Downloaded from http://journals.lww.com/nsca-scj by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywC
X1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8KKGKV0Ymy+78= on 02/04/2024
Selection of Key
Performance Indicators
for Your Sport and
Program: Proposing a
Complementary ProcessDriven Approach
Jo Clubb, BSc,1 Sian Victoria Allen, PhD,2 and Kate K. Yung, PT, PhD3,4,5
Global Performance Insights, United Kingdom; 2Product Innovation, Lululemon Athletica, Vancouver, Canada;
3
Medical and Performance Innovations, Kitchee Sports Club, Hong Kong SAR, China; 4Centre for Data Science,
Queensland University of Technology, Brisbane, QLD, Australia; and 5Department of Orthopaedics and Traumatology,
Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
1
ABSTRACT
Key performance indicators (KPIs) are
commonplace in business and sport.
They offer an objective means to link
data and processes with performance
outcomes. Yet, their application in
sports performance, particularly team
sports, is not without issue. Here, we
review 4 key issues relating to KPI
application in team sports; lack of a
universal definition, complexity of performance, drifting from on-field performance goals with off-field targets, and
agency issues across different key
stakeholders. With these issues relating
to sports performance KPIs in mind, we
propose a complementary approach to
help practitioners focus on implementing the conditions that create performance environments and opportunities
for success in a complex sporting
Address correspondence to Jo Clubb, jo.
clubb@acu.edu.au.
environment. Ongoing process trackers
(OPTs) are quantifiable measures of the
execution of behaviors and processes
that create the environments, cultures,
and conditions for successful performance outcomes. This approach
equips sports science practitioners with
key questions they can ask themselves
and their team when starting to select
and use OPTs in their program.
INTRODUCTION
ey
performance
indicators
(KPIs) are used to evaluate the
performance of a sports team,
department, staff, and/or athletes themselves (12). They are commonplace in
business (52) and sports (30,35) on
account of the many benefits they offer.
Some examples include enabling objective evaluation of an organization, team,
or individual in meeting performance
goals (28), informing training and
K
practice decisions (25), and directly
being able to predict competition performance from KPIs (44,60).
Despite their ubiquity and copious benefits, some issues still exist with their use
in sports performance. These include
potential detrimental effects of measurement itself on athlete behaviors (24,41),
and concern with how well KPIs can
truly approximate performance in complex dynamic events such as team sports
(35). Furthermore, the increasing attention on sports performance support and
abundance of available data may induce
pressure to use KPIs to quantify the value
of performance support and try to demonstrate return on investment (12,31).
Conversely, practitioners are keen to
KEY WORDS:
sports science; sports performance; key
performance indicators; objectives and key
results; athlete monitoring
Copyright Ó National Strength and Conditioning Association
90 VOLUME 46 | NUMBER 1 | FEBRUARY 2024
Copyright © National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
Downloaded from http://journals.lww.com/nsca-scj by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywC
X1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8KKGKV0Ymy+78= on 02/04/2024
demonstrate how the data amassed and
the subsequent interventions used have a
positive impact on performance. Therefore, the purpose of this article is to discuss the issues with using KPIs in team
sports performance support. Based on
these issues, we propose a new framework, ongoing process trackers (OPTs).
This approach, which could be used in
conjunction with KPIs, is intended to
help sports performance practitioners
better select and track indicators of the
processes that ultimately underpin sports
performance.
CURRENT LANDSCAPE OF KEY
PERFORMANCE INDICATORS IN
SPORTS PERFORMANCE
Striving for peak performance is a central tenet of sporting endeavor. Thus, it
follows that sport staff will seek indicators that underpin performance on an
organizational, departmental, and individual level. Indeed, a recent organizational staff structure for team sports
proposed that performance staff,
including practitioners across sports
science, strength and conditioning,
nutrition, and psychology, and team
sport staff, made up of coaching and
scouting staff among others, each provide expertise related to specific KPIs
(11). Although the use of KPIs is relevant for team sport staff, in this article,
we focus our discussion predominantly
as it relates to performance staff.
One recent framework (12) has outlined
the following steps for performance staff
to use KPIs in a sporting setting.
Identify what it takes to succeed
Define the performance model
Determine KPIs
Assess the athlete
Plan and deploy the program of
interventions
Review
A performance model can be dissected
into the following determinants: physiologic demands, technical requirements,
tactical requirements, psychological
skills, equipment characteristics, health
aspects, and rules and regulations (12).
In
individual
time–distance-based
sports, the determinants of performance
may be more straightforward. For
instance, structural equation modeling in
swimming explained 79% of performance in young male athletes based on
biomechanical and energetic profiles (4).
Only variables that can be assessed by
performance staff were included in the
model and given the high prediction of
swim performance demonstrated, it
follows that the variables identified can
therefore be used for training control
and evaluation (4).
