Sports science is the application of scientific principles (e.g. human anatomy, physiology, physics, chemistry and engineering) to exercise and sport. One of the goals of sports science is to help athletes and teams achieve the best possible sporting performