10 challenges for a sport scientist
10 Challenges Facing Today’s Applied Sport
Scientist
Yann Le Meur 1 2
and Lorena Torres-Ronda 3 4
1
AS Monaco Football Club, Monaco,2
Universit´e Cˆote d’Azur, LAMHESS, Nice, France,3
National Basketball Association (NBA), San Antonio, Texas, US, and 4
Institute for
Health and Sport (IHES), Victoria University, Melbourne, AUS
Applied Science | High-performance | Opinion Paper
Introduction
The role of the sport scientist in high-performance sport
organisations is currently very diverse internationally.
Countries like Australia or the United Kingdom have long
histories of placing sport scientists in professional teams and
federations; these countries have been pioneers in this area
via/through the English Institute of Sport (EIS), the Australian
Institute of Sport (AIS) or professional team clubs
(e.g. Australian Football League, Rugby League or the Premier
League). There, the figure of the sport scientist is well
integrated in the organisational chart, playing a key role in
the overall performance and the staff are completely familiar
with the role, in the same way they are with fitness coaches
or physiotherapists. However, this situation is not common in
other countries like Spain, France, or the United States (US),
to mention but a few. For example, in the US only about a
third of the National Basketball Association (NBA) organisations
(30 franchises in total) have a full-time sport scientist on
their performance staff. In another example, in France, where
the French 1st division in football is growing yearly and the
TV rights are currently exceeding 1 billion Euros per season,
only two clubs (out of 20 Ligue 1 teams) have a sport scientist
working full-time, to the best of our knowledge and at the
time of writing. This situation is also similar in other professional
or Olympic sports, which makes this job exciting but
at the same time extremely challenging since, in most cases,
everything still needs to be built.
Being aware of this challenging situation, we decided to
write this opinion paper to share our experience in this area.
Seen from the outside, being a sport scientist in a country
(or a sport organisation) without tradition in this field could
seem easy. Moreover, often the media reports how top-teams
are building their success by taking advantage of the latest
research or from novel technologies. People retain the sexiest
aspects of the job: nice dashboards, 2.0 technologies or
fluid communication, among others; but less is said or written
about the submerged part of the iceberg, which involves
complex human relationships, doubts, personalities, mistakes,
resilience or educating the sporting community.
The main goal of this article is to expose some of the challenges
that, in our opinion and experience, may involve the
implementation of sport science in high-performance and professional
sports lacking tradition in this role, and to discuss
the concerns pertaining to the work of the sport scientist in
those environments where such a position is new.
CHALLENGE 1: Understanding your (new) context
and challenging yourself
In a country or an organisation where the implementation of
sport science remains in its infancy, the general profile of a
full-time sport scientist position is a male with 30-45 years
of age, preferably with a PhD in sport sciences, although not
necessarily with previous experience in that particular sport,
but presumably with previous experience as a strength and
conditioning coach. However, this is just a stereotype.
The sport scientist is expected to provide support to the
performance and medical staff, mainly through the implementation
of monitoring strategies and readiness assessments. It
is also common that they may be involved in the process of
recovery, optimising injury prevention, nutritional strategies
or even overseeing the strength and conditioning programs.
Some of them can also have research and development responsibilities.
On the other hand, some are not allowed by their
institution or the league (1) to share or publish team data in
order to maintain the research processes internally. However,
sometimes expectations may not be well defined or clear, at it
is up to the sport scientist to define them him/herself.
One of the first challenges is certainly to understand the
context and the sport/club culture (the non-written codes),
and probably the individual will have to adapt depending on
their sport science background: academia versus “hands-on”
(2). The path of the sport scientist generally starts in the academic
environment (university, research laboratories, or alike),
where after a sport science degree, he/she conducts a PhD in
a specific field of knowledge (e.g. physiology, recovery, sports
nutrition, etc.). In this context, there is time for reflection
to address the research question, data collection can take several
weeks (or months), and most of the time the deadlines
for the different steps of the process or the final result are
vague. The arguments of the conclusions are research-based
(aka evidence-based), and the results are valued by a thesis
committee or a peer-reviewed journal process, where the final
reward is a dissertation and published paper(s).