Such division of determinants offers performance staff an understanding of the
underpinning qualities to performance,
such as the physical capacities that can
be developed to enable the athlete to
meet, and potentially surpass, the physical demands of the sport. Associations
between jump power and heading success, and strength (predicted 1 repetition
maximum from a 3 repetition maximum
test) and tackle success in elite youth
soccer may warrant development of
such physical capacities, for example
(59). In addition, increases in reactive
strength (measured via drop jump performance) have been associated with
reductions in sprint times, whereas
increases in power (via countermovement jump performance) were associated with improvements in change of
direction abilities in elite female soccer
players (20). However, team sports performance offers greater complexity than
can often be broken down into linear
determinants of success (1). As such, simple deterministic approaches, such as
those used in individual time–distancebased sports, may be less suitable.
Therefore, the current approach to
applying KPIs in the team sport environment warrants a critical review.
ISSUES AND CHALLENGES WITH
KEY PERFORMANCE INDICATORS
In reviewing KPIs through a critical
lens, we have identified 4 areas of concern for their current application in
team sports. They are as follows.
Definition: Lack of a universal
definition
Complexity: Isolated metrics overlook the complexity of performance
Goodhart’s law: The threat of drifting
from on-field performance with offfield targets
Agency issues: Different stakeholders
often have competing interests
In this section, we will delve into each
of these issue areas in further detail.
LACK OF A UNIVERSAL
DEFINITION
Although many researchers have
aimed to formalize the definition of
KPIs for different sectors (18,36,40),
there remains a lack of universal agreement, especially in sport. Given the
widespread familiarity with the term,
it may be believed that a universal definition is unnecessary. Yet, potential
misuse of terminology is a long-time
cause for discussion in sports science
(34,54). One recent definition in sports
science is:
“a quantifiable measure used to evaluate
the success of an organization or employee
in meeting a performance objective” (12).
A performance objective is subsequently illustrated as winning a league,
tournament, or other championship,
achieving a specific time, distance, or
mass lifted in centimeter-gram-second
sports, or beating the opposition in
tactical events (12). Clearly in this
instance, clarity of the collective performance objective is required for KPIs to
be effective. Yet, this definition of KPIs
is firmly linked to a single-outcome
measure. Meanwhile, other definitions
use the properties of the measure itself,
asserting that KPIs should be a valid
measure of performance, an objective
measurement using a known scale of
measurement, and provide a valid
way of interpretation (42).
To add further confusion, similar but
different terminology, such as “performance indicators” (30) also exists. A
performance indicator is “a selection,
or combination, of action variables that
aims to define some or all aspects of a
performance” (30). In team sports, the
relationship between performance
indicators and match outcome has
been explored in Australian rules football (48), soccer (13) and rugby union
(33). In this context, performance indicators are statistical actions that can be
used to evaluate teams and individual
91
Copyright © National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
Strength and Conditioning Journal | www.nsca-scj.com
Key Performance Indicators
athletes, including which indicators are
likely to result in a winning outcome.
Downloaded from http://journals.lww.com/nsca-scj by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywC
X1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8KKGKV0Ymy+78= on 02/04/2024
It is clear from these various definitions
that a useful performance indicator
should relate to successful performance or outcome. These applications
traditionally sit within the performance analysis realm of team sports.
However, these definitions lack guidance for how such KPIs can be used
in practical terms. The focus on statistical actions during match play also
limits their use to the wider multidisciplinary performance staff. It is therefore unclear how current definitions
of KPIs relate to sports science data
collection. Such ambiguity may fuel
agency issues with how different stakeholders consider, interpret, and use
data in relation to their interpretation
of the term KPI.
ISOLATED METRICS OVERLOOK
THE COMPLEXITY OF
PERFORMANCE
As performance staff increasingly seek to
relate sports science data to performance, it seems (at least to the authors)
that KPIs may have become synonymous with broader terms such as metrics or variables, confusing the issue
further. This is perhaps because of the
abundance of metrics, thanks to the
expansion of data collection in today’s
sporting environments. Indeed, a recent
article described how the increase in data
streams within the contemporary training environment may cloud parsimonious and valid applications if not used
appropriately (31). It may also be
because of the breaking down of sports
performance into silos in traditional
fields such as physiology, biomechanics,
and performance analysis (53), in which
the term “performance indicator” may
have a specific context.
Previous literature has categorized performance indicators into match classification (e.g., score, number of shots on
targets), biomechanical (e.g., optimal
release angle for javelin throw (7)), technical (e.g., passes to oppositions (32)),
and tactical (e.g., passes and possessions
(30)). Yet, consideration is warranted as
to whether each of these categories
and individual indicators truly reflect
performance, and if so, how they combine to do so. One of the reasons why
individual indicators may not truly
reflect performance is because sports
performance, particularly in team
sports, is a complex entity (3). As such,
team performance is not only achieved
by qualities of the individual athletes
(e.g., technical skills or physical abilities), but also the emerging pattern
from the dynamic interaction between
individuals, their opponents, and environments (51). Therefore, the impact
of using isolated or specific measures
as KPIs, such as physical running output captured by in-game tracking technologies, is often limited (10,15).
Furthermore, different leagues may
require different physical or technical
KPIs to best approximate performance
(16). As well as overarching consideration for context, such as league or
position, more nuanced contextual factors are often lacking in developing
KPIs. Phatak et al. (46) recently demonstrated the need to account for
phase of play and other contextual factors such as ball possession. For example, accounting for ball possession
changes the interpretation of fouls as
a KPI in soccer (46). Caution is therefore warranted when it comes to labeling data as KPIs, particularly isolated
metrics that lack contextual narratives.
DRIFTING FROM ON-FIELD
PERFORMANCE WITH OFF-FIELD
TARGETS
Performance staff attempt to translate
their understanding of what it takes to
succeed into performance goals (12).
Drifting from these on-field performance
goals is a threat, because it may result in
time and attention being placed on areas
less meaningful to performance. This
may be driven by the different motivations of various stakeholders within team
sports, as we shall discuss in the next
section. In addition, using targets from
objective measurements may underpin
a drift from performance goals. This is
exemplified by Goodhart’s law. Named
after British economist Charles Goodhart, the common adaptation of the decree is by Marilyn Strathern:
“When a measure becomes a target, it
ceases to be a good measure.”
When outcomes are complex, as demonstrated by sport performance, a single
measure cannot represent them. This is
why there is rarely (if ever) a single KPI;
the complexity of performance warrants
multiple. Even within specific disciplines, physical development for example, a single measurement is often
underpinned by a multitude of factors.
This is illustrated by low predictive relationships between acceleration and
lower limb strength and power, for
example, indicating a complex interaction between sprint technique and leg
muscle performance (37). Therefore, if
each indicator is imperfectly correlated
with the goal of performance, concentrating on them in isolation may inadvertently create unwanted distractions
and inefficient application of resources.
This has been exemplified elsewhere in
areas such as academic publishing (21),
higher education (19), and government
spending (29) to name a few.
Although using KPIs as targets can
drive processes that have positive effects
on performance, Goodhart’s law serves
as a reminder that targets may distract
from the goal of on-field sporting performance. Given the limited time and
resources available to performance staff,
these must be spent on the most impactful contributors to performance. Lower
limb strength and power measures may
frequently be converted into targets for
athletic development, but although
meaningful, they do not solely account
for performance. Although strength and
maximal power were the best discriminators of playing level in rugby league,
they still only accounted for 12–17% of
the variation in playing level (1). Similarly, KPIs that focus on vertical force
production, such as those derived from
countermovement jump performance,
may overlook the importance of horizontal force production and therefore,
limit transference of gym-based strength
to on-field performance (47).
Beyond the issue of time efficiency,
performance staff are in danger of
“naive interventionism” if potential
92 VOLUME 46 | NUMBER 1 | FEBRUARY 2024
Copyright © National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
Downloaded from http://journals.lww.com/nsca-scj by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywC
X1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8KKGKV0Ymy+78= on 02/04/2024
harmful effects of so-called performance targets are not considered
(55). Indeed, iatrogenics (“caused by
the healer” in Greek) represents a treatment that causes more harm than good
(55). Goodhart’s law may underpin iatrogenics in sports performance that
result from turning measures into evaluations. In some cases, this may have
been witnessed through the assessment
of total distance covered as measured
by tracking technology, which has
been reported to have led to some athletes running around during breaks in
play simply to increase their distance
covered (23). Similarly, velocity based
training provides objective feedback on
bar velocity numbers during strength
work, which can improve training
intent, but with poor implementation
could encourage athletes to chase targets to the detriment of technique, and
potentially safety (23).
Another example is performance staff
may set targets to address asymmetries
assessed through strength and power
testing, such as ,10% interlimb asymmetry for return to sport from injury
(8,38). However, clinicians have also
acknowledged that the unaffected limb
is rarely normal (43) and research has
yet to demonstrate a clear influence of
asymmetry on performance (8,39). Further research is warranted to understand
whether intervention planning to target
asymmetry reduction is beneficial (43).
A final example may be setting bodyweight targets, which could lead to athletes engaging in unhealthy weight loss
behaviors. For example, 22% of youth
American football players given bodyweight targets in order to be selected
to compete were deemed to be at risk
of abnormal eating behaviors, with eating binges, excessive exercise and drastic
weight loss methods such as sauna use
reported (61). Such body-mass manipulation can lead to dehydration that may
affect performance in subsequent training activities (6), and similar thermal
weight loss techniques have been
described as “concerning” in combat
sports (5). Despite good intentions, such
emphasis on metrics has the potential to
adversely affect the quality of output and
can distract from, or even replace the
original purpose (23). Therefore, performance staff should use continuous
reflection and intention to ensure any
targets introduced serve their central
goal of enhancing sports performance.
