Hay un tipo de datos al que no se hace mención y que, en mi opinión, son lo más relevantes en una situación de competición: los datos emocionales, psicológicos. Sin desdeñar la información física y de rendimiento, en paralelo dispondría de una disección en datos del comportamiento mental de los deportistas de mi equipo. De su estabilidad, competitividad, falta de estrés, etc. van a depender muchas de nuestras opciones de victoria.

Study of the kinematics and kinetics from not just a biomechanical perspective but also through the lens of anatomy (design of the body) and motor control (how the brain controls movement). Video analysis, wearable technology, force plates, speed measuring devices (launch monitors, radar guns etc.), electromyography all play a role, but unless the expert involved understands many aspects of kinesiology, and can analyze meaningful aspects of movement, progress cannot be optimal.

An important component of a growth sustaining environment is dedication to significant and continual improvement fueled in part by targeted affirmations. Data analytics can provide powerful performance anchored feedback that can be central in achieving epic positive deviance rather than continually slipping back towards normalcy. It is easy to be ordinary and ignighting extraordinary performance may be fueled by creative utilization of data analytics.

One thing I found helpful is with the help of data analytics one can do SWOT analysis of a team . -To improve player performance the MBO (Management by Objectives) model can be a game changer. -With the help of AI one can do real time performance tracking . - Try to focus on Physical, mental and emotional well being of an individual. -Analyze historical data to maximize scoring opportunities.

Both individual and colective stats should be analyzed. It’s crucial that we have a full understanding of what we want from our team and we should benchmark team stats in order to monitor fluctuations. Different opponents, starting players, venues, and weather can influence team performances and that should be taken into consideration when doing our analysis. Data should be used to look for hints that can direct us to the problem in our performances. This information should then be confirmed with video and only objective conclusions should be brought to discussion with the players. Individual stats tend to have more fluctuations between matches and we should not precipitate into conclusions based on data with small prevalence.

By analyzing data from previous matches, we have identified trends in our opponents’ play, helping players make tactical adjustments. An example of these trends would be spotting a specific player’s tendencies and exploiting areas of qualitative or positional superiority on the field. Additionally, we have used visual tools like heat maps to show where our players spend their time, helping them to identify tendencies or areas for improvement.

First you better review all the things needed to win. Without a computer and science. Can I trust you Do you care Do you have a desire to be great Are you committed to excellence How do you treat your teammates Is there confidence Are willing to play for your teammate What’s your commitment to win away from the team and on off days. Are you on time Are you durable Then you can buy the computer and do analytics. However, the science that MIT is using with Texas A&M in strength and conditioning is the best out there period. Have used all the gps, load count, etc etc as first to do it at fsu in 2010.

Data analytics has been a game changer for my approach in sports. It provides a clear picture of each player’s strengths and weaknesses, allowing for targeted improvement. Video analysis helps break down complex plays and fine-tune strategies, while wearables give real-time data on fitness levels, helping to prevent injuries and optimize performance. Overall, it’s helped us make more informed decisions, boosting both individual and team performance. I can't imagine managing a team without it now!