For a sport scientist working in a high-level or professional
sport organisation the situation is completely different. Unlike
the academic environment, orientated towards a specialisation,
the spectrum of topics to cover is large and does not
always rely on the initial specialisation or area of expertise
of the sport scientist. The scientific method should be the
same, an orderly series of procedures to try to extend our
knowledge and solve questions that include (but are not limited
to): data collection, data analysis, drawing conclusions
and, finally, communicating the results. However, the process
is quite different compared to academia.
Firstly, questions can potentially come from very different
areas related to performance, which pushes the sport scientist
to develop a multifaceted/polyvalent profile instead of exacerbating
the one specific area of expertise, although the need
for specialisation can also occur. Secondly, the data collection
needs to be time-efficient, easy to gather, as non-fatiguing /
non-invasive as possible, and often completed by the whole
team simultaneously (3). Additionally, the amount of time
available for data analysis is short and in most cases a report
must be delivered before the next training session, which
usually means in the following minutes, hours or the next day.
The data collection (e.g. training, game, physical assessments)
and its analysis processes (i.e. reports) are usually established
at the beginning of the season and remain stable during the
sportperfsci.com 1 SPSR - 2019 | Mar | 57 | v1
10 challenges for a sport scientist
current season. On top of that, the new data tsunami (4)
pushes the sport scientist to keep developing data analysis
skills (not only basic statistical analysis, but data mining and
programming) or to collaborate with other experts (e.g. data
analysts, data scientist) to make the process as efficient as possible
and the reports understandable and interpretable by the
different receivers of the information. Related to this point,
the way to communicate the results differs in both contexts
too. In university, the sport scientist mainly has to teach
students and/or to drive research, and he/she makes the decisions
(in agreement with the university). On the contrary, in a
high-performance organisation the situation is quite different.
In this context, the role of the sport scientist is to facilitate
the process of decision-making of others, from the head coach
and his/her staff to the management personnel.
On the other hand, the same way Australia or the UK have
a great tradition in sport science, individuals from these countries
may be disadvantaged by their knowledge of the US major
leagues’ sports (NBA, NFL, NHL, or MLB) or other sports.
Hence, maybe one way or another, you can find yourself in a
new context.
Tips to handle challenge 1
ˆ Understand your context.
ˆ Understand the sport that you are working in.
ˆ If your role is not well defined, it may be on you to define
it yourself.
ˆ Diversify your field of expertise; sport science is a multidisciplinary
science.
ˆ You will likely be expected to provide support to the performance
and medical staff and even to report to management:
– use clear and simple language to communicate with others.
Adapt your way to communicate to the receiver.
– be concise in your explanations; extend them when re-
quired.
– focus on the practical implications, and on the potential
underlying mechanisms when asked.
– create a reporting system that includes different levels
of communication:
1. key information, concise and straight-to-point
2. comprehensive reports with a deeper level of detail
– build easy-to-digest sources of information for the staff
and players, and more complex when appropriate.
ˆ Develop processes to speed-up data analysis.
ˆ Diversify the sources that you are using to learn: scientific
journals, blogs, podcasts, YouTube channels, or contact experts
in different fields (see Appendix for some recommen-
dations).
ˆ Demonstrate curiosity and be open to explore what is done
in other areas rather than only sport sciences and sport
performance.
ˆ Collaborate with universities, industries and other organisations/clubs
in the same or other sports with common
challenges (5).
CHALLENGE 2: Building trust
The staff of a team is a complex social network in which people
are interacting to achieve common goals (e.g. win a medal or a
championship; improve the position in the standings; develop
players), and in combination with personal interests (e.g. personally
and/or professional growth, personal gratification or
job security, to mention a few). In some contexts, depending
on the department structure, the new sport scientist (or any
new addition) can be seen as a disruptive element, especially
if it involves the redistribution of responsibilities and the dynamics
between staff members. Some people will be pleased
by this new addition, but others may be sceptical and even
reluctant. To maximise how to be seen as a valuable role it
is important to decipher the personality of the staff members
(e.g. motivation, influences, etc.) and how the interactions in
the club/staff are established.
Professional team sports are often composed of different
groups (e.g. sport management, coaching staff, medical staff,
analytics, etc.) and usually each party operates based on its
own internal organisation, led by one or a few members, who
typically are also responsible for the inter-group communication.
We perceive that the role of sport scientist implies interaction
with these different groups; building trust in each of
them requires time, patience, and perseverance.
Depending on how well they understand your role, it can
determine: i) the time you will need to implement your work,
ii) your credibility, and iii) the financial resources and human
power you might need to implement your ideas.