DIFFERENT STAKEHOLDERS
OFTEN HAVE COMPETING
INTERESTS
KPIs can be different for different stakeholders. In business, organizations have
multiple stakeholders reflecting multiple
functions (52). Similarly in sport, different
stakeholders can be seen as competitors
with different motivations and means to
achieve them (22). For example, physical
preparation staff may seek to set high
training load targets to maximize performance, whereas medical staff seek to
control training load to minimize risk
of injury (22). However, agency problems and conflict may arise if performance staff select these KPIs in relative
isolation, without considering the interests of all involved stakeholders, even if
well-intentioned. For example, an injured
athlete may be concerned about their
place in the team and an upcoming contract extension, and thereby wanting to
play as soon as possible, whereas the
medical staff are predominantly concerned about the rehabilitation and subsequent re-injury risk.
Nevertheless, the team sport staff (e.g.,
coaches) would like the player to compete in an imminent important game,
because they are concerned about the
team’s winning percentage. When the
above stakeholders’ KPIs do not align,
it may lead to tension within the sports
organization. To resolve these kinds of
agency problems, performance staff
and team sport staff may adopt a shared
decision-making model when making
decisions regarding rehabilitation (62).
Expansion of this model, however, is
needed to better support them in how
to go about selecting their KPIs or
performance-focused measures.
Indeed, the rehabilitation setting may
warrant greater attention to KPIs, given
the more controlled nature of returning
an athlete from injury, and potential tension between physical performance and
medical staff during such an interdisciplinary process (22). KPIs may cover
medical (e.g., palpation pain and range
of motion), physical (e.g., high-speed
running and accelerations), and technical
aspects (e.g., passing and tackling) (56).
Time and/or clinical markers for return
to play may also be seen as a KPI (9).
Although these markers may not necessarily be named KPIs per se, they serve
similar purposes in evaluating the player’s performance and gauging their progression in RTP.
When performance is placed as the primary goal, competition between key
stakeholders
should
disappear.
Performance-focused measures determined in an interdisciplinary manner
can bring stakeholders together as teammates (22). For instance, greater preseason participation has been associated
with lower in-season injury risk (58);
therefore, the so-called training loadinjury paradox is actually in the best
interest of physical preparation and the
medical staff. Targets for injury availability may also be used, given the relationship between injuries and chance of
success demonstrated across a variety
of sports (12). It remains clear, however,
that differing responsibilities within the
performance staff, in addition to the
wider team sport staff, can threaten
agency issues when incorporating KPIs
in applied practice.
A NEW FRAMEWORK FOR
PERFORMANCE INDICATORS:
ONGOING PROCESS TRACKERS
One of the main reasons KPIs are used
so broadly is that they provide many
well-established benefits in supporting
individuals, teams, and organizations in
monitoring progress toward desired performance goals. However, given some of
the issues highlighted above, complementing KPIs with other tools may offer
a more complete approach to evaluating
performance progress over the longterm. Here, we propose a new approach
to KPIs that may offer a solution to any
unintended consequences associated
with traditional KPIs and a complementary means to help more holistically
track and support the progress of athletes or teams toward performance goals.
93
Copyright © National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
Strength and Conditioning Journal | www.nsca-scj.com
Key Performance Indicators
Downloaded from http://journals.lww.com/nsca-scj by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywC
X1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8KKGKV0Ymy+78= on 02/04/2024
Ongoing process trackers are quantifiable measures of the execution of behaviors and processes that create the
environments, cultures, and conditions
for successful performance outcomes.
Where traditional KPIs are often based
on metrics that directly serve outcome
goals, OPTs focus on measuring how
well an athlete or team are adhering to
the pathway toward achieving specific
outcomes. The rationale for the development of OPTs thus stems heavily from
literature describing the developmental
pathway to peak performance of top
athletes, and literature related to the
interplay between process and outcome
for supporting successful sporting performance. Specifically, one of the key
Table 1
Characteristics of effective OPTs
Characteristic
Long-term
Actions
Establish a bold vision, then align and
commit to the long-term goals it will
take to achieve the vision as a
multidisciplinary team
Applied examples
Team promoted to the first division after 3
years
Develop the leading physical preparation
program in the league. Evidenced by
scoring the most points in the latter
stages of games
Focused on the processes and behaviors Assemble the necessary multidisciplinary Each athlete understands and can
articulate the “why” behind their
expertise and bring all stakeholders
that constitute the pathway to
physical preparation program
together
performance success
Breakdown long-term goals into the steps Each athlete completes a designated
number of personalized physical
it will take to achieve them harnessing
preparation sessions a month
this expertise
All athletes are on time for all training
Acknowledge the complex and nonlinear Use a basket of OPTs
sessions
nature of performance
Think about the environment, conditions,
All athletes bring the right kit and
