2018). Figure 4.9 contains table and chart outlining non-linear
weighting of the reps depending of how close they are to failure. The formula for weight
is the following:
Weight
1.000
0.807
0.651
0.525
0.423
0.341
0.275
0.222
0.179
0.144
0.116
0.094
0.076
0.061
0.049
0.040
1.200
1.000
0.800
Weight
Rep In Reserve
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
0.600
0.400
0.200
0.000
0
2
4
6
8
10
12
14
16
Rep In Reserve
Figure 4.9. Exertion load weights. Reps closer to failure get more weight
Similarly to how we calculate tonnage, this weight is multiplied with the (absolute)
load. Table 4.29 contains two examples for one set of 5 repetition with 120kg, but one
with 1RIR and the other with 3RIR.
Set of 5reps with 120kg reaching 1RIR on the last rep
Load
120
120
120
120
120
Rep
1
2
3
4
5
XL (peripheral)
XL (central)
329.54
65.91
RIR
5
4
3
2
1
rep Weight
0.34
0.42
0.52
0.65
0.81
Set of 5reps with 120kg reaching 3RIR on the last rep
XL
40.96
50.78
62.96
78.06
96.78
329.54
Load
120
120
120
120
120
Rep
1
2
3
4
5
XL (peripheral)
XL (central)
214.37
42.87
RIR
7
6
5
4
3
rep Weight
0.22
0.28
0.34
0.42
0.52
XL
26.64
33.03
40.96
50.78
62.96
214.37
Table 4.29. Example calculus for the exertion load (XL). Robert Frederick differentiates between
peripheral XL (pXL) and central XL (cXL) (Frederick, 2017, 2018).
Robert Frederick differentiates between peripheral XL (PXL) and central XL
(CXL) (Frederick, 2017, 2018). Peripheral XL is a sum of XL of every rep, while CXL is
PXL divided by number of reps. According to Frederic, PXL correlates to peripheral load
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STRENGTH TRAINING MANUAL Volume One
causing peripheral fatigue and represents hypertrophy stimulus, while CXL correlates
to central load causing central fatigue and represents strength stimulus. XL metrics can
also be expressed relatively (similar to tonnage vs impulse), where rPXL is the sum of
rep weights multiplied by %1RM (rather than load), or easier, it represents PXL divided
by 1RM.
Let's see a few examples combining all the metrics including novel XL metrics.
3x5 with different RIR ra�ng
3x3 vs 3x5 with equal RIR
5x5 with different 1RMs
1x10 vs 10x1
More reps at same load
3x10
Normal 3x10 @70%
vs
Myoreps (restpause)
Myoreps
Sets
3
3
3
3
3
5
5
1
10
3
3
1
1
1
Total
1
1
1
1
1
1
1
Total
Reps
5
5
5
5
3
5
5
10
1
8
6
10
10
10
1RM
150
150
150
150
150
150
100
150
150
150
150
150
150
150
%1RM
80%
80%
80%
81%
86%
75%
75%
75%
75%
70%
70%
70%
70%
70%
Load
120
120
120
122
129
113
75
113
113
105
105
105
105
105
RIR
1
3
5
2
2
2
2
0
9
3
5
3
2
1
12
4
4
3
3
2
2
150
150
150
150
150
150
150
70%
70%
70%
70%
70%
70%
70%
105
105
105
105
105
105
105
1
1
0
1
0
1
0
NL
15
15
15
15
9
25
25
10
10
24
18
10
10
10
30
12
4
4
3
3
2
2
30
aRI Tonnage
80%
1800
80%
1800
80%
1800
81%
1823
86%
1161
75%
2813
75%
1875
75%
1125
75%
1125
2520
70%
70%
1890
70%
1050
70%
1050
70%
1050
70%
3150
70%
1260
70%
420
70%
420
70%
315
70%
315
70%
210
70%
210
70%
3150
Impulse
12.00
12.00
12.00
12.15
7.74
18.75
18.75
7.50
7.50
16.80
12.60
7.00
7.00
7.00
21.00
8.40
2.80
2.80
2.10
2.10
1.40
1.40
21.00
INOL
0.75
0.75
0.75
0.79
0.64
1.00
1.00
0.40
0.40
0.80
0.60
0.33
0.33
0.33
1.00
0.40
0.13
0.13
0.10
0.10
0.07
0.07
1.00
PXL
988.62
643.11
418.35
807.33
618.56
1245.88
830.59
513.78
162.48
701.31
402.75
251.59
311.94
386.76
950.29
404.58
252.51
313.08
208.08
257.99
152.99
189.69
1778.92
CXL
197.72
128.62
83.67
161.47
206.19
249.18
166.12
51.38
162.48
87.66
67.12
25.16
31.19
38.68
95.03
33.72
63.13
78.27
69.36
86.00
76.50
94.84
501.81
rPXL
6.59
4.29
2.79
5.38
4.12
8.31
8.31
3.43
1.08
4.68
2.68
1.68
2.08
2.58
6.34
2.70
1.68
2.09
1.39
1.72
1.02
1.26
11.86
rCXL
1.32
0.86
0.56
1.08
1.37
1.66
1.66
0.34
1.08
0.58
0.45
0.17
0.21
0.26
0.63
0.22
0.42
0.52
0.46
0.57
0.51
0.63
3.35
pred1RM
144
152
160
150
150
139
92
150
150
143
143
150
147
143
147
150
prox1RM
93%
93%
93%
94%
95%
87%
87%
100%
77%
89%
84%
93%
93%
93%
93%
98%
150
98%
Table 4.30. Few set and rep examples and accompanying load metrics
The most interesting example from Table 4.30, is the 3x10 versus Myoreps
(Fagerli, 2012). Myoreps, or Rest-Pause, involves using one set to failure or very close
to it (the first set, usually referred to as activation set), and then, after a short break
(usually few breath cycles) performing multiple sets also very close to failure. Table 4.30
utilized 12-4-4-3-3-2-2 Myoreps. What is interesting to note, is that contemporary
metrics are equal in 3x10 and Myoreps, while XL metrics show clear benefit of Myoreps
in terms of PXL (1779 vs. 950) and CXL (502 vs. 95) while keeping in mind that the
number of lifts is the same for both conditions.
Table 4.31 contains example for 3x3 @90% and cluster sets (3x5 @90%).
Cluster sets involve taking a short break (racking the weight) after every rep. Table is
represented ‘per-rep’ with summaries for every set and a summary for the workout.
This was needed because RIR is different for every rep during the cluster method. Please
keep in mind that this is a fictive example and not the real data collected.
What can be seen from the Table 4.31 is that cluster sets accumulate more reps
(15 vs. 9) at 90%, with lower RIR (estimated with avgRIR, which takes into accord RIR
rating of every rep, rather than only taking last rep’s RIR as the set representative).
Cluster set showed higher PXL (1444 vs. 995) but lower CXL (289 vs 332). However,
when divided by number of lift, both PXL (96 vs. 110 per rep) and CXL (19 vs. 37 per
rep) were lower. I might speculate that clusters allow more reps accumulated at higher
%1RM with lower load penalty (as expressed by CXL and PXL per rep).
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MLADEN JOVANOVIĆ
If having been a keen reader, you might have realized that I used opposite
inferences - with Myoreps I glorified higher XL metrics, while with cluster reps I
glorified lower XL metrics. And that is because I am a biased piece of crap and I explained
the causes AFTER the fact (and with my priori belief that myoreps and cluster sets are
better than straight sets). As a side note, this is the reason why studies need to be preregistered in the first place, otherwise we all fit our narrative to the analysis. The point
is, that we do not know, with great confidence, what metrics, as constructs, correlate
(or predict) with improvements in hypertrophy and strength during strength training.
With Myoreps, I assumed it is the XL metric, while with cluster sets I assumed it is
the number of reps over 90% 1RM. The take home message is that these are needed
“Small World” models, but at the end of the day, we still don’t know much about causal
networks (hence my appreciation of uncertainty with Agile Periodization framework).
Unless you asked ‘evidence-based’ overconfident lab coats, of course.
