The job of a coach is to make decisions. It is choosing the best players at all times, preparing them well, and being able to manage the best way to play,  to be successful. In order to complete this task, coaches are receiving more and more help and the field of science has started to take part in the decisions that are taken in the game. When finishing a training session or a match, players provide to the technical staff with data of all kinds. If they have used a GPS device, they will know what distance each player has covered during the session, at what speed, how frequently the technical-practical actions have taken place, the accelerations and decelerations, etc. If the club a sophisticated software, it will be able to collect the number of passes, throwings, the distance between players, each player’s heat map, etc. It is even possible to talk with the player about his perception of the effort exerted (fatigue) or his mood. All this data can help us make better decisions and that is why we are so interested to have this information.

However, in order for these reports to be really useful for the coaches and for the sports data scientist to fully bring in his expertise to the team, there are several conditions that should be fulfilled. In a recent work¹, Martin Buchheit suggests three aspects to manage when creating reports for the coaches:

1- Having an adequate level of comprehension of the data and their analysis. It is about keeping in mind:

• Selecting the most relevant indicators, variables, and statistics to help coaches to make decisions.
• Technology is not a solution per se for problems. The questions must be well oriented from the pitch POV.
• Validity, reliability, and usefulness of the data to answer the coaches’ questions must be valued rigorously.
• Apart from the p values, it is advisable to incorporate the size of the effect in the data analysis. When you are working with a relatively small number of observations or players and you cannot control many variables that can be influencing what is happening, the interpretation of data with a traditional statistical approach can be very difficult.

2- The report must be attractive and informative, with a good visual representation of the data. You must pay attention to:

• The reports must be as simple and informative as possible. For that to occur we need to highlight outstanding aspects or meaningful differences so it can be understood quickly, including error bars wherever it is possible for uncertainty. The effectiveness will rely on designing abilities and a creative mindset to acknowledge scientific knowledge.
• The tone and message must be aligned to the coaches and players preferences and habits. You have to pay attention in order to know when to use more or less visual information for reports, quantitative or qualitative interpretations or different kinds of figures or tables.
• You must take into account the feedback from previous reports to find the ideal strategy for the presentation of future reports.

3- Having adequate communication skills to deliver efficiently data and reports to coaches and players.
A strong personality is often a must to survive professionally, but having an open mind, being humble and empathetic, are some important aspects to thrive in this job.

Carlos Lago Peñas

References:

¹ Buchheit, M. (2017). Want to see my report, coach? Aspetar Sports Medicine Journal. 6: 36-43.