and culture you want to create to
equipment to all training sessions
facilitate long-term success and develop
OPTs to help reinforce these
Represent and engage all key
stakeholders
Medical: each athlete completes a full
Include at least one OPT per key
blood panel every 3 mo to optimize
stakeholder group
opportunity for physical adaptation
Allow key stakeholders to design their own
Psychology: each athlete completes
OPTs to best support identified longreflective practice journaling after each
term goals
physical preparation session to seek
Communicate all stakeholder OPTs for full
opportunities to accelerate learning and
transparency and alignment
development
Contextual
Consider different ways to appropriately
assess OPTs, such as observational
measures
Adapt OPTs as needed based on new
information, learnings, and context
Prevention of Goodhart’s law
Antigoal: Athletes having to get up early to
Develop “antigoals”
attend a mandatory team recovery
If KPIs are also used, review alongside OPTs
session the day after a match or
to ensure outcomes and processes are
competition, compromising their sleep
continually assessed (see below)
and ironically, their recovery and
ongoing physical development
Integration of OPTs and KPIs
Experienced athlete with perfect Olympic
Consider the learning and skill
lifting technique: focus on hitting
development phase of individual
specific testing numbers
athletes and their readiness for focusing
Lesser experienced athlete: focus on
on processes or outcomes
Olympic lifting technique development,
for example, integrating and executing
specific coaching cues or drills
Improvements to running technique, as
observed and assessed by multiple
practitioners and/or coaches
94 VOLUME 46 | NUMBER 1 | FEBRUARY 2024
Copyright © National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
Downloaded from http://journals.lww.com/nsca-scj by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywC
X1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8KKGKV0Ymy+78= on 02/04/2024
factors distinguishing “super-elite” athletes (Olympic and/or World Champions)
from
“elite”
athletes
(international representatives but nonmedalists) in a multidisciplinary developmental biography study (27) was the
joint focus of super-elites on mastery
and outcome goals, whereas elite athletes demonstrated a strong outcome
focus only. In addition, although superelite athletes reported similar training
volumes and training characteristics in
adulthood, their continued performance
improvement compared with elite athletes was attributed in significant part to
the positive psychosocial characteristics
of their training environment related to
their mastery orientation (26). Furthermore, in team sports, a perceived mastery climate created by coaches and
performance staff is a stronger predictor
of player performance than individual
psychological factors such as mental
toughness and grit (45).
Indeed, focusing on the process over
the outcome has long been a strategy
favored by top coaches to help athletes
manage the challenges and stressors
associated with performance under
pressure (14). Equally, a recent metaanalysis concluded that using process
goals had a much larger positive effect
on athlete performance (d 5 1.36)
compared with performance goals (d
5 0.44). Process goals can be effective
when set in isolation (57). That said,
other research has shown that performance is best served by focusing on
process goals for areas of learning
and development, with a switch to outcome focuses for areas of mastery (63).
Practically speaking, we suggest that
practitioners may wish to integrate
OPTs and KPIs into their measurement
practice, potentially with individualized approaches for different athletes.
Borrowing from the business world,
many top companies such as Google,
Amazon, and Uber have successfully
used a goal system called objectives
and key results (OKRs) to help set
goals and track progress toward them
(17). Where traditional KPIs are often
fixed and act to monitor the day-to-day
health of a system (e.g., 80% squad
availability), OKRs are agile and designed to also hold teams to bold and
ambitious long-term goals (e.g.,
become the top injury management
program in the league). Thus, we have
adapted several elements key to the
success of OKRs in this framework,
in the hope that this will help practitioners effectively implement OPTs
within their program. Table 1 presents
the characteristics of OPTs with corresponding actions for practitioners,
along with applied examples.
By helping to focus athletes, departments, and/or entire teams and organizations on the process over the outcome,
complementing KPIs with OPTs may
offer several potential advantages over
traditional KPIs alone. First, by their
design, they aim to reinforce behaviors
that contribute to performance success,
helping to avoid the negative consequences of Goodhart’s law—these positive behaviors function as measures and
targets that are helpful for performance
(24). Conversely, they can include “antigoals,” behaviors or approaches that
should be avoided to meet the OPTs.
This feature would ensure that performance is never inadvertently compromised to achieve targets.
Second, given the complexity of human
performance, even our best predictive
models populated by reams of data still
struggle to help us understand how the
multiple variables traditionally assigned
as KPIs combine to contribute to team
sport performance, particularly in openskill sports such as soccer, basketball,
and Australian rules football (35).
Instead, OPTs would help acknowledge
these unknowns and would be intended
to help tip an athlete’s or team’s odds in
favor of success. Third, they offer the
capacity to harness the experience, intuition, and context of practitioner and
coaching teams in defining the processes
for success in ways that traditional KPIs
Figure 1. A checklist infographic for selecting and using OPTs.