A first step could be to find the time and the way to interact
with each of these groups, to understand their daily
duties, responsibilities and relationships, interactions between
the different groups and other staff members or potential needs
and explain to them what a sport scientist can provide to the
staff. The perception of the sport scientist’s role might hugely
differ between staff members depending on their previous experience.
A second step could be to try to identify allies and
start to work with people who have already successfully collaborated
with such kind of support (6). In an unfavourable
environment, where for example some staff members may have
experienced poor collaboration with a sport scientist in the
past, we will have to look for alternatives to build trust, either
starting from a personal perspective or giving space and
time to earn that professional trust both ways.
Optimising each opportunity to achieve this goal is probably
one of the most important aspects to consider. In this
sense, demonstrating emotional intelligence is key. In elite
sport, credibility and confidence are crucial.
Tips to handle challenge 2
ˆ Understand and respect the work of others.
ˆ Learn from the expertise and experience of others. Share
yours.
ˆ Do your best to be viewed as a resource, not as a constraint.
Ask how you could provide some help or if your work could
complement theirs.
ˆ Identify your best ambassadors in the staff and those who
are less interested or reluctant. Drive projects with the first
ones while remaining ready to collaborate with the others.
ˆ Be empathic with other staff members when you want to
implement something new and adjust your suggestions according
to that. Understanding is the most important step
for communication.
ˆ Accept and support the staff decision, including when they
do not follow your suggestions.
ˆ Work on your patience and tolerance to frustration. The
information that you provide is only one piece of the puzzle!
ˆ Demonstrate emotional stability and keep smiling. Circumstances
are never perfect, but your attitude can be.
ˆ Be fair and reliable, including (especially) in the bad mo-
ments.
ˆ Recognise your mistakes and that sometimes you don’t have
the answer.
ˆ Share your reports quickly, but double check before sending
them!
sportperfsci.com 2 SPSR - 2019 | Mar | 57 | v1
10 challenges for a sport scientist
ˆ Recognise that building trust requires time. Rome was not
built in a day!
CHALLENGE 3: Maximise the athletes’ buy-in
The athletes are the most important piece of the puzzle when
it comes to sports performance. We can have the best facilities,
the latest technology or the coolest wearables but if
the players don’t want to use these resources and we have the
technology in a storage room or gathering dust, that will be
of no help. Also, the program has to fit in the organisation’s
culture; understanding context is critical again.
When it comes to monitoring the players, we have to ensure
that we are able to collect data; the type of data we want
and the type of technology (and which one) we will use for
that purpose will depend on the context and the needs. It
helps to make things easy and comfortable for the athletes,
for example, adopt some strategies like: they don’t even notice
that they are being measured (e.g. tracking loads with
semi-automatic cameras), the process is minimally invasive
(e.g. microsensors), the technology is an integral part of the
equipment (e.g. VBT sensors), the assessment is just part of
the session (e.g. a submaximal running test during a warm
up), or simply, they don’t have to go to a different building to
do an assessment. Making things optional as a starting point
can help too. Also, they have to know that the data belongs
to them: it is their data. Make sure they know why we are
collecting the data, give them feedback, explain to them why
monitoring can help their performance, try to find the right
arguments and deliver them at the right time or try to establish
different channels of communication when you do not
succeed with connecting with some athletes (leave your ego
aside).
Tips to handle challenge 3
ˆ Listen to the players.
ˆ Maximise your emotional intelligence: watch their body
language, be empathic and build strong relationships when
possible.
ˆ Provide individualised information and feedback. One size
does not fit all. Individualise the way you interact with
them according to their personality, needs, interests, etc.,
and target small changes over time, rather than the all-ornothing
approach.
ˆ Create visual reports to facilitate your interactions with
your athletes. Try to make them as eye-catching and easyto-digest
as you can.
ˆ Adopt a positive attitude.
ˆ Be flexible.
CHALLENGE 4: Making good use of the technology
There has been a sharp evolution of technology available in
sports performance over the last decade. Based on both subjective
and objective data collected with multiple tools (e.g.
app, tracking systems, etc.), the sport scientist can now potentially
provide much feedback to the coaches. The staff can
rest a player, give the player more minutes in a training session
or during a game, or modify task constraints during a practice
to achieve certain individual goals for that particular session.