Straight sets 3x3 @90% (135kg)
Set Summary
Set Summary
Set
1
1
1
Rep
1
2
3
1RM
150
150
150
%1RM
90%
90%
90%
Load
135
135
135
RIR
2
1
0
NL
1
1
1
aRI
90%
90%
90%
Tonnage
135
135
135
Impulse
0.90
0.90
0.90
INOL
0.10
0.10
0.10
PXL
87.82
108.88
135.00
CXL
29.27
36.29
45.00
rPXL
0.59
0.73
0.90
rCXL
0.20
0.24
0.30
1
1
1
3
1
2
3
150
150
150
150
70%
90%
90%
90%
105
135
135
135
1.00
2
1
0
3
1
1
1
90%
90%
90%
90%
405
135
135
135
2.70
0.90
0.90
0.90
0.30
0.10
0.10
0.10
331.70
87.82
108.88
135.00
110.57
29.27
36.29
45.00
2.21
0.59
0.73
0.90
0.74
0.20
0.24
0.30
1
1
1
3
1
2
3
150
150
150
150
70%
90%
90%
90%
105
135
135
135
1.00
2
1
0
3
1
1
1
90%
90%
90%
90%
405
135
135
135
2.70
0.90
0.90
0.90
0.30
0.10
0.10
0.10
331.70
87.82
108.88
135.00
110.57
29.27
36.29
45.00
2.21
0.59
0.73
0.90
0.74
0.20
0.24
0.30
3
150
70%
105
1.00
3
90%
405
2.70
0.30
331.70
110.57
2.21
0.74
avg1RM avg%1RM
150
90%
avgLoad
135
avgRIR
1.00
NL
9
aRI
90%
Tonnage
1215
Impulse
8.10
INOL
0.90
PXL
995.11
CXL
331.70
rPXL
6.63
rCXL
2.21
%1RM
90%
90%
90%
90%
90%
70%
90%
90%
90%
90%
90%
70%
90%
90%
90%
90%
90%
70%
Load
135
135
135
135
135
105
135
135
135
135
135
105
135
135
135
135
135
105
RIR
2
2
2
1
1
1.60
2
2
2
1
1
1.60
2
2
2
1
1
1.60
NL
1
1
1
1
1
5
1
1
1
1
1
5
1
1
1
1
1
5
aRI
90%
90%
90%
90%
90%
90%
90%
90%
90%
90%
90%
90%
90%
90%
90%
90%
90%
90%
Tonnage
135
135
135
135
135
675
135
135
135
135
135
675
135
135
135
135
135
675
Impulse
0.90
0.90
0.90
0.90
0.90
4.50
0.90
0.90
0.90
0.90
0.90
4.50
0.90
0.90
0.90
0.90
0.90
4.50
INOL
0.10
0.10
0.10
0.10
0.10
0.50
0.10
0.10
0.10
0.10
0.10
0.50
0.10
0.10
0.10
0.10
0.10
0.50
PXL
87.82
87.82
87.82
108.88
108.88
481.22
87.82
87.82
87.82
108.88
108.88
481.22
87.82
87.82
87.82
108.88
108.88
481.22
CXL
17.56
17.56
17.56
21.78
21.78
96.24
17.56
17.56
17.56
21.78
21.78
96.24
17.56
17.56
17.56
21.78
21.78
96.24
rPXL
0.59
0.59
0.59
0.73
0.73
3.21
0.59
0.59
0.59
0.73
0.73
3.21
0.59
0.59
0.59
0.73
0.73
3.21
rCXL
0.12
0.12
0.12
0.15
0.15
0.64
0.12
0.12
0.12
0.15
0.15
0.64
0.12
0.12
0.12
0.15
0.15
0.64
avg1RM avg%1RM
150
90%
avgLoad
135
avgRIR
1.60
NL
15
aRI
90%
Tonnage
2025
Impulse
13.50
INOL
1.50
PXL
1443.67
CXL
288.73
rPXL
9.62
rCXL
1.92
Set Summary
Workout
Sets
3
avgReps
3
Cluster sets 3x5 @90% (135kg)
Set Summary
Set Summary
Set Summary
Workout
Set
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Sets
3
Rep
1
2
3
4
5
5
1
2
3
4
5
5
1
2
3
4
5
5
avgReps
5
1RM
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
Table 4.31. Straight sets 3x3 @90% versus Cluster Sets 3x5 @90%
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STRENGTH TRAINING MANUAL Volume One
To wrap this segment on XL metrics, the following two tables (Table 4.32 and
Table 4.33) contains calculated rPXL and rCXL for Load-Exertion table.
Exer�on / Reps in Reserve (RIR)
% 1RM
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
0 RIR
1 RIR
2 RIR
3 RIR
4 RIR
5 RIR
6 RIR
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
0 RIR
1 RIR
2 RIR
3 RIR
4 RIR
5 RIR
6 RIR
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
1
2
3
4
5
6
7
8
9
10
11
12
13
14
7 RIR
1
2
3
4
5
6
7
8
9
10
11
12
13
Exer�on / Reps in Reserve (RIR)
8 RIR
9 RIR
10 RIR
11 RIR
12 RIR
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
1
2
3
4
5
6
7
8
7 RIR
8 RIR
9 RIR
10 RIR
11 RIR
12 RIR
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
50%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
50%
49%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
50%
49%
48%
% 1RM
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
0 RIR
1 RIR
2 RIR
3 RIR
4 RIR
5 RIR
6 RIR
7 RIR
8 RIR
9 RIR
10 RIR
11 RIR
12 RIR
1.00
1.69
2.23
2.63
2.92
3.12
3.26
3.35
3.40
3.43
3.43
3.41
3.39
3.35
3.31
3.26
3.22
3.16
3.11
3.06
0.76
1.32
1.75
2.06
2.29
2.45
2.56
2.63
2.68
2.70
2.70
2.69
2.67
2.64
2.61
2.58
2.54
2.50
2.46
0.59
1.04
1.37
1.62
1.80
1.92
2.01
2.07
2.11
2.12
2.13
2.12
2.11
2.09
2.06
2.03
2.01
1.98
0.46
0.81
1.07
1.27
1.41
1.51
1.58
1.63
1.66
1.67
1.68
1.67
1.66
1.65
1.63
1.61
1.59
0.36
0.64
0.84
1.00
1.11
1.19
1.25
1.28
1.31
1.32
1.32
1.32
1.31
1.30
1.29
1.27
0.28
0.50
0.66
0.78
0.87
0.94
0.98
1.01
1.03
1.04
1.04
1.04
1.04
1.03
1.02
0.22
0.39
0.52
0.62
0.69
0.74
0.77
0.80
0.81
0.82
0.82
0.82
0.82
0.81
0.18
0.31
0.41
0.48
0.54
0.58
0.61
0.63
0.64
0.65
0.65
0.65
0.65
0.14
0.24
0.32
0.38
0.43
0.46
0.48
0.50
0.51
0.51
0.51
0.51
0.11
0.19
0.25
0.30
0.34
0.36
0.38
0.39
0.40
0.40
0.41
0.09
0.15
0.20
0.24
0.26
0.28
0.30
0.31
0.32
0.32
0.07
0.12
0.16
0.19
0.21
0.22
0.24
0.24
0.25
0.05
0.09
0.12
0.15
0.16
0.18
0.19
0.19
0 RIR
1 RIR
2 RIR
3 RIR
4 RIR
5 RIR
6 RIR
7 RIR
8 RIR
9 RIR
10 RIR
11 RIR
12 RIR
1.00
1.69
2.23
2.63
2.92
3.12
3.26
3.35
3.40
3.43
3.43
3.41
3.39
3.35
3.31
3.26
3.22
3.16
3.11
3.06
0.76
1.32
1.75
2.06
2.29
2.45
2.56
2.63
2.68
2.70
2.70
2.69
2.67
2.64
2.61
2.58
2.54
2.50
2.46
2.42
0.59
1.04
1.37
1.62
1.80
1.92
2.01
2.07
2.11
2.12
2.13
2.12
2.11
2.09
2.06
2.03
2.01
1.98
1.95
1.91
0.46
0.81
1.07
1.27
1.41
1.51
1.58
1.63
1.66
1.67
1.68
1.67
1.66
1.65
1.63
1.61
1.59
1.56
1.54
1.51
0.36
0.64
0.84
1.00
1.11
1.19
1.25
1.28
1.31
1.32
1.32
1.32
1.31
1.30
1.29
1.27
1.25
1.24
1.22
1.20
0.28
0.50
0.66
0.78
0.87
0.94
0.98
1.01
1.03
1.04
1.04
1.04
1.04
1.03
1.02
1.00
0.99
0.98
0.96
0.95
0.22
0.39
0.52
0.62
0.69
0.74
0.77
0.80
0.81
0.82
0.82
0.82
0.82
0.81
0.80
0.79
0.78
0.77
0.76
0.75
0.18
0.31
0.41
0.48
0.54
0.58
0.61
0.63
0.64
0.65
0.65
0.65
0.65
0.64
0.64
0.63
0.62
0.61
0.60
0.60
0.14
0.24
0.32
0.38
0.43
0.46
0.48
0.50
0.51
0.51
0.51
0.51
0.51
0.51
0.50
0.50
0.49
0.49
0.48
0.47
0.11
0.19
0.25
0.30
0.34
0.36
0.38
0.39
0.40
0.40
0.41
0.41
0.40
0.40
0.40
0.39
0.39
0.38
0.38
0.37
0.09
0.15
0.20
0.24
0.26
0.28
0.30
0.31
0.32
0.32
0.32
0.32
0.32
0.32
0.32
0.31
0.31
0.31
0.30
0.30
0.07
0.12
0.16
0.19
0.21
0.22
0.24
0.24
0.25
0.25
0.25
0.25
0.25
0.25
0.25
0.25
0.24
0.24
0.24
0.24
0.05
0.09
0.12
0.15
0.16
0.18
0.19
0.19
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.19
0.19
0.19
0.19
Exer�on / Reps in Reserve (RIR)
# Reps
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Exer�on / Reps in Reserve (RIR)
# Reps
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Table 4.32. Relative PXL estimated using Load-Exertion table. Please note that there seems to be an
area with the highest rPXL (red), which indicated the highest stimuli for hypertrophy (given XL model).