95
Copyright © National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
Strength and Conditioning Journal | www.nsca-scj.com
Key Performance Indicators
Downloaded from http://journals.lww.com/nsca-scj by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywC
X1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8KKGKV0Ymy+78= on 02/04/2024
based solely on data-driven targets often
neglect (24). Even in a data-abundant
sports performance environment, it warrants remembering that not everything
that can be measured matters, and not everything that matters can be measured (49). In
addition, OPTs may also help drive talent development in a team, program, or
organization by creating a culture that
encourages younger or less-experienced
athletes to model the positive behaviors
of more experienced athletes, and helping to incentivize the value of long-term
athlete development, and short-term
performance outcomes (2). Finally, by
encouraging athletes to focus on controllable factors, OPTs may offer the ancillary benefit of fostering athlete
autonomy and intrinsic motivation
(50), helping prevent burnout and supporting athlete well-being while facilitating long-term performance success.
goals rather than a sole focus on outcome measures. Using a basket of
OPTs allows different key stakeholders
to engage and align to support the
behaviors that can lead to long-term
goals of an organization. Practitioners
can use the OPT checklist (Figure 1) to
track and demonstrate how their program supports process-driven goals.
Conflicts of Interest and Source of Funding:
The authors report no conflicts of interest
and no source of funding.
Jo Clubb is a
sports science
consultant at her
company, Global
Performance
Insights.
4.
5.
6.
7.
8.
9.
10.
11.
Multiple strategies may support the
effective implementation of OPTs in
sports performance environments.
Given the multitude of data now collected, combined with the nonlinear
relationship to performance, using
OPTs may also help practitioners
demonstrate the buy-in and success
of a program with some distance from
on-field outcomes. Figure 1 displays a
checklist with key questions performance staff practitioners can ask themselves and their team when starting to
select and use OPTs in their program.
12.
Sian Victoria
Allen is a physiologist working in
industry R&D
at lululemon
athletic.
13.
14.
15.
16.
Kate K. Yung is
a researcher and
the Director of
Medical and
Performance
Innovations at
Kitchee S.C.
CONCLUSION
Despite widespread adoption, using
KPIs can be problematic given the
complex and nonlinear nature of team
sports performance. This concern is
compounded by the growing data
abundance and multidisciplinary practitioners within the performance staff,
which can cause a drift from on-field
performance goals and agency issues
across different stakeholders. Given
these issues, we propose a complementary framework, OPTs, that shifts
attention to the processes that underpin performance. These are quantifiable measures of the behaviors and
processes that create the environment
for success, underpinned by mastery
3.
17.
18.
19.
20.
21.
22.
REFERENCES
1.
2.
Baker DG, Newton RU. Comparison of lower body
strength, power, acceleration, speed, agility, and
sprint momentum to describe and compare playing
rank among professional rugby league players.
J Strength Cond Res 22: 153–158, 2008.
Baker J, Schorer J, Wattie N. Compromising talent:
Issues in identifying and selecting talent in sport.
Quest 70: 48–63, 2018.
23.
Balague N, Torrents C, Hristovski R, Davids K,
Araújo D. Overview of complex systems in sport.
J Syst Sci Complex 26: 4–13, 2013.
Barbosa TM, Costa M, Marinho DA, Coelho J, Moreira
M, Silva AJ. Modeling the links between young
swimmers’ performance: Energetic and biomechanic
profiles. Pediatr Exerc Sci 22: 379–391, 2010.
Barley OR, Chapman DW, Abbiss CR. Weight
loss strategies in combat sports and concerning
habits in mixed martial arts. Int J Sports Physiol
Perform 13: 933–939, 2018.
Barr SI. Effects of dehydration on exercise
performance. Can J Appl Physiol 24: 164–172,
1999.
Best RJ, Bartlett RM, Sawyer RA. Optimal javelin
release. J Appl Biomech 11: 371–394, 1995.
Bishop C, Turner A, Read P. Effects of inter-limb
asymmetries on physical and sports performance: A
systematic review. J Sports Sci 36: 1135–1144,
2018.
Brinlee AW, Dickenson SB, Hunter-Giordano A,
Snyder-Mackler L. ACL reconstruction rehabilitation:
Clinical data, biologic healing, and criterion-based
milestones to inform a return-to-sport guideline. Sports
Health 14: 770–779, 2022.
Brito Souza D, López-Del Campo R, Blanco-Pita
H, Resta R, Del Coso J. Association of match
running performance with and without ball
possession to football performance. Int J Perform
Anal Sport 20: 483–494, 2020.
Calleja-González J, Bird SP, Huyghe T, et al. The
recovery umbrella in the world of elite sport: Do not
forget the coaching and performance staff. Sports
9: 169, 2021.
Cardinale M. Key performance indicators. In:
NSCA’s Essentials of Sport Science. Champaign,
IL: Human Kinetics, Inc, 2022.
Castellano J, Casamichana D, Lago C. The use of
match statistics that discriminate between
successful and unsuccessful soccer teams. J Hum
Kinetics 31: 137–147, 2012.
Dehghansai N, Pinder RA, Baker J, Renshaw I.
Challenges and stresses experienced by athletes
and coaches leading up to the Paralympic Games.
PLoS ONE 16: e0251171, 2021.