Since there is a plethora of tools to use and a potential multitude
of parameters to track, the best solution is certainly
to start with a question to address. Even if technology has
the potential to revolutionise decision-making, training prescription,
and injury management, it will never directly affect
the outcome by itself. The people on the staff who use the
data will always have that responsibility. For this reason, the
key always remains to address problems that we are facing.
Especially when a sport scientist has just been hired by an
organisation, the temptation can be to ask the organisation
or club to buy new tools in order to show that (s)he is not
left behind in comparison to other organisations, which are
using the same technology or because of a willingness to make
her/his work look sexy and sophisticated. Such a strategy may
be protective in the short-term but is likely to be disastrous
in the mid-to-long-term because time will reveal that such an
investment is not improving the way staff are making their
decisions or helping the athletes to get better. Creating virtual
problems to justify the use of certain technology can turn
against you in the long run.
To make technology your friend, the best option certainly
remains to be highly selective and to invest in solutions that
have high chances of success. To better understand how to
maximise your probabilities of making a good investment, we
encourage the reader to read the Critical Process for the Implementation
of Technology in Sport Organizations (7). As a
summary, it is possible to identify four steps in this process:
1. the identification of the priority problems to solve
2. the search for potential solutions. A potential mistake can
be determining the solution before identifying the performance
problem. Being innovators or early adopters of technology
shouldn’t be incompatible with investigating the
product (e.g. accuracy, reliability, utility, cost: benefit ratio,
accessibility to the data, integration with 3rd parties,
to mention but a few) and the anticipation of all the potential
barriers associated with the implementation of a given
technology in the organisation
3. the identification of suitable innovations
4. proposing some for adoption
As a sport scientist, part of our job is to provide answers
in regard to key performance indicators of the sport, profiling
athletes/players, assessing fitness, readiness to perform and
fatigue, programming and periodization, etc. Having a good
understanding of the context of the problem to solve will be
very helpful when it comes to deciding whether it is worth
measuring (measure what matters!, 8), and how are we going
to measure it and why (9). Technology should help to make
our job more efficient and effective, as well as to support others
in making informed decisions.
Last but not least, the people who are responsible for the
daily implementation and use of the technology have to understand
its benefits, the data (metrics), and how to use it to their
benefit (7). It is critical to provide a constant message across
the staff and the organisation about the technology since, as
we mentioned earlier in this section, the people who use the
data from technology will always have the responsibility of
making decisions.
Tips to handle challenge 4
ˆ Players are the primary focus: technology must be player
friendly.
ˆ Try to identify potential staff problems, observe how people
work, and/or ask them if they have identified problems
that certain technology potentially could help with.
ˆ When you identify a potential solution (technology):
– challenge the sellers, be sceptical about what they are
claiming, ask for independent validation studies to see
how robust their arguments about the technology are,
and ask questions about the validity, the reliability and
the sensibility of the technology. If they don’t have it,
but you think it is still worth giving it a try, do your own
sportperfsci.com 3 SPSR - 2019 | Mar | 57 | v1
10 challenges for a sport scientist
validation studies, and ask them to develop their product
if necessary; there are people willing to make their
product better, and the collaboration between both parties
can be mutually beneficial.
– read the scientific literature that includes this technology
in the study, if available.
– ask feedback from other practitioners using it or that
have used it in the past. “Learn from the mistakes of
others. You can’t live long enough to make them all
yourself” (Eleanor Roosevelt).
– sometimes you can present the technology to your colleagues
before making the decision to buy it, in order
to maximise your chances of getting their buy-in in the
future.
– anticipate the amount of data that this new resource will
generate, and how you will store it, analyse it, include
it in your reports or if you will need to build new ones,
and how you will communicate the information with the
other members of staff.
ˆ We suggest making the best use of the budget; provide arguments
for your decisions and provide feedback about the
job completed using those resources.
ˆ Conduct a survey and identify the current and future
trends. What is available today? If the technology is not
ready yet, is there potential to be better in the short-, midor
long-term?
ˆ Stay up-to-date.
CHALLENGE 5: Handling the data tsunami
“There are things that can be measured. There are things that
are worth measuring. But what can be measured is not always
what is always worth measuring” (10).
As mentioned above, the evolution of more affordable and
accessible technology is intrinsically associated with the explosion
of the quantity of data that can be collected on a daily
basis to monitor workloads, game demands, athletes’ wellness,
fitness levels or recovery, among others. This phenomenon is
common across sports and can potentially revolutionise the
way staff make decisions. Nevertheless, the transition from
data collection to decision-making is a rocky road and sometimes
people are not complete aware of it.
