The role of Sport Scientist
Physical load monitoring has advance significantly during the last century (1). Sport is become more demanding and it is more difficult to win. There is a need of keeping a good physical capacity of athletes to withstand the high competition demands: both improve performance and decrease the injury risk. The position of Sport Scientist (SS) is becoming more required to supply the work of technical staff (coaches and S&C Coaches) in the field through the load analysis provided by players. Thus, the role of SS involves the analysis of internal- and external load parameters throughout different tests and monitoring methods and tools and compare and interpret the results with the research to provide coach a detailed report of athletes’ physical performance. However, there are several doubts about how the training load may affect the physical performance of high-level athletes.
It should be noted that the main objective of SS is to provide a detailed and practical report interpreting the athletes’ physical performance taking into account the scientist literature so the coach can easily use and solve his doubts. Therefore, the provided information should be clear and summarized, avoiding long and tedious reports and adapted to the coach requirements: digital vs paper format, quantitative vs qualitative, tables or graphs, among others.
3 most important step to make an adequate report (2)
- Appropriate analysis and understanding of data. Using the right variables and statistical tests. They have to be useful to answer the questions that are asked by coaches.
- Provide attractive reports through a good presentation and visualization: creativity (using colors, diagrams, tables, etc).
- Good communication skills and attitude to efficiently deliver the reports to coaches (this is the most important point for the author).
The SS must provide ‘good knowledge’ to assess the performance of athletes, the competition plan and load monitoring (3). It is useful to compare the obtained data with current scientific knowledge. However, the SS must develop intervention strategies that facilitate the S&C coaches work. It should be noted that they can never have access to all the information relevant to a given problem. Therefore, the decision making should be based on a practical and flexible interpretation of data; either quantitatively and qualitatively.
The decision making in load monitoring: ‘Green, amber or red light?’
Knowing the physical state of players to withstand the competition demands showing their ‘level’ of readiness simulating the lights of traffic-lights (4) might be a good way to assess the physical capacity of athletes and how they are assimilating the load providing coaches an easier way to take decisions relative to the possible risks to assume for using a determinate player in competition or reprogramming the training load. Thus, the physical performance and injury risk relationship should be added and, logically, individualized. The main goal of the traffic-light system is providing coaches a ‘visual’ and rapidly interpreted method to facilitate the decision making.
Interpretation of the traffic lights for decision making (Figure 2):
- GREEN: things should continue as per normal.
- AMBER: suggests caution. It may suppose a risk if left unattended.
- RED: alarm. Action is required.
This evaluation method of traffic light might be differentiated depending of what it wants to evaluate: physical performance or injury risks; using parameters or variables that can be adapted to the specific objective. Nonetheless, the final purpose is knowing what players are ready to compete (green light). Therefore, I personally consider that this relationship should include both a good fitness of player and low risk of injury. On the other hand, the differentiation by colors might be used to assess anything more visual and easier.
What coaches need from Sport Scientist (1):
- A way to evaluate athlete potential
- A way to evaluate an athlete’s current status
- A way to evaluate how an athlete is responding to a training program
- A way to measure progress, that is translatable into performance
Foster (1) highlight the subjective perception of effort provided by players due to the large correlation between internal and external load (2).
Statistical analysis
The statistical analysis or tests performed by SS will vary depending of what they want to calculate. It is logically understood that the results must be reliable and valid, in addition to practical application for training programming.
Traditional null hypothesis significance testing (NHST) based on p-values has always been used. However, the author considers it an inappropriate test for this kind of sample due to the low number of players into the team and to answer the questions that arise from the field. The magnitude-based inference (MBI) is an innovate and relevant method which facilitates his clinical interpretation.
The MBI proposed by Batterham (5) is based on two simple concepts:
- Changes/differences in any variable are systematically compared to a typical threshold representative of a smallest important or meaningful change.
- Not all changes are worthwhile. Is the change longer than the SWC? How many times greater? Small, moderate, large or very large. (SWC: small-worthwhile change)
- Instead of a classic ‘yes or no’ type response (NHST), the probabilities for these changes/differences to be ‘real’ (greater than the SWC) are reported.
- More precisely: both quantitatively and qualitatively changes.
- The percentage change and associated qualitative interpretations are generally set a priori: <1% (almost certainly not); 1-5% (very unlikely); 5-25% (probably not); 25-75% (possible); 75-95% (likely); 95-99 (very likely); >99% (almost certain).
- Final decisions can be translated into plain language when chatting with coaches
The duties of Sport Scientist (1–4):
- Reports:
- Simple and precise.
- Horizontal text.
- Remove extra decimals and ‘noise’.
- Images better than written text: VISUAL.
- Use different colors (fast and better interpretation).
- Highlight the main results.
- Add plots and tables.
- Selection of appropriate variables and metrics.
- Summarize the data.
- The results must answer the questions of coaches and adapting to their needs.
- Develop a database.
- Improve the integration of different multidisciplinary areas.
- Support the results with scientist knowledge.
Conclusions
The role of SS is still not fully established in sport, even in top-level. Although it may seem illogical due to the high number of tools and methods for load monitoring and management, in addition to the high demands in high-level, there is controversy regarding the SS’ tasks and despite of this role is well established in many staffs and there is an increasing number of clubs which are incorporating this role into the staff, I personally believe that there is still a long way to go as practitioners (in the field) work still far away from sport scientists possibly due to an inadequate analysis and management of data.
As aforementioned, the data must be interpreted and adapted to answer the questions of coaches and provide practical application before delivery to facilitate the work of practitioners and therefore focus on practice. So, SS should not only be limited to analyse the workload and deliver a excel sheet with multitude of ‘raw’ data to coaches and S&C coaches so that they have to find out the adequate load and why. The SS should interpret the data, take decisions and deliver precise and easily and fast understood reports adapted to the specific requirements from technical staff.
As we can see in Figure 2 retrieved from Robertson (4), using different colors simulating the traffic lights according to the level of readiness of player may be an easy and precise method. Foster (1) concludes that currently the great number of evaluation and monitoring tools may be a problem for coaches as the cannot manage all of them, so it is of paramount importance to summarize the data. ‘More is not better’.
Finally, creating an area of investigation and development (I+D) within the clubs can be very useful to improve and progress the analysis of specific physical or technical-tactical performance.
References
- Foster C, Rodriguez-Marroyo JA, de Koning JJ. Monitoring Training Loads: The Past, the Present, and the Future. Int J Sports Physiol Perform. 2017; 1–24.
- Buchheit M. Want to see my report coach? Sports science reporting in the realworld. Aspetar Sport Med J. 2017; 6: 36–43.
- Robertson S. Man & machine: Adaptive tools for the contemporary performance analyst. J Sports Sci. 2020; 00(00): 1–9.
- Robertson S, Bartlett JD, Gastin PB. Red, Amber, or Green? Athlete Monitoring in Team Sport: The Need for Decision-Support Systems. Int J Sports Physiol Perform. 2017; 12(Suppl 2): S2-73-S2-79.
- Batterham AM, Hopkins WG. Making Meaningful Inferences About Magnitudes. Int J Sports Physiol Perform. 2006; 1(1): 50–7.
Berni Guerrero-Calderón
S&C Coach | Rehab Therapist | Sport Scientist
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This article has been made based on the references showed, other studies reviewed but not showed and according to the experience and knowledge of the author. In this way, it may include subjective ideas and opinions not contrasted in the research.
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