Del Coso J, Brito de Souza D, Moreno-Perez V,
et al. Influence of players’ maximum running speed
on the team’s ranking position at the end of the
Spanish LaLiga. Int J Environ Res Public Health
17: 8815, 2020.
Dellal A, Chamari K, Wong DP, et al. Comparison
of physical and technical performance in European
soccer match-play: FA premier league and La liga.
Eur J Sport Sci 11: 51–59, 2011.
Doerr J. Measure What Matters: OKRs: The
Simple Idea That Drives 10x Growth. London,
United Kingdom: Portfolio Penguin, 2018.
Domı́nguez E, Pérez B, Rubio ÁL, Zapata MA. A
taxonomy for key performance indicators
management. Comput Stand Inter 64: 24–40, 2019.
Elton L. Goodhart’s law and performance
indicators in higher education. Eval Res Educ 18:
120–128, 2004.
Emmonds S, Nicholson G, Begg C, Jones B,
Bissas A. Importance of physical qualities for
speed and change of direction ability in elite
female soccer players. J Strength Cond Res 33:
1669–1677, 2019.
Fire M, Guestrin C. Over-optimization of academic
publishing metrics: Observing Goodhart’s law in
action. GigaScience 8: giz053, 2019.
Gabbett TJ, Whiteley R. Two training-load paradoxes:
Can we work harder and smarter, can physical
preparation and medical Be teammates? Int J Sports
Physiol Perform 12: S250–S254, 2017.
Gamble P. Prepared: Unlocking Human
Performance With Lessons From Elite Sport.
Informed in Sport Publishing, 2020. Available at:
https://www.amazon.co.uk/Prepared-UnlockingHuman-Performance-Lessons/dp/177521866X.
Accessed April 12, 2023.
96 VOLUME 46 | NUMBER 1 | FEBRUARY 2024
Copyright © National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
24.
Downloaded from http://journals.lww.com/nsca-scj by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywC
X1AWnYQp/IlQrHD3i3D0OdRyi7TvSFl4Cf3VC4/OAVpDDa8KKGKV0Ymy+78= on 02/04/2024
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
Gamble P, Chia L, Allen S. The illogic of being datadriven: Reasserting control and restoring balance in
our relationship with data and technology in football.
Sci Med Football 4: 338–341, 2020.
Groom R, Cushion C, Nelson L. The delivery of
video-based performance analysis by England
youth soccer coaches: Towards a grounded
theory. J Appl Sport Psychol 23: 16–32, 2011.
Güllich A, Hardy L, Kuncheva L, et al.
Developmental biographies of olympic super-elite
and elite athletes: A multidisciplinary pattern
recognition analysis. J Expert 2: 23–46, 2019.
Hardy L, Barlow M, Evans L, Rees T, Woodman T,
Warr C. Great British medalists: Psychosocial
biographies of super-elite and elite athletes from
Olympic sports. Prog Brain Res 232: 1–119,
2017.
Herold M, Kempe M, Bauer P, Meyer T. Attacking
key performance indicators in soccer: Current
practice and perceptions from the elite to youth
academy level. J Sports Sci Med 20: 158–169,
2021.
Hood C, Piotrowska B. Goodhart’s law and the
gaming of UK public spending numbers. Public
Perform Manag Rev 44: 250–271, 2021.
Hughes MD, Bartlett RM. The use of performance
indicators in performance analysis. J Sports Sci
20: 739–754, 2002.
James LP, Talpey SW, Young WB, Geneau MC,
Newton RU, Gastin PB. Strength classification
and diagnosis: Not all strength is created equal.
Strength Cond J 45: 333–341, 2023.
James N. Notational analysis in soccer: Past,
present and future. Int J Perform Anal Sport 6: 67–
81, 2006.
Jones NMP, Mellalieu SD, James N. Team
performance indicators as a function of winning
and losing in rugby union. Int J Perform Anal Sport
4: 61–71, 2004.
Knuttgen HG, Kraemer WJ. Terminology and
measurement in exercise performance. J Strength
Cond Res 1: 1–10, 1987.
Lames M, McGarry T. On the search for reliable
performance indicators in game sports. Int J
Perform Anal Sport 7: 62–79, 2007.
Lindberg C-F, Tan S, Yan J, Starfelt F. Key
performance indicators improve industrial
performance. Energ Proced 75: 1785–1790,
2015.
Lockie RG, Jalilvand F, Callaghan SJ, Jeffriess MD,
Murphy AJ. Interaction between leg muscle
performance and sprint acceleration kinematics.
J Hum Kinetics 49: 65–74, 2015.
Maestroni L, Read P, Bishop C, Turner A. Strength
and power training in rehabilitation: Underpinning
principles and practical strategies to return
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
athletes to high performance. Sports Med 50:
239–252, 2020.
Maloney SJ. The relationship between asymmetry
and athletic performance: A critical review.
J Strength Cond Res 33: 2579–2593, 2019.