This relatively new scenario makes data handling considerably
challenging, especially when the volume of data and/or
the number of players to monitor is large. The higher the volume
of data, the greater the need to have capacity to filter,
clean, organise, analyse, and present the information.
It can happen that people rush the filtering and cleaning
data processes, which could compromise the final conclusions.
We recommend spending time making sure that the data is
correct and trustworthy (data quality).
If the quantity of data that you are collecting is large, we
suggest building a robust database from the beginning, trying
to minimise missing data, and being able to have a historical
database over time.
We have to keep in mind that although we might work in
a team sport, recommendations are frequently based on individual
needs. Thereby, we should be able to have individual
reports, and not only delivering team reports. Also, the statistical
or data analysis that we might use should have two
levels: i) individual level, ii) group level (team, league, etc.).
It is beyond the scope of this text to discuss statistical analysis
techniques, however, we suggest being open-minded, since
neither classical statistical analysis nor trendy solutions may
always fit your needs.
Remain open to collaborate with data science experts. If
they are doing the analysis, you must ensure that the results
make sense, meaning they are going to provide useful information
for the performance and coaching staff. Using machine
learning algorithms will not do you any service if results can’t
be interpreted and used by the coaches or staff. On the other
hand, remain open to learn about/from these techniques too,
since they might help in the progress of development and in-
novation.
When delivering the information, it must frequently be provided
as soon as possible to the people, so they can adjust their
decisions. For example, there will be cases where the staff or
coaches will need to make a quick decision based on availability
status and it will be critical to edit and share the reports
fast, after each training session or match. If the report is delivered
late, the potential impact will be substantially reduced.
To do so, we might have to have different levels of reports,
one with few metrics (the most relevant information that we
can quickly share), and a more detailed report in which we
can spend more time on its analysis and the interpretation for
those receiving it.
Tips to handle challenge 5
ˆ Measure what matters most and evolve and improve the
process from there.
ˆ Develop your skills using resources that help to make the
data analysis more time-efficient and its presentation effective.
Some examples,
– reports based on spreadsheets
– software or environments based on programming language,
focus on statistical analysis
– platforms for analysis and visual presentation (dashboards),
to make them interactive and easy to share on
different tools (PC, tablets, smartphones).
ˆ Have discussion with the people who will receive the information
and make sure that the reports are easy-to-digest
and eye-catching for them.
ˆ If you have the possibility, ask support from a data scientist
to help you with this challenge.
ˆ Use machine learning to explore your data and try to provide
insights into how to interpret it.
CHALLENGE 6: Keeping things simple
As mentioned above, the more data you collect, the harder
the challenge to keep information straight-to-the point and
easy-to-digest. The phenomena that we want to explore and
better understand as sport scientists are complex and multifaceted
(e.g. fatigue, injury prevention). We stress again that
we provide information to the members of the coaching and
the medical staff to optimise their decision-making, but not
to make the decisions for them, unless a particular decision
is part of our responsibilities. We have to keep in mind that
workloads, as an example, can be our primary concern, but
the medical staff will have other things in mind like an injured
starting player, and the coaches a game to prepare; thus, we
have to reconsider how to simplify the reports and the key
information we shared during both meetings and informal discussions.
Concentrate on the information your audience needs
to know.
sportperfsci.com 4 SPSR - 2019 | Mar | 57 | v1
10 challenges for a sport scientist
Tips to handle challenge 6
ˆ Constantly challenge the reports that you’re sharing with
the staff members: are they using it? If they are not or only
partially, push yourself to try to understand why. Keep
challenging yourself as long as the response is not satisfying.
Finding the optimal option is often a rocky road
requiring setting up a trial-and-error approach.
ˆ Be aware that compiling simple reports can become. . .
complex. To solve this, consider building interactive dashboards
telling a story, rather than rigid reports (11).
ˆ Frequently, less is more. Even if you are collecting a great
amount of data, focus on reporting what is really relevant.
ˆ Keep learning about metrics and potential new metrics,
and about how to you use them in your reports.
ˆ Bullet-points: have 3-4 key points highlighting the main
information you want to share, since some people may not
take the time to read the report in full.
ˆ You can use machine learning to identify the parameters
you should highlight in your reports, without losing too
much information (e.g. principal component analysis, clus-
tering).