Keep in mind that this is Small World model
Exer�on / Reps in Reserve (RIR)
% 1RM
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
0 RIR
1 RIR
2 RIR
3 RIR
4 RIR
5 RIR
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
0 RIR
1 RIR
2 RIR
3 RIR
4 RIR
5 RIR
6 RIR
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
6 RIR
1
2
3
4
5
6
7
8
9
10
11
12
13
14
7 RIR
1
2
3
4
5
6
7
8
9
10
11
12
13
Exer�on / Reps in Reserve (RIR)
8 RIR
9 RIR
10 RIR
11 RIR
12 RIR
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
1
2
3
4
5
6
7
8
7 RIR
8 RIR
9 RIR
10 RIR
11 RIR
12 RIR
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
50%
71%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
50%
49%
70%
68%
67%
65%
64%
63%
61%
60%
59%
58%
57%
56%
55%
54%
53%
52%
51%
50%
49%
48%
% 1RM
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
73%
71%
70%
68%
67%
65%
64%
63%
61%
60%
0 RIR
1 RIR
2 RIR
3 RIR
4 RIR
5 RIR
6 RIR
7 RIR
8 RIR
9 RIR
10 RIR
11 RIR
12 RIR
1.00
0.85
0.74
0.66
0.58
0.52
0.47
0.42
0.38
0.34
0.31
0.28
0.26
0.24
0.22
0.20
0.19
0.18
0.16
0.15
0.76
0.66
0.58
0.52
0.46
0.41
0.37
0.33
0.30
0.27
0.25
0.22
0.21
0.19
0.17
0.16
0.15
0.14
0.13
0.59
0.52
0.46
0.40
0.36
0.32
0.29
0.26
0.23
0.21
0.19
0.18
0.16
0.15
0.14
0.13
0.12
0.11
0.46
0.41
0.36
0.32
0.28
0.25
0.23
0.20
0.18
0.17
0.15
0.14
0.13
0.12
0.11
0.10
0.09
0.36
0.32
0.28
0.25
0.22
0.20
0.18
0.16
0.15
0.13
0.12
0.11
0.10
0.09
0.09
0.08
0.28
0.25
0.22
0.20
0.17
0.16
0.14
0.13
0.11
0.10
0.09
0.09
0.08
0.07
0.07
0.22
0.20
0.17
0.15
0.14
0.12
0.11
0.10
0.09
0.08
0.07
0.07
0.06
0.06
0.18
0.15
0.14
0.12
0.11
0.10
0.09
0.08
0.07
0.06
0.06
0.05
0.05
0.14
0.12
0.11
0.10
0.09
0.08
0.07
0.06
0.06
0.05
0.05
0.04
0.11
0.10
0.08
0.08
0.07
0.06
0.05
0.05
0.04
0.04
0.04
0.09
0.08
0.07
0.06
0.05
0.05
0.04
0.04
0.04
0.03
0.07
0.06
0.05
0.05
0.04
0.04
0.03
0.03
0.03
0.05
0.05
0.04
0.04
0.03
0.03
0.03
0.02
0 RIR
1 RIR
2 RIR
3 RIR
4 RIR
5 RIR
6 RIR
7 RIR
8 RIR
9 RIR
10 RIR
11 RIR
12 RIR
1.00
0.85
0.74
0.66
0.58
0.52
0.47
0.42
0.38
0.34
0.31
0.28
0.26
0.24
0.22
0.20
0.19
0.18
0.16
0.15
0.76
0.66
0.58
0.52
0.46
0.41
0.37
0.33
0.30
0.27
0.25
0.22
0.21
0.19
0.17
0.16
0.15
0.14
0.13
0.12
0.59
0.52
0.46
0.40
0.36
0.32
0.29
0.26
0.23
0.21
0.19
0.18
0.16
0.15
0.14
0.13
0.12
0.11
0.10
0.10
0.46
0.41
0.36
0.32
0.28
0.25
0.23
0.20
0.18
0.17
0.15
0.14
0.13
0.12
0.11
0.10
0.09
0.09
0.08
0.08
0.36
0.32
0.28
0.25
0.22
0.20
0.18
0.16
0.15
0.13
0.12
0.11
0.10
0.09
0.09
0.08
0.07
0.07
0.06
0.06
0.28
0.25
0.22
0.20
0.17
0.16
0.14
0.13
0.11
0.10
0.09
0.09
0.08
0.07
0.07
0.06
0.06
0.05
0.05
0.05
0.22
0.20
0.17
0.15
0.14
0.12
0.11
0.10
0.09
0.08
0.07
0.07
0.06
0.06
0.05
0.05
0.05
0.04
0.04
0.04
0.18
0.15
0.14
0.12
0.11
0.10
0.09
0.08
0.07
0.06
0.06
0.05
0.05
0.05
0.04
0.04
0.04
0.03
0.03
0.03
0.14
0.12
0.11
0.10
0.09
0.08
0.07
0.06
0.06
0.05
0.05
0.04
0.04
0.04
0.03
0.03
0.03
0.03
0.03
0.02
0.11
0.10
0.08
0.08
0.07
0.06
0.05
0.05
0.04
0.04
0.04
0.03
0.03
0.03
0.03
0.02
0.02
0.02
0.02
0.02
0.09
0.08
0.07
0.06
0.05
0.05
0.04
0.04
0.04
0.03
0.03
0.03
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.01
0.07
0.06
0.05
0.05
0.04
0.04
0.03
0.03
0.03
0.03
0.02
0.02
0.02
0.02
0.02
0.02
0.01
0.01
0.01
0.01
0.05
0.05
0.04
0.04
0.03
0.03
0.03
0.02
0.02
0.02
0.02
0.02
0.02
0.01
0.01
0.01
0.01
0.01
0.01
0.01
Exer�on / Reps in Reserve (RIR)
# Reps
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Exer�on / Reps in Reserve (RIR)
# Reps
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Table 4.33. Relative CXL estimated using Load-Exertion table. Please note that there seems to be
an area with the highest rCXL (red), which indicated the highest stimuli for strength (given XL model).
Keep in mind that this is Small World model
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MLADEN JOVANOVIĆ
Table 4.33. Relative CXL estimated using Load-Exertion table. Please note that
there seems to be an area with the highest rCXL (red), which indicated the highest
stimuli for strength (given XL model). Keep in mind that this is Small World model
Ballistic Movements
As mentioned at the beginning of this chapter, prescription for ballistic movements
is a bit tricky (or trickier compared to grinding movements). Ballistic movements are
tricky to define as well - they usually have a flight phase, where the implement or the
body travels through the space (e.g., vertical jump, bench throw, broad jump). But it is
not that easy - if you take a look at classification on the Figure 3.4, ballistic movements
also consist of Olympic lifting and “fast grinding”, neither of which has “open” end
point, where the implement “flies off”34. These two categories have defined stopping
points. Could it be that definition of ballistic movement is similar to the definition of
pornography: “I can’t define pornography, but I know it when I see it.” To me, ballistic
either has a flight phase (object or the body), or it is done with the explosive effort. For
example, sub maximal squat jumps have flight phase, but are not done with maximal
explosive effort, while explosive squats have explosive effort, but no flight phase.
Olympic lifting can be considered explosive since there is explosive effort, but
there is also a small “flight” of the barbell, before one catches it at a specific point and
rhythm. Compared to, say, squat jumps, in Olympic lifting (i.e., snatch, clean) sub-max
weights are also caught with the same rhythm and at the same height. Otherwise, one
would accelerate the bar so high, that the technique would be modified, and one might
end up performing ‘muscle’ variants of the snatch and clean. For this reason, I think
Load-Velocity profiling of the Olympic lifting is bullshit. If the barbell reaches same
point and path with the same movement rhythm, that means that the velocity needs to
be quite similar across loads.
With the fast grinding movements, there will be some “breaking phase”. This
is needed to actually prevent the implement or the body becoming ballistic. This
method, termed “dynamic effort method” or (DE), is a staple in Westside Barbell
programs (Simmons, 2007) and involves lifting 50-60% of 1RM for few reps (2-3) as
fast as possible35. Shorter break, and repeated for around 10 sets. This is sometimes
accompanied with the use of accommodating resistance, such as bands or chains, which
34 Some Olympic lifting derivatives, like Snatch High Pull doesn’t have fixed end point
35 This can mean multiple things: (1) concentric portion of the lift is as fast as possible, (2) both eccentric
and concentric are as fast as possible, followed by a pause, and (3) all reps are done as fast as possible.
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STRENGTH TRAINING MANUAL Volume One
increase the weight at the top (hence reduce this “breaking phase”). Some coaches, like
Mike Tuchscherer (Tuchscherer, 2013a,b)36 are critics of this method. But usually these
type of disagreement happened due “Small World” models using a single metric that is
defined as a construct that causes adaptation and improvement. For example, the idea
behind DE is that compensatory acceleration during concentric range produce high
forces, and those high forces are what drives adaptation. Well, according to research,
Mike, and some of my own observations, forces (peak forces) with submaximal fast
grinding movements are not that high37. But then, are the peak forces the only thing
that causes adaptation? What about second-order effect of such a workout within
bigger picture? These are all things that need to be considered when discussing cause
and effects. For this reason, I am neither for nor against “fast grinding” - I am enlisting
them and discussing them in this manual for the sake of completeness - it is up to you
if you want to use them.
When it comes to ‘true’ ballistic movements (i.e., not Olympic lifting nor fast
grinding), we have two issues to solve: (1) what is 1RM in the ballistic movement, and
(2) what is failure in the ballistic movement. I will discuss these two separately, but
will also include their application to Olympic and fast grinding movements (and other
applications).
What is 1RM with ballistic movements
Figuring out 1RM with Olympic lifting is relatively easy - it is the maximal weight
that you can clean, jerk or snatch. Fast grinding, usually uses 50-60% of the grinding
1RM (e.g., if your squat 1RM is 200kg, for dynamic effort you should use around 100120kg). But what about say, jump squats, or bench press throw?38 What would be the
highest load (1RM) that can be used in training with ballistic movements?
One simple rule of thumb (i.e., heuristic) that can be used, is that implement
(i.e., barbell) or body needs to travel at least 10-15cm. This means that if you increase
load in the movement, eventually you will not be able to jump or throw over 10-15cm.
Since this is the load after which the movement pretty much looks like crap, it can be
considered 1RM for the movement. Using the ballistic equation:
36 I wrote response to Mike Tuchscherer’s opinion (Jovanovic, 2013b,c)
37 According to my bench press data (N=1), to reach over 90% of Peak Force output one needs to use loads
over 82% 1RM. To reach over 80% of Peak Force output one need to use more than 68% 1RM. Both above
recommended 50-60% 1RM for Dynamic Effort method (“fast grinding”) (Jovanovic, 2013b,c)
38 I will exclude other type of jumps and throws here, and focus mainly to ‘barbell’ ballistic movements,
such as hex bar jump, squat jump, bench throw.
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MLADEN JOVANOVIĆ
or
10cm is equal to 1.4 m/s. This refers to take-off-velocity (TOV) of the barbell (in
say bench throw) or center-of-mass (COM) of the barbell-body system (as in squat
jump). Thus, it is tricky to use this threshold in Load-Velocity profiling, particularly
with squat jump. Also, note that TOV is quite similar to peak-velocity (PV), but not the
same, since there will be some deceleration involved just before take off. But again,
other quality thresholds can be used if you have specialized equipment to use. In the
ideal world, one can use force plate, contact mat or LPT (linear position transducer)
to estimate this from 3 to 4 load increments. The easiest would be to use contact mat
and measure jump height across loads, and figure out load for 10cm jump height using
linear or polynomial regression (which means that when performing load profiling,
one doesn’t need to go to 1RM, particularly with ballistic movements).
But in the real world, most don’t have access to this equipment, so we need to use
simple to remember heuristics. The question is, how is ballistic 1RM related to grinding
1RM (e.g., bench throw to bench press, squat jump to back squat)? Of course, this will
differ depending on whether there is a concentric only or countermovement action,
experience of the lifter, type of movement and so forth. But what would be simple,
conservative and easy to remember rule of thumb that could be used as a prior when
figuring out the highest load for ballistic movement, and something we can use to
prescribe? The simple solution would be half or 50%. For example, if your squat 1RM is
180kg, squat jump 1RM is 90kg. Perfect? Oh hell no! Useful? Probably good conservative
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STRENGTH TRAINING MANUAL Volume One
estimate you can use. Will you use this load? Hell no - we will use this as 1RM to prescribe
off, same as we did with the grinding movements. Thus, one will jump with much smaller
weight. In either way, I suggest using some type of measurement - it can also be your
eyes. If it looks like shit, smells like shit, taste like shit, it probably is shit. With ballistic
movements, it is always useful to start light, and progress from there. No amount of
profiling can beat this common sense.
Total System Load
Mike Boyle (Boyle, Verstegen & Cosgrove, 2010) suggested using 40% of the
total system load (e.g. bodyweight + barbell load in the squat) for squat jump load
when training (see Table 4.34). Please note that this is not squat jump 1RM, but rather
suggested load for training.
Athlete A
Athlete B
Athlete C
Athlete D
Bodyweight
75
100
80
80
1RM
150
150
150
200
Total
225
250
230
280
40%
90
100
92
112
SJ with
15
0
12
32
Table 4.34. Mike Boyle recommendation for suggesting squat jump load
(Boyle, Verstegen & Cosgrove, 2010)
I believe that this "Mike Boyle rule" is too conservative, but it could be applied
when working with complete noobs, particularly with the squat jump. It is better to
be safe than sorry. What is interesting, is that Mike pinpoints the issues of not taking
bodyweight into account. As already explained in this chapter, there is no a single,
objective approach, but rather pluralistic approaches, particularly when external versus
total system are considered. If one plans performing load profiling, then exact external
load can be estimated (1RM), and if one doesn’t plan changing bodyweight much (e.g.
over 10%) over the next few weeks, then total system load approach is not needed.
Similarly to what is being discussed before, total system load makes complete sense,
but it makes things more complex and assumes everything else is correct. Adding more
complexity to uncertain estimates to begin with, doesn’t make things more precise - it
makes it look more ‘scientific’ and probably less useful. Hence I opt for the less precise,
but simpler approaches in this manual, by using them as priors and using your common
sense to adjust on the go and across training sprints and phases.
Peak Power Bullshit, or Peak Bullshit
Some Intellectuals Yet Idiots (IYIs) believe that there is a magic load that produces
peak power at which individuals should train. This is utter bullshit. First, the calculus
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MLADEN JOVANOVIĆ
of this Peak Power (PP) Load depends on the metric used (e.g., mean velocity, peak
velocity, take-off velocity), whether this velocity is related to barbell only, or COM,
whether the load is only external or total system load. All of these will give different
locations of PP (Jovanovic, 2013a). Second, the jump over Is/Ought gap is believing that
lifting load associated with PP will somehow magically improve the Power construct.
If you remember from Chapter 2, this is reflective vs. formative model (Figure 2.19).
In this regard, I am taking constructivist stance and believe that this represents
formative model - or just a numerical representation and simplification. In addition, I
particularly don’t believe one should train solely at this optimal load that produces PP,
but rather across different loads (Jovanovic, 2013a). It is formative Small World model,
and IYIs would argue and publish useless scientific papers (you must admit that “The
optimal load to train peak power” sounds scientific, but if you scratch the surface, it is
bullshit) until the cows come home. I just don’t buy that crap, nor should you. All the
“optimization” models are based on a single or few parameters of the Small World that
needs to be optimized so the target variable maximizes or minimizes.
To conclude, the highest load that can be used in ballistic movement (i.e., not
the Olympic lifting or fast grinding) is around 50% of related grinding exercise 1RM
(this heuristic will be applied to small number of exercises: squat jump, bench throw,
hex bar jump). This has NOTHING to do with Peak Power bullshit propaganda, but it is
rather a simple rule of thumb to base off your loads using special variation of the LoadExertion table. It bears repeating that doesn’t mean you should train at this load - they
represent maximal loads, and you can always (and probably should) start lower.
What is failure with ballistic movements
(and how many reps to do)
So now we have 1RM of the ballistic exercise. How many max reps can (or should)
be performed at say, 90% or 80% 1RM? Here we need to differentiate between quality
reps which are done with the aim of improving explosiveness as a quality, and fatigue
reps which are done to improve some type of explosive endurance39 . Quality reps hence
have some type of the quality threshold over which one doesn’t go. This could usually
mean 10-20% drop in height, power, velocity or what have you. With fatigue reps, the
performance might drop much further, and might approach a failure point. In this
39 As a keen reader, you have probably noticed that I have performed a jump over Is/Ought gap here. I
have assumed that quality reps improve “explosiveness”, while fatigue reps improve “ability to maintain
explosiveness” (explosive endurance). It is thus better to classify based on the action performed, rather
than potential outcome.
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STRENGTH TRAINING MANUAL Volume One
case, failure point is defined similarly as ballistic 1RM - a point where height of the
implement or the body doesn’t reach 10cm.
When it comes to Olympic lifting, this quality threshold is tricky to measure, and
might indicate change in technique, rhythm, depth of the catch and so forth. Prilepin
table (Table 4.35) has traditionally been applied as heuristic to suggest number of reps
per set, as well as number of lifts.
Prilepin's Chart
% 1RM
90% +
80-90%
70-80%
55-65%
Reps per set
Total Reps
Op�mal
Total Reps
Range
1 to 2
2 to 4
3 to 6
3 to 6
7
15
18
24
4 to 10
10 to 20
12 to 24
18 to 30
Volume Guidelines
HIGH
MEDIUM
LOW
Total Reps
Total Reps
Total Reps
10
7
4
20
15
10
24
18
12
30
24
18
Table 4.35. Prilepin Table
Fast grinding movements have been already discussed, and they involve sets
of 2-3 reps at around 50% of 1RM. For other bodyweight movements (i.e., jumps and
throws), when done intensively (with the maximal intent), the highest number of reps
should be around 5 to 6, after which the quality drops. If these are done extensively
(sub-maximal intent), for example rhythmical jumps, then this number can go higher.
In any case, it is up to you to decide what are you trying to do and what to achieve.
One thing that I’ve noticed analyzing some of my data as well as other studies,
is that during the grinding movements, if we use velocity loss40 of 10-20% (i.e., quality
threshold) then the number of quality reps are halved compared to the maximal
number of reps that are potentially possible. For example, if one uses 10RM, which is
approximately around 75% 1RM (given Epley’s formula) maximal number of reps is 10.
The 10-20% threshold will happen at around half that number, or 5 in this case41. It has
been shown that minimizing and controlling for this velocity (or quality) drop with the
grinding movements, using LPTs or other velocity measurement tools, one minimizes
fatigue between sessions and negative effects of lifting to maximal training adaptations
(Sánchez-Medina & González-Badillo, 2011; González Badillo, 2017; Pareja-Blanco et
al., 2017b,a; Jovanovic, 2017c).This simple heuristic can be very useful for athletes who
are in-season, who are just starting to lift (to minimize the soreness as well), or for
those who have a lot of other training sessions. Therefore, this one-half heuristic can be
applied to Load-Exertion table to indicate threshold for quality reps. Converting this to
40 Velocity is calculated using fastest rep, usually the first rep. For example, if velocity loss 10% is used,
one performs repetitions in a set until velocity doesn’t drop more than 10%.
41 This represents rough rule of thumb from my re-analysis of some published papers and my own data
(Jovanovic, 2017c). This heuristic will be covered in the PhD papers I am writing.