Maté A, Trujillo J, Mylopoulos J.
Conceptualizing and specifying key
performance indicators in business strategy
models. In: Conceptual Modeling (Vol. 7532).
Atzeni P, Cheung D, and Ram S, eds.
Berlin, Heidelberg: Springer Berlin
Heidelberg, 2012. pp. 282–291. Available
at: http://link.springer.com/10.1007/978-3642-34002-4_22. Accessed December 20,
2022.
McGuigan M. Monitoring Training and
Performance in Athletes. Champaign, IL: Human
Kinetics, 2017.
O’Donoghue P. Research Methods for Sports
Performance Analysis. Routledge, 2009. Available
at: https://www.taylorfrancis.com/books/
9781134005369. Accessed December 20, 2022.
Paton BM, Read P, Van Dyk N, et al. London
international consensus and delphi study on
hamstring injuries part 3: Rehabilitation, running
and return to sport. Br J Sports Med 57: 278–291,
2023.
Perl J, Memmert D. A pilot study on offensive
success in soccer based on space and ball control
—key performance indicators and key to
understand game dynamics. Int J Comput Sci
Sport 16: 65–75, 2017.
Pettersen SD, Martinussen M, Handegård BH,
Rasmussen L-MP, Koposov R, Adolfsen F. Beyond
physical ability—predicting women’s football
performance from psychological factors. Front
Psychol 14: 1146372, 2023. Available at: https://
www.frontiersin.org/articles/10.3389/fpsyg.
2023.1146372/full. Accessed April 4, 2023.
Phatak AA, Mehta S, Wieland F-G, et al. Context is
key: Normalization as a novel approach to sport
specific preprocessing of KPI’s for match analysis
in soccer. Sci Rep 12: 1117, 2022.
Randell AD, Cronin JB, Keogh JW, Gill ND.
Transference of strength and power adaptation to
sports performance—horizontal and vertical force
production. Strength Cond J 32: 100–106, 2010.
Robertson S, Back N, Bartlett JD. Explaining
match outcome in elite Australian Rules football
using team performance indicators. J Sports Sci
34: 637–644, 2016.
Rosling H, Rosling O, Rönnlund AR. Factfulness:
Ten Reasons We’re Wrong about the World—and
Why Things Are Better Than You Think. London,
United Kingdom: SCEPTRE, 2018.
Ryan RM, Deci EL. Self-determination theory and
the facilitation of intrinsic motivation, social
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
development, and well-being. Am Psychol 55: 68–
78, 2000.
Salmon PM, McLean S. Complexity in the beautiful
game: Implications for football research and
practice. Sci Med Football 4: 162–167, 2020.
Schein EH. Organizational Culture and
Leadership. 3. San Francisco, CA: Jossey-Bass,
2004.
Springham M, Walker G, Strudwick T, Turner A.
Developing strength and conditioning coaches for
professional football. Coaching Prof Football 50:
9–16, 2018.
Staunton CA, Abt G, Weaving D, Wundersitz
DWT. Misuse of the term “load” in sport and
exercise science. J Sci Med Sport 25: 439–444,
2022.
Taleb NN. Antifragile: How to Live in a World We
Don’t Understand: London, United Kingdom: Allen
Lane, 2012.
Whiteley R, van Dyk N, Wangensteen A, Hansen
C. Clinical implications from daily physiotherapy
examination of 131 acute hamstring injuries and
their association with running speed and
rehabilitation progression. Br J Sports Med 52:
303–310, 2018.
Williamson O, Swann C, Bennett KJM, et al. The
performance and psychological effects of goal
setting in sport: A systematic review and metaanalysis. Int Rev Sport Exerc Psychol 1–29: 2022.
Windt J, Gabbett TJ, Ferris D, Khan KM. Training
load–injury paradox: Is greater preseason
participation associated with lower in-season
injury risk in elite rugby league players? Br J Sports
Med 51: 645–650, 2017.
Wing CE, Turner AN, Bishop CJ. Importance of
strength and power on key performance indicators
in elite youth soccer. J Strength Cond Res 34:
2006–2014, 2020.
Yang G, Leicht AS, Lago C, Gómez M-Á. Key team
physical and technical performance indicators
indicative of team quality in the soccer Chinese
super league. Res Sports Med 26: 158–167,
2018.
Yeargin S, Torres-McGehee TM, Emerson D, Koller J,
Dickinson J. Hydration, eating attitudes and
behaviors in age and weight-restricted youth
American football players. Nutrients 13: 2565, 2021.
Yung KK, Ardern CL, Serpiello FR, Robertson S. A
framework for clinicians to improve the decisionmaking process in return to sport. Sports Med
Open 8: 52, 2022.
Zimmerman BJ, Kitsantas A. Developmental
phases in self-regulation: Shifting from process
goals to outcome goals. J Educ Psychol 89: 29–
36, 1997.
97
Copyright © National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
Strength and Conditioning Journal | www.nsca-scj.com