ˆ Data communication checklist (for a more complete review,
12):
– The context:
* Who is your audience?
· Narrow your target audience. Create different
communication for different audiences. The more
you know about your audience, the better.
* What do you need them to know or do?
· Live communication: you have more control
· Written communication: you have less control
· Considering how much control you have over how
your audience consumes the information and the
level of the detail needed is important when you
start to generate content.
* Communication mechanism
* Desired tone
– Visualisation: Gestalt principles of visual perception for
data visualisation:
* Proximity
* Similarity
* Enclosure
* Closure
* Continuity
* Connection
CHALLENGE 7: Not putting the cart before the horse
Protocols from scientific studies are often a simplification of
the reality. “Past science tended to look at events as individual
occurrences that seemingly happened in isolation (. . . )
and many times the different fields of science would concentrate
on the event without trying to see how it fit into the bigger
picture. We are still concerned with carefully examining individual
events, but the shift has now become toward making the
whole picture” (13).
In our context, the whole picture would be the equivalent of
the applied world. We have to use research-based principles
when appropriate, but we also should be critical and sceptical
about some literature conclusions we read; be aware that the
context of a scientific study may differ from our environment,
and that evidence-based is not research-based.
Sometimes as young sport scientists recently certificated we
can err on over-confidence: “I’ve studied it; this article confirms
it, so it has to be true; I’m right and we should do it this
way”. But the experience that you accumulate working with
athletes in a professional ecosystem helps you to realise how
complex things can be and that there are always many ways
to approach a given situation. Without detracting from the
importance of studying, reading or applying protocols coming
from scientific research, experience allows you to become
aware of how difficult it sometimes is to apply all your knowledge,
and forces you to frequently reinvent yourself. Today’s
solution may differ from tomorrow’s solution. The complexity
of the problems that we try to apprehend in sport science
should always encourage us to decipher the uniqueness of the
situation that we are facing before formulating any recommendation
(14).
Tips to handle challenge 7
ˆ Keep things simple at the beginning.
ˆ You can save time by learning from others’ experience, especially
from people sharing the mistakes that they have
made in the past.
ˆ You may not have all the answers, and that is fine. Do your
best to try to solve questions, be honest if you can’t right
now, seek assistance or guidance if possible.
ˆ The fact that an article has been published in a high-impact
factor journal does not imply that you can systemically
transfer what you read to your environment. “Content is
king, but context is God” (15).
ˆ We discourage self-promotion, when it is out of place.
ˆ Do not commit to predict things if you are not able to
predict them (16-17).
ˆ Building a methodology of work takes time; be always ready
to challenge your own processes.
ˆ Implement projects with the academy or university, where
we can provide a more controlled environment and try new
things before implementing them with our main athletes or
team.
CHALLENGE 8: Contribute to the vision of the organ-
isation
Building and strengthening a culture driven by sport science in
a club or a federation takes time. When you start from scratch
it is critical to gain the buy-in and trust of the players, the
staff and/or management.
Rather than proclaiming that sport science will be a game
changer, we believe that humility, honesty, hard work, quality
in your job and patience are paramount. Implementing
sport science in elite sport is about how you can contribute to
strengthening your institution with the process of maximising
performance and helping people to optimise their decisionmaking
on a daily basis.
It remains important to be proactive, update different
groups from time to time about what you are doing, which
projects you are working on and the steps you identify that
will keep reinforcing the institution.
Tips to handle challenge 8
ˆ Understand your context.
ˆ Clarify the expectations of the club about your role and
make sure that they fit with what you can bring.
ˆ Embrace the club’s vision and culture.
ˆ Be proactive, defend your ideas with assertiveness, and with
humility.
ˆ When you talk to people without experience or background
in sport science, try to adopt simple and concise explanations,
based on practical cases.
sportperfsci.com 5 SPSR - 2019 | Mar | 57 | v1
10 challenges for a sport scientist
CHALLENGE 9: Managing your pace
The moment you are hired by a professional club or a federation
to support high-level athletes is probably an exciting time
and a tremendous joy. At the highest level only a few positions
are available, so the enthusiasm and motivation for such
a great opportunity are justifiably immense, if/when it becomes
real. Nonetheless, we suggest taking time to check your
priorities, your principles and how you are going to manage
your pace. Having the eagerness to prove to people that they
made the right choice selecting you, to meet their expectations
and to try to provide solutions and answers to their questions
is understandable. Yet, we recommend pacing yourself, by
taking a bit of time to observe and then, when appropriate,
take actionable steps.