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MLADEN JOVANOVIĆ
equation, this means that %1RM associated with a particular number of reps is the one
associated with double reps:
%1RM = 1 / (0.0333 x Reps x 2 + 1)
%1RM = 1 / (0.0666 x Reps + 1)
or
Reps = (15.015 / %1RM) - 15.015
Table 4.36 might convey this one-half heuristic a bit better.
Max Reps
Reps
%1RM
1
100%
2
94%
3
91%
4
88%
5
86%
6
83%
7
81%
8
79%
9
77%
10
75%
11
73%
12
71%
Quality Reps
Reps
%1RM
1
94%
2
88%
3
83%
4
79%
5
75%
6
71%
7
68%
8
65%
9
63%
10
60%
11
58%
12
56%
Table 4.36. Quality reps (i.e. reps done over quality threshold, usually 10-20% velocity drop
The question that remains unanswered is whether this can be applied to ballistic
lifts (e.g. squat jump, hex bar jump, bench throw). This is questionable, since I am not
sure if Epley’s formula can be applied to them as well (how many reps over 10cm height
one can do at given %1RM). But assuming it can be applied, using 0.0666 instead of
0.0333 in Load-Exertion table, one can get a special version of this table that I termed
Ballistic Load-Exertion Table. Please note that this is still quite speculative (particularly
its application to ballistic lifts). Table 4.37 contains Ballistic Load-Exertion Table
together with Prilepin Table for the sake of comparison.
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STRENGTH TRAINING MANUAL Volume One
Exer�on / Reps in Reserve (RIR)
% 1RM
94%
88%
83%
79%
75%
71%
68%
65%
63%
60%
Max reps
1 rep short
2 reps short
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
Max reps
1 rep short
2 reps short
94%
88%
83%
79%
75%
71%
68%
65%
63%
60%
88%
83%
79%
75%
71%
68%
65%
63%
60%
58%
83%
79%
75%
71%
68%
65%
63%
60%
58%
56%
1
2
3
4
5
6
7
8
Prilepin's Chart
5 reps short
Reps per set
Total Reps
Op�mal
1
2
3
4
5
6
1
2
3
4
5
1 to 2
2 to 4
2 to 4
3 to 6
3 to 6
3 to 6
3 to 6
3 to 6
3 to 6
3 to 6
7
15
15
18
18
18
24
24
24
24
3 reps short
4 reps short
5 reps short
79%
75%
71%
68%
65%
63%
60%
58%
56%
54%
75%
71%
68%
65%
63%
60%
58%
56%
54%
52%
71%
68%
65%
63%
60%
58%
56%
54%
52%
50%
3 reps short
1
2
3
4
5
6
7
4 reps short
Volume Guidelines
Total Reps
Range
4 to 10
10 to 20
10 to 20
12 to 24
12 to 24
12 to 24
18 to 30
18 to 30
18 to 30
18 to 30
HIGH
MEDIUM
LOW
Total Reps
10
20
20
24
24
24
30
30
30
30
Total Reps
7
15
15
18
18
18
24
24
24
24
Total Reps
4
10
10
12
12
12
18
18
18
18
Exer�on / Reps in Reserve (RIR)
# Reps
1
2
3
4
5
6
7
8
9
10
Table 4.37. Ballistic Load-Exertion Table
The Ballistic Load-Exertion table can be used for planning grinding movements42,
Olympic lifts, and potentially to ballistic lifts such as hex bar jump, bench throw and
squat jump. The max 6 reps heuristic can be applied here as well. Table 4.38 contains
example of using known hex bar deadlift (grinding movement) to estimate load for hex
bar jump (ballistic) using half-load and half-reps heuristics.
Load ratio column from Table 4.38 indicates simpler heuristic suggested by Dan
Baker43 when prescribing load for jump squats and bench throws using current cycle
squat and bench press reps and loads (for example, if one uses 3x5 with 110kg bench
press, then bench throw is 40% of that or 3x5 with 45kg).
It is important to remember that prescription for ballistic movements is tricky
(particularly if one wants a specific number of reps and load) and that the presented
heuristics for planning ballistic movements should be taken with a grain of salt.
Ballistic Load-Exertion table can be useful for prescribing Olympic lifting and for
estimating maximal load for ballistic movements. With Olympic lifting, I personally
prefer looser prescription (either using rep or intensity zones) and go by feel, as well as
using progressive warm-up sets. When it comes to ballistic movements, such as bench
throws and hex bar jumps, load can really vary, and in this particular situation, Ballistic
Load-Exertion table can be used just to make sure not to overdo it (ideally, you want
to use some type of live feedback and velocity monitoring). For other types of ballistic
movements (e.g. bodyweight jumps, and throws) the above recommendations, besides
42 With the aim of minimizing fatigue and soreness (although the total number of reps will be more
important) with in-season athletes, athletes just starting up (who are learning techniques), or those who
are training with very high frequency (although some go even lower with %ages)
43 Dan Baker actually suggest using 40-60% (Joyce, 2014)
164
MLADEN JOVANOVIĆ
limiting number of reps to 5-6, is pretty much useless.
The next chapter will discuss planning the training phase using Load-Exertion
and Ballistic Load-Exertion tables to create two methods of progression. As always, it is
important to remember that these are all “Small World” models. We need to keep that
in mind.
# Reps
1
2
3
4
5
6
7
8
9
10
Grinding
1RM
%1RM
100%
94%
91%
88%
86%
83%
81%
79%
77%
75%
150
Load
150
141
136
132
129
125
122
118
115
113
Ballis�c
1RM
%1RM
94%
88%
83%
79%
75%
71%
50%
75
Load
70
66
63
59
56
54
Load Ra�o
47%
47%
46%
45%
44%
43%
Figure 4.38. Example load calculus for hex bar jumps using known hex bar deadlift 1RM.
165
STRENGTH TRAINING MANUAL Volume One
Appendix: Exercise List
166
MLADEN JOVANOVIĆ
Name
Clean (Blocks)
Clean High Pull (Blocks)
Clean Pull (Blocks)
Snatch (Blocks)
Snatch High Pull (Blocks)
Snatch Pull (Blocks)
Clean
Clean High Pull
Clean Pull
Power Clean
Split Clean
Clean & Jerk
Power Snatch
Snatch
Snatch Balance
Snatch High Pull
Snatch Pull
Split Snatch
Clean (Hang)
Clean (Muscle)
Clean High Pull (Hang)
Clean Pull (Hang)
Power Clean (Hang)
Power Snatch (Hang)
Snatch (Hang)
Snatch (Muscle)
Snatch High Pull (Hang)
Snatch Pull (Hang)
Rack Pull
Deadli�
Snatch Grip Deadli�
Sumo Deadli�
Bridge (Straight Leg Ball)
Bridge (Straight Leg)
Bridge Drop Downs (Ball)
Bridge Li� and Curl (Ball)
Bridge Li� and Curl (Slide Board)
Glute Bridge (Ball)
Glute Bridge (Elevated Feet)
Glute Ham Raise (GHR)
Hip Thrust (Ball)
Hyper 45 degree
Hyper 90 degree
Nordic Curl
Pull Through
Reverse Hyper
Sumo Pull Through
DB Romanian Deadli�
Glute Bridge (Floor)
Good Morning
Hip Thrust (Bench)
Romanian Deadli�
Sumo Good Morning
Sumo Romanian Deadli�
Trap Bar Romania Deadli�
Zercher Romanian Deadli�
Bridge 1-Leg (Straight Leg Ball)
Bridge 1-Leg (Straight Leg)
Bridge Drop Downs (Slide Board)
Bridge Drop Downs 1-Leg (Ball)
Bridge Drop Downs 1-Leg (Slide Board)
Bridge Li� and Curl 1-Leg (Ball)
Bridge Li� and Curl 1-Leg (Slide Board)
Glute Bridge 1-Leg (Ball)
Glute Bridge 1-Leg (Elevated Feet)
Glute Bridge 1-Leg (Floor)
Glute Bridge 1-Leg Alterna�ng (Floor)
Hip Thrust 1-Leg (Ball)
Hip Thrust 1-Leg (Bench)
Hyper 45 degree 1-Leg
Hyper 90 degree 1-Leg
Lateral Bridge 1-Leg (Straight Leg Ball)
Lateral Bridge 1-Leg (Straight Leg)
Reverse Hyper 1-Leg
DB Romanian Deadli� 1-Arm/1-Leg (Contralateral)
DB Romanian Deadli� 1-Arm/1-Leg (Ipsilateral)
DB Romanian Deadli� 2-Arm/1-Leg
Good Morning 1-Leg
Plate Good Morning 1-Leg (Overhead)
Romanian Deadli� 1-Leg
Barbell Curls
DB Curls
Rings Inverted Row 1-Arm
1-Arm/1-Leg Row (Contralateral)
1-Arm/1-Leg Row (Ipsilateral)
Bench Pull
Bent Over Row
Cable Row (Neutral)
Cable Row (Pronated)
Cable Row (Rope)
Cable Row (Supinated)
Chest Supported Row
DB Bench Row 1-Arm
DB Bench Row 2-Arm
DB Bent Over Row 1-Arm (Neutral)
DB Bent Over Row 1-Arm (Wide)
Category
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Ballis�c
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Pa�ern
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Olympic
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Hinge
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Variant
Blocks
Blocks
Blocks
Blocks
Blocks
Blocks
Ground
Ground
Ground
Ground
Ground
Ground
Ground
Ground
Ground
Ground
Ground
Ground
Hang
Hang
Hang
Hang
Hang
Hang
Hang
Hang
Hang
Hang
Blocks
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Accessory
Accessory
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
%
95%
75%
105%
95%
75%
105%
100%
80%
110%
85%
90%
100%
85%
100%
80%
80%
110%
90%
95%
60%
75%
105%
80%
80%
95%
60%
75%
105%
110%
100%
75%
100%
Related to
Clean
Clean
Clean
Snatch
Snatch
Snatch
Clean
Clean
Clean
Clean
Clean
Clean and Jerk
Snatch
Snatch
Snatch
Snatch
Snatch
Snatch
Clean
Clean
Clean
Clean
Clean
Snatch
Snatch
Snatch
Snatch
Snatch
Deadli�
Deadli�
Deadli�
Deadli�
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
35% Squat
105% Squat
50% Squat
100% Squat
75% Squat
40% Squat
65% Squat
75% Squat
70% Squat
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
30% Squat
25% Squat
20% Squat
30% Squat
10% Squat
45% Squat
35% Pull-up
20% Pull-up
None
25% Pull-Up
25% Pull-Up
70% Pull-Up
65% Pull-Up
60% Pull-Up
60% Pull-Up
60% Pull-Up
60% Pull-Up
70% Pull-Up
35% Pull-Up
30% Pull-Up
35% Pull-Up
30% Pull-Up
%BW Used
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Equipment Used
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Fitness Ball
Bodyweight
Fitness Ball
Fitness Ball
Slideboard
Fitness Ball
Bodyweight
Machine
Fitness Ball
Machine
Machine
Bodyweight
Machine
Machine
Machine
Dumbells
Barbell
Barbell
Bodyweight
Barbell
Barbell
Barbell
Trap Bar
Barbell
Fitness Ball
Bodyweight
Slideboard
Fitness Ball
Slideboard
Fitness Ball
Slideboard
Fitness Ball
Bodyweight
Bodyweight
Bodyweight
Fitness Ball
Bodyweight
Machine
Machine
Fitness Ball
Bodyweight
Machine
Dumbells
Dumbells
Dumbells
Barbell
Plates
Barbell
Barbell
Dumbells
Gymnas�c rings
Dumbells
Dumbells
Barbell
Barbell
Machine
Machine
Machine
Machine
Machine
Dumbells
Dumbells
Dumbells
Dumbells
Note
From 95-105%
* Each dumbell
>105%
* Each dumbell
* Each dumbell
167
* Each dumbell
* Each dumbell
* Each dumbell
* Each dumbell
Good Morning 1-Leg
Plate Good Morning 1-Leg (Overhead)
Romanian Deadli� 1-Leg
Barbell Curls
DB Curls
Rings Inverted Row 1-Arm
1-Arm/1-Leg Row (Contralateral)
1-Arm/1-Leg Row (Ipsilateral)
Bench Pull
Bent Over Row
Name
Cable (Blocks)
Row (Neutral)
Clean
Cable High
Row (Pronated)
Clean
Pull (Blocks)
Cable Pull
Row(Blocks)
(Rope)
Clean
Cable Row
(Supinated)
Snatch
(Blocks)
Chest Supported
Row
Snatch
High Pull (Blocks)
DB Bench
1-Arm
Snatch
PullRow
(Blocks)
DB Bench Row 2-Arm
Clean
DB Bent
Over
Clean
High
PullRow 1-Arm (Neutral)
DB
Bent
Clean
PullOver Row 1-Arm (Wide)
DB BentClean
Over Row 2-Arm (Alterna�ng)
Power
DB
Over Row 2-Arm (Neutral)
SplitBent
Clean
DB
Bent
Over Row 2-Arm (Wide)
Clean
& Jerk
Rings
PowerInverted
Snatch Row (Neutral)
Rings
SnatchInverted Row (Rota�on)
Rings
SnatchInverted
BalanceRow (Wide)
Bar
PullHigh
Ups Pull
(Neutral)
Snatch
Bar
Pull
Ups (Pronated)
Snatch Pull
Bar
Ups (Supinated)
SplitPull
Snatch
Pull Down
(Neutral)
Clean
(Hang)
Pull Down
(Pronated)
Clean
(Muscle)
Pull Down
Clean
High(Supinated)
Pull (Hang)
Pull Down
(Wide)
Clean
Pull (Hang)
Rings Pull
Ups(Hang)
(Neutral)
Power
Clean
Rings Pull
Ups (Hang)
(Pronated)
Power
Snatch
Rings
Ups (Supinated)
SnatchPull
(Hang)
Rings
Ups (Wide)
SnatchPull
(Muscle)
Rope
SnatchClimbs
High Pull (Hang)
Towel Pull-ups
Snatch
Pull (Hang)
BenchPull
Press
Rack
DB Bench Press 1-Arm
Deadli�
DB Bench
Press
2-Arm
Snatch
Grip
Deadli�
DB Bench
Press 2-Arm (Alterna�ng)
Sumo
Deadli�
DB Floor
Press Leg Ball)
Bridge
(Straight
DB Incline
BenchLeg)
Press 1-Arm
Bridge
(Straight
DB Incline
Bench
Press
2-Arm
Bridge
Drop
Downs
(Ball)
DB Incline
Press
2-Arm (Alterna�ng)
Bridge
Li� Bench
and Curl
(Ball)
DeclineLi�
Bench
Bridge
and Press
Curl (Slide Board)
Floor Press
Glute
Bridge (Ball)
InclineBridge
Bench(Elevated
Press
Glute
Feet)
Push Ups
Glute
Ham(Narrow)
Raise (GHR)
PushThrust
Ups (Normal)
Hip
(Ball)
Push Ups
(Wide)
Hyper
45 degree
Ring PushUps
(Normal)
Hyper
90 degree
Ring PushUps
Nordic
Curl (Wide)
DipsThrough
Pull
Ring DipsHyper
Reverse
1/2 Kneeling
KB Press
Sumo
Pull Through
1/2Romanian
Kneeling Land
Mine Press
DB
Deadli�
DB Press
1-Arm
Glute
Bridge
(Floor)
DB Press
2-Arm
Good
Morning
DB Press
(Alterna�ng)
Hip
Thrust2-Arm
(Bench)
DB Push Press
1-Arm
Romanian
Deadli�
DB Push
Press
2-Arm
Sumo
Good
Morning
KB Press
1-Arm Deadli�
Sumo
Romanian
KB Press
2-Arm Deadli�
Trap
Bar Romania
KB PressRomanian
2-Arm (Alterna�ng)
Zercher
Deadli�
KB Push1-Leg
Press(Straight
1-Arm Leg Ball)
Bridge
KB Push1-Leg
Press(Straight
2-Arm Leg)
Bridge
Log Press
Bridge
Drop Downs (Slide Board)
MilitaryDrop
PressDowns 1-Leg (Ball)
Bridge
Push Press
Bridge
Drop Downs 1-Leg (Slide Board)
Trap Bar
Bridge
Li�Press
and Curl 1-Leg (Ball)
Press Up
Bridge
Li� and Curl 1-Leg (Slide Board)
Yoga Push
Up1-Leg (Ball)
Glute
Bridge
Sled Backward
Pushes
Glute
Bridge 1-Leg
(Elevated Feet)
Sled Marching
Glute
Bridge 1-Leg (Floor)
Sled Walking
Lunges
Glute
Bridge 1-Leg
Alterna�ng (Floor)
Sled
Cross Over
Hip Thrust
1-LegPushes
(Ball)
Sled
Diagonal
Bakcward
Hip Thrust
1-Leg
(Bench)Pushes
Sled
Lateral
Pushes
Hyper
45 degree
1-Leg
Prisoner
Hyper 90Squat
degree 1-Leg
Wall Squat
Lateral
Bridge 1-Leg (Straight Leg Ball)
Back Squat
Lateral
Bridge 1-Leg (Straight Leg)
Barbell Bulgarian
Split Squat
Reverse
Hyper 1-Leg
Barbell
LateralDeadli�
Split Squat
DB
Romanian
1-Arm/1-Leg (Contralateral)
Barbell
Split Squat
DB
Romanian
Deadli� 1-Arm/1-Leg (Ipsilateral)
BeltRomanian
Squat
DB
Deadli� 2-Arm/1-Leg
Box Squat
Good
Morning 1-Leg
Cable
Lateral
Lunges
Plate Good Morning 1-Leg (Overhead)
Cable Lateral
Split Squat
Romanian
Deadli�
1-Leg
DB Bulgarian
Barbell
Curls Split Squat
DB Curls
Lateral Split Squat
DB
Split
Squat Row 1-Arm
Rings
Inverted
DB
Squat
1-Arm/1-Leg
Row (Contralateral)
Front
Squat Row (Ipsilateral)
1-Arm/1-Leg
GobletPull
Bulgarian Split Squat
Bench
Goblet
Lateral
Bent Over
RowSplit Squat
Goblet
Split(Neutral)
Squat
Cable Row
Goblet
Squat
Cable Row
(Pronated)
Ke�lebell
Squat
Cable RowFront
(Rope)
Leg Press
Cable
Row (Supinated)
Overhead
Split Squat
Chest Supported
Row
Overhead
Squat1-Arm
DB Bench Row
Sumo
BackRow
Squat
DB Bench
2-Arm
Trap
Bar Over
SquatRow 1-Arm (Neutral)
DB Bent
Zercher
DB
Bent Squat
Over Row 1-Arm (Wide)
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Category
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Ballis�c
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Hinge
Hinge
Hinge
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pa�ern
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Pull
Olympic
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Push
Hinge
Sled Push
Hinge
Sled Push
Hinge
Sled Push
Hinge
Sled
HingePush
Sled
HingePush
Sled
HingePush
Squat
Hinge
Squat
Hinge
Squat
Hinge
Squat
Hinge
Squat
Hinge
Squat
Hinge
Squat
Hinge
Squat
Hinge
Squat
Hinge
Squat
Hinge
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Squat
Pull
Single Leg
Single Leg
Single Leg
Accessory
Accessory
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Variant
Horizontal
Blocks
Horizontal
Blocks
Horizontal
Blocks
Horizontal
Blocks
Horizontal
Blocks
Horizontal
Blocks
Horizontal
Ground
Horizontal
Ground
Horizontal
Ground
Horizontal
Ground
Horizontal
Ground
Horizontal
Ground
Horizontal
Ground
Horizontal
Ground
Horizontal
Ground
Ver�cal
Ground
Ver�cal
Ground
Ver�cal
Ground
Ver�cal
Hang
Ver�cal
Hang
Ver�cal
Hang
Ver�cal
Hang
Ver�cal
Hang
Ver�cal
Hang
Ver�cal
Hang
Ver�cal
Hang
Ver�cal
Hang
Ver�cal
Hang
Horizontal
Blocks
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Ver�calLeg
Double
Ver�cal Leg
Double
Ver�cal Leg
Double
Ver�cal Leg
Double
Ver�cal Leg
Double
Ver�calLeg
Double
Ver�cal Leg
Double
Ver�cal
Double Leg
Ver�cal Leg
Double
Ver�calLeg
Double
Ver�calLeg
Double
Ver�calLeg
Double
Ver�calLeg
Single
Ver�calLeg
Single
Ver�calLeg
Single
Ver�calLeg
Single
Ver�calLeg
Single
Ver�calLeg
Single
Ver�calLeg
Single
Ver�calLeg
Single
Backward
Single
Leg
Forward
Single
Leg
Forward
Single
Leg
Lateral
Single Leg
Lateral
Single Leg
Lateral
Single Leg
DoubleLeg
Leg
Single
DoubleLeg
Leg
Single
DoubleLeg
Leg
Single
DoubleLeg
Leg
Single
DoubleLeg