It is good practice to help the organisation understand the
importance of having time for fast thinking to solve today’s
needs, and for slow thinking to solve all our needs, investing
time to make the right steps and the right decisions for the
mid- and long-term success (18).
Tips to handle challenge 9
ˆ Make a plan; design a framework for short-, mid- and longterm
goals and how you envisage its implementation.
ˆ Pace yourself; differentiate your doable goals and more
those more challenging.
ˆ Keep in mind what you have already accomplished, to help
you keep a positive attitude.
ˆ Identify your weaknesses and do your best to work on them.
ˆ Consider your errors as opportunities to progress (re-
silience).
ˆ Regulate your expectations and push yourself when you feel
it is the right moment.
ˆ Habits and routines can help.
CHALLENGE 10: Keeping the balance right
In the high-performance environment, it is not uncommon to
work 7 days a week and to spend a lot of time away from
family and friends. This can be especially challenging when
you have kids and you can’t spend as much time as you would
like with them. Your lifestyle is atypical, very often we don’t
have weekends, we might have to keep working when you go
back home, we can’t plan vacations ahead of time, and they
are usually very short!
Managing the balance between an exciting job and your
private life is important, since high-performance sport jobs
are often unstable, unpredictable and emotionally challenging.
Elite sport consists of wins, defeats, joys and deceptions,
that may all occur in short periods of time. Having a social
and personal live outside the work environment and some alternative
projects outside your main job are probably good
ways to strengthen your emotional balance, mental serenity,
your resilience and your chances of success in the long run.
Even if your job is very demanding and even if you feel you
lack time, we recommend having a physically active lifestyle.
There is always a way to find time for exercise: go to work
by cycling, plan gym sessions at lunchtime, take advantage of
the days spent at the hotel when the team is playing away,
or practice sport with your kids. It will benefit your health,
creativity and your productivity at work. Likewise, in some
contexts, there will be low activity periods. Optimise these
opportunities to rest or charge your batteries, since it may be
some time until the next break.
If you have a family, and it’s your priority, consider each
job opportunity as a team project rather than a personal opportunity.
Try to anticipate how your life will look like and
if everybody will benefit from this experience. Sometimes it
may be worth it to take opportunities which at first glance
may not optimal for everybody, but keep in mind that - if it is
the case - it may not be sustainable in the long-term. Always
pay attention to the wellbeing of your family and make it your
priority.
Tips to handle challenge 10
ˆ Keep in mind how lucky you are to work in elite sports.
Putting aside the challenges, remember all the efforts you
have made to get here and that many people would like to
have your job!
ˆ You can be in a strong position in a great institution today
but remember that in elite sport things can change very
quickly. Be aware of this reality and be prepared if you get
sacked, especially if your position is linked to other people
(e.g. a head coach). If you demonstrate strong skills, a
good personality and honesty you will get other opportunities.
Keep believing in yourself.
ˆ Be positive. The toughest moments often represent the
best opportunities to test yourself outside of your comfort
zone.
ˆ Be optimistic. Try to find an opportunity in every diffi-
culty.
ˆ When possible, have a project outside of your job, something
that can help you to be a better professional or a
project with close colleagues/friends who motivate you, and
make it fun!
ˆ Enjoy your breaks, and if possible let your computer and
your smartphone rest during these important moments of
the year!
ˆ Devote time to yourself.
ˆ Exercise regularly.
ˆ Mindfulness may be of interest. Meditation facilitates patience,
self-control and being in the ‘here and now’ (19)
ˆ Have social support: family, friends, mentors. . .
ˆ Put things into perspective.
Conclusions
The challenges that we can face as a sport scientist in a highlevel
sport environment are abundant and diverse. Thus, the
actions needed to tackle them are likely also diverse and may
require a multidimensional approach. We are aware that it is
difficult to cover all the potential challenges you might face,
because every organisation/club/team represents a different
context. We are also aware that we don’t have all the answers
and potential solutions. We wanted to present here some of
those challenges that we consider most common. We do not intend
to provide recipes or a manual on the best way to address
them, we simply wanted to share some of the situations that
we or close colleagues have dealt with, what we have learned
from our experience, how we could manage things better and
helping others who may expect to do a similar job. We believe
that values such as adaptability, hard work and dedication, curiosity,
collaboration and resilience are important to succeed
when you become a sport scientist in a new environment, or
in an institution with no tradition in this field. However, we
encourage you to identify your challenges and share with the
community which tips, values and principles help you to overcome
them and achieve your goals.