Leg
Single
DoubleLeg
Leg
Single
DoubleLeg
Leg
Single
Double
Leg
Single Leg
Double
Leg
Single Leg
DoubleLeg
Leg
Single
Double Leg
Accessory
Double
Leg
Accessory
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double
Leg
Horizontal
Double Leg
Horizontal
STRENGTH TRAINING MANUAL Volume One
168
30%
10%
45%
35%
20%
25%
25%
70%
65%
%
60%
95%
60%
75%
60%
105%
60%
95%
70%
75%
35%
105%
30%
100%
35%
80%
30%
110%
30%
85%
35%
90%
30%
100%
70%
85%
70%
100%
65%
80%
100%
80%
100%
110%
105%
90%
90%
95%
90%
60%
95%
75%
85%
105%
95%
80%
90%
80%
95%
85%
60%
90%
75%
90%
105%
100%
110%
30%
100%
35%
75%
30%
100%
30%
25%
30%
25%
105%
90%
80%
90%
100%
95%
90%
85%
120%
105%
35%
75%
35%
35%
105%
35%
50%
30%
100%
40%
75%
40%
35%
65%
35%
75%
30%
70%
40%
40%
100%
100%
120%
100%
100%
50%
30%
50%
25%
90%
20%
100%
30%
25%
10%
30%
45%
25%
35%
15%
20%
25%
40%
25%
85%
25%
50%
70%
40%
65%
30%
60%
70%
60%
45%
60%
130%
60%
35%
70%
70%
35%
90%
30%
110%
35%
60%
30%
Squat
Squat
Squat
Pull-up
Pull-up
None
Pull-Up
Pull-Up
Pull-Up
Pull-Up to
Related
Pull-Up
Clean
Pull-Up
Clean
Pull-Up
Clean
Pull-Up
Snatch
Pull-Up
Snatch
Pull-Up
Snatch
Pull-Up
Clean
Pull-Up
Clean
Pull-Up
Clean
Pull-Up
Clean
Pull-Up
Clean
Pull-Up
Clean and Jerk
Pull-Up
Snatch
Pull-Up
Snatch
Pull-Up
Snatch
Pull-Up
Snatch
Pull-Up
Snatch
Pull-Up
Snatch
Pull-Up
Clean
Pull-Up
Clean
Pull-Up
Clean
Pull-Up
Clean
Pull-Up
Clean
Pull-Up
Snatch
Pull-Up
Snatch
Pull-Up
Snatch
Pull-Up
Snatch
Pull-Up
Snatch
Bench Press
Deadli�
Bench Press
Deadli�
Bench Press
Deadli�
Bench Press
Deadli�
Bench Press
None
Bench Press
None
Bench Press
None
Bench Press
None
Bench Press
None
Bench Press
None
Bench Press
None
Bench Press
None
Bench Press
None
Bench Press
None
Bench Press
None
Bench Press
None
Bench Press
None
Bench Press
None
Millitary Press
None
Millitary Press
Squat
Millitary Press
Squat
Millitary Press
Squat
Millitary Press
Squat
Millitary Press
Squat
Millitary Press
Squat
Millitary Press
Squat
Millitary Press
Squat
Millitary Press
Squat
Millitary Press
None
Millitary Press
None
Millitary Press
None
Millitary Press
None
Millitary Press
None
Millitary Press
None
None
None
None
None
None
None
None
None
None
None
Squat
None
Squat
None
Squat
Squat
Squat
Squat
Squat
Squat
Squat
Pull-up
Squat
Pull-up
Squat
None
Squat
Pull-Up
Squat
Pull-Up
Squat
Pull-Up
Squat
Pull-Up
Squat
Pull-Up
Squat
Pull-Up
Squat
Pull-Up
Squat
Pull-Up
Squat
Pull-Up
Squat
Pull-Up
Squat
Pull-Up
Squat
Pull-Up
Squat
Pull-Up
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%Used
%BW
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
60%
0%
60%
0%
60%
0%
100%
0%
100%
0%
100%
0%
0%
0%
0%
0%
100%
0%
100%
0%
100%
0%
100%
0%
100%
0%
100%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
70%
0%
70%
0%
70%
0%
70%
0%
70%
0%
100%
0%
100%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
100%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Barbell
Plates
Barbell
Barbell
Dumbells
Gymnas�c rings
Dumbells
Dumbells
Barbell
Barbell
Equipment
Used
Machine
Barbell
Machine
Barbell
Machine
Barbell
Machine
Barbell
Machine
Barbell
Dumbells
Barbell
Dumbells
Barbell
Dumbells
Barbell
Dumbells
Barbell
Dumbells
Barbell
Dumbells
Barbell
Dumbells
Barbell
Gymnas�c
rings
Barbell
Gymnas�c
rings
Barbell
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rings
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Chin
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Barbell
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Dumbells
Barbell
Dumbells
Barbell
Dumbells
Barbell
Dumbells
Fitness
Ball
Dumbells
Bodyweight
Dumbells
Fitness
Ball
Dumbells
Fitness
Ball
Barbell
Slideboard
Barbell Ball
Fitness
Barbell
Bodyweight
Plates
Machine
Plates Ball
Fitness
Plates
Machine
Dip Belt
Machine
Dip Belt
Bodyweight
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Gymnas�c rings
Machine
Landmine
Machine
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Dumbells
Dumbells
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Dumbells
Barbell
Dumbells
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Barbell
Ke�lebell
Trap
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Ke�lebell
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Ke�lebell
Fitness
Ball
Ke�lebell
Bodyweight
Log
Slideboard
Barbell Ball
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Barbell
Slideboard
Trap BarBall
Fitness
Bodyweight
Slideboard
Bodyweight
Fitness
Ball
Sled/Prowler
Bodyweight
Sled/Prowler
Bodyweight
Sled/Prowler
Bodyweight
Sled/Prowler
Fitness Ball
Sled/Prowler
Bodyweight
Sled/Prowler
Machine
Bodyweight
Machine
Fitness Ball
Barbell
Bodyweight
Barbell
Machine
Barbell
Dumbells
Barbell
Dumbells
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Dumbells
Barbell
Machine
Plates
Machine
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Barbell
Dumbells
Dumbells
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Dumbells
Barbell
Dumbells
Ke�lebell
Barbell
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Ke�lebell
Machine
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Dumbells
Trap Bar
Dumbells
Barbell
Dumbells
* Each dumbell
Note
* Each dumbell
* Each dumbell
* Each dumbell
* Each dumbell
* Each dumbell
* Each dumbell
* Each dumbell
* Each dumbell
* Each95-105%
dumbell
From
* Each dumbell
* Each dumbell
* Each dumbell
>105%
* Each dumbell
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* Each dumbell
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* Each dumbell
* Each dumbell
* Each dumbell
* Hard to carry/hold
* Each Ke�lebell
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* Each dumbell
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Box Squat
Cable Lateral Lunges
Cable Lateral Split Squat
DB Bulgarian Split Squat
DB Lateral Split Squat
DB Split Squat
DB Squat
Front Squat
Goblet Bulgarian Split Squat
Goblet Lateral Split Squat
Name
Goblet(Blocks)
Split Squat
Clean
GobletHigh
Squat
Clean
Pull (Blocks)
Ke�lebell
Squat
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Pull Front
(Blocks)
Leg Press
Snatch
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Overhead
Split
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High
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Overhead
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PullSquat
(Blocks)
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Clean
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Squat
Clean
High
Pull
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1-Leg
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DB Single
Split
CleanLeg Squat 1-Arm
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Single
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Box Pistol Squat
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Balance
Rings
SnatchBulgarian
High PullSplit Squat
Speed
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Pull
Wall
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Split Snatch
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Lateral Lunges
Clean
Barbell(Muscle)
Lunges
Clean
BarbellHigh
Reverse
Lunges
Clean
Pull (Hang)
BarbellPull
Step
Up
Clean
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BarbellClean
Walking
Lunges
Power
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(Hang)
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DropReverse
Downs (Ball)
Bridge Li� and Curl (Ball)
Bridge Li� and Curl (Slide Board)
Glute Bridge (Ball)
Glute Bridge (Elevated Feet)
Glute Ham Raise (GHR)
Hip Thrust (Ball)
Hyper 45 degree
Hyper 90 degree
Nordic Curl
Pull Through
Reverse Hyper
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Glute Bridge (Floor)
Good Morning
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Trap Bar Romania Deadli�
Zercher Romanian Deadli�
Bridge 1-Leg (Straight Leg Ball)
Bridge 1-Leg (Straight Leg)
Bridge Drop Downs (Slide Board)
Bridge Drop Downs 1-Leg (Ball)
Bridge Drop Downs 1-Leg (Slide Board)
Bridge Li� and Curl 1-Leg (Ball)
Bridge Li� and Curl 1-Leg (Slide Board)
Glute Bridge 1-Leg (Ball)
Glute Bridge 1-Leg (Elevated Feet)
Glute Bridge 1-Leg (Floor)
Glute Bridge 1-Leg Alterna�ng (Floor)
Hip Thrust 1-Leg (Ball)
Hip Thrust 1-Leg (Bench)
Hyper 45 degree 1-Leg
Hyper 90 degree 1-Leg
Lateral Bridge 1-Leg (Straight Leg Ball)
Lateral Bridge 1-Leg (Straight Leg)
Reverse Hyper 1-Leg
DB Romanian Deadli� 1-Arm/1-Leg (Contralateral)
DB Romanian Deadli� 1-Arm/1-Leg (Ipsilateral)
DB Romanian Deadli� 2-Arm/1-Leg
Good Morning 1-Leg
Plate Good Morning 1-Leg (Overhead)
Romanian Deadli� 1-Leg
Barbell Curls
DB Curls
Rings Inverted Row 1-Arm
1-Arm/1-Leg Row (Contralateral)
1-Arm/1-Leg Row (Ipsilateral)
Bench Pull
Bent Over Row
Cable Row (Neutral)
Cable Row (Pronated)
Cable Row (Rope)
Cable Row (Supinated)
Chest Supported Row
DB Bench Row 1-Arm
DB Bench Row 2-Arm
DB Bent Over Row 1-Arm (Neutral)
DB Bent Over Row 1-Arm (Wide)
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Category
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Ballis�c
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Ballis�c
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Ballis�c
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Ballis�c
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Ballis�c
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Ballis�c
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Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Grinding
Squat
Squat
Squat
Squat
Squat
Squat
Squat
Squat
Squat
Squat
Pa�ern
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
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Olympic
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Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
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Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
Squat
Olympic
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Squat
Hinge
Squat
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Squat
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Squat
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Squat
Hinge
Squat
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Hinge
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Hinge
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Hinge
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Hinge
Hinge
Hinge
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Hinge
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Hinge
Hinge
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Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
Pull
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Pull
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Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Variant
Double Leg
Blocks
Double Leg
Blocks
Double Leg
Blocks
Double Leg
Blocks
Double Leg
Blocks
Double Leg
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Double Leg
Ground
Double Leg
Ground
Double Leg
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Ground
Single Leg
Ground
Single
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Single
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Single
GroundLeg
Single
GroundLeg
Single
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Single
GroundLeg
Single
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Single Leg
Hang
Single Leg
Hang
Single Leg
Hang
Single Leg
Hang
Single Leg
Hang
Single
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Single
Hang Leg
Single
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Single Leg
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Hang
Single Leg
Blocks
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Double
Leg
Single Leg
Double
Leg
Single Leg
Double
Leg
Single Leg
Double
Leg
Single Leg
Double
Leg
Single Leg
Double
Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Double Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Single Leg
Accessory
Accessory
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
Horizontal
100%
25%
30%
25%
15%
25%
40%
85%
50%
40%
%
30%
95%
70%
75%
45%
105%
130%
95%
35%
75%
70%
105%
90%
100%
110%
80%
60%
110%
85%
90%
100%
85%
100%
80%
80%
110%
90%
25%
95%
40%
60%
40%
75%
40%
105%
35%
80%
10%
80%
20%
95%
20%
60%
20%
75%
20%
105%
25%
110%
70%
100%
30%
75%
30%
100%
30%
20%
35%
Squat
Squat
Squat
Squat
Squat
Squat
Squat
Squat
Squat
Squat to
Related
Squat
Clean
Squat
Clean
Squat
Clean
Squat
Snatch
Squat
Snatch
Squat
Snatch
Squat
Clean
Squat
Clean
Squat
Clean
None
Clean
None
Clean
None
Clean and Jerk
None
Snatch
None
Snatch
None
Snatch
None
Snatch
None
Snatch
None
Snatch
Squat
Clean
Squat
Clean
Squat
Clean
Squat
Clean
Squat
Clean
Squat
Snatch
Squat
Snatch
Squat
Snatch
Squat
Snatch
Squat
Snatch
Squat
Deadli�
Squat
Deadli�
Squat
Deadli�
Squat
Deadli�
Squat
None
Squat
None
Squat
None
None
None
None
None
None
None
None
None
None
None
None
None
35% Squat
105% Squat
50% Squat
100% Squat
75% Squat
40% Squat
65% Squat
75% Squat
70% Squat
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
None
30% Squat
25% Squat
20% Squat
30% Squat
10% Squat
45% Squat
35% Pull-up
20% Pull-up
None
25% Pull-Up
25% Pull-Up
70% Pull-Up
65% Pull-Up
60% Pull-Up
60% Pull-Up
60% Pull-Up
60% Pull-Up
70% Pull-Up
35% Pull-Up
30% Pull-Up
35% Pull-Up
30% Pull-Up
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%Used
%BW
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Barbell
Machine
Machine
Dumbells
Dumbells
Dumbells
Dumbells
Barbell
Ke�lebell
Ke�lebell Used
Equipment
Ke�lebell
Barbell
Ke�lebell
Barbell
Ke�lebell
Barbell
Machine
Barbell
Barbell
Barbell
Barbell
Trap Bar
Barbell
Barbell
Bodyweight
Barbell
Dumbells
Barbell
Dumbells
Barbell
Bodyweight
Barbell
Bodyweight
Barbell
Bodyweight
Barbell
Gymnas�c
rings
Barbell
Bodyweight
Barbell
Fitness Ball
Barbell
Barbell
Barbell
Barbell
Barbell
Barbell
Dumbells
Barbell
Dumbells
Barbell
Dumbells
Barbell
Dumbells
Barbell
Dumbells
Barbell
Ke�lebell
Barbell
Machine
Barbell
Barbell
Barbell
Barbell Ball
Fitness
Slideboard
Bodyweight
Slideboard
Fitness
Ball
Fitness Ball
Slideboard
Fitness Ball
Bodyweight
Machine
Fitness Ball
Machine
Machine
Bodyweight
Machine
Machine
Machine
Dumbells
Barbell
Barbell
Bodyweight
Barbell
Barbell
Barbell
Trap Bar
Barbell
Fitness Ball
Bodyweight
Slideboard
Fitness Ball
Slideboard
Fitness Ball
Slideboard
Fitness Ball
Bodyweight
Bodyweight
Bodyweight
Fitness Ball
Bodyweight
Machine
Machine
Fitness Ball
Bodyweight
Machine
Dumbells
Dumbells
Dumbells
Barbell
Plates
Barbell
Barbell
Dumbells
Gymnas�c rings
Dumbells
Dumbells
Barbell
Barbell
Machine
Machine
Machine
Machine
Machine
Dumbells
Dumbells
Dumbells
Dumbells
* Each dumbell
* Each dumbell
MLADEN JOVANOVIĆ
* Each dumbell
* Each dumbell
Note
* Hard to carry/hold
* Each Ke�lebell
* Each dumbell
* Each dumbell
* Each dumbell
* Each dumbell
From 95-105%
* Each dumbell
>105%
* Each dumbell
* Each dumbell
169
* Each dumbell
* Each dumbell
* Each dumbell
* Each dumbell
STRENGTH TRAINING MANUAL Volume One
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About
Mladen Jovanović is a Serbian Strength and Conditioning Coach and Sport
Scientist. Mladen was involved in the physical preparation of professional, amateur
and recreational athletes of various ages in sports, such as basketball, soccer,
volleyball, martial arts, tennis and Australian rules football. In 2010, Mladen started
the Complementary Training website and in 2017, developed the scheduling and
monitoring application, AthleteSR. He is currently pursuing his PhD at the Faculty of
Sports and Physical Education in Belgrade, Serbia.
Twitter: @physical_prep
Instagram: @physical_prep
Facebook: www.facebook.com/complementarytraining/
Website: www.complementarytraining.net
Email: coach.mladen.jovanovic@gmail.com
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