Feel free to share your own thoughts by commenting on this
opinion paper directly on Sport Performance and Science Re-
ports.
sportperfsci.com 6 SPSR - 2019 | Mar | 57 | v1
10 challenges for a sport scientist
Twitter: Follow Yann Le Meur @YLMSportScience and
Lorena Torres @Lorenatorres07
Acknowledgments
The authors would like to thank Jo Clubb (@JoClubbSportSci)
for English editing assistance.
References
1. McLean BD, Strack D, Russell J, Coutts AJ. Quantifying
Physical Demands in the National Basketball Association
(NBA): Challenges in Developing Best-Practice Models for
Athlete Care and Performance. Int J Sports Physiol Perform.
2019 Apr;14(4):414-420
2. Buchheit M. Houston, We Still Have a Problem. Int J
Sports Physiol Perform. 2017a Sep;12(8):1111-1114
3. Starling LT, Lambert MI. Monitoring Rugby Players for
Fitness and Fatigue: What Do Coaches Want? Int J Sports
Physiol Perform. 2018 Jul 1;13(6):777-782
4. Coutts AJ. In the age of technology, Occam’s razor still
applies. Int J Sports Physiol Perform. 2014 Sep;9(5):741
5. McGuigan MM, Cormack S, Rowell A. Industry based Postgraduate
Scholarships in High Performance Sport. Sport Perf
Sci Rep. 2018 Mar v1
6. Buchheit M. Outside the Box. Int J Sports Physiol Perform.
2017b Sep;12(8):1001-1002
7. Torres-Ronda L, Schelling X. Critical Process for the Implementation
of Technology in Sport Organizations. Strength
Cond J 2017 Jun, 39(1):54-59
8. Doerr J. Measure what matters. Portfolio; 2018. 320p
9. Sinek S. Start with Why: How Great Leaders Inspire Everyone
to Take Action. 2011, Portfolio. 256p
10. Muller JZ. The Tyranny of Metrics. 2017, Princeton University
Press. 240p
11. Lacome M, Simpson B, Buchheit M. Monitoring training
status with player-tracking technology. Still on the road to
Rome. Aspetar Sport Medicine Journal. 2018 Jun, 7(1):64-66
12. Nussbaumer Knaflic C. Storytelling with Data: A Data
Visualization Guide for Business Professionals. 2015, Wiley.
255p
13. Rutherford A. The Systems Thinker: Essential Thinking
Skills for Solving Problems, Managing Chaos, and Creating
Lasting Solutions in a Complex World. 2018, Kindle.
14. McGuigan MM. Extreme Positions in Sport Science and
the Importance of Context: It Depends? Int J Sports Physiol
Perform. 2016 Oct;11(7):841
15. Buchheit M. Content is king, but context is God. HIIT
Science blog. 2018 [cited 27 March 2019]. Available from
https://hiitscience.com/content-is-king-but-context-is-god/
16. McCall A, Fanchini M, Coutts AJ. Prediction: The
Modern-Day Sport-Science and Sports Medicine ”Quest for
the Holy Grail”. Int J Sports Physiol Perform. 2017
May;12(5):704-706
17. Silver, N. The signal and the Noise: Why So Many Predictions
Fail-but Some Don’t. 2015, Penguin Books. 560p
18. Kahneman D. Thinking Fast and Slow. Farrar, Straus
and Giroux; 2011. 499p
19. Williams M, Penman D. Mindfulness: A Practical Guide
to Finding Peace in a Frantic World. 2011, Piatkus. 288p
Copyright: The articles published on Science Performance and Science
Reports are distributed under the terms of the Creative Commons Attribution
4.0 International License (http://creativecommons.org/licenses/by/4.0/),
which permits unrestricted use, distribution, and reproduction in any medium,
provided you give appropriate credit to the original author(s) and the
source, provide a link to the Creative Commons license, and indicate if
changes were made. The Creative Commons Public Domain Dedication
waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the
data made available in this article, unless otherwise stated.
sportperfsci.com 7 SPSR - 2019 | Mar | 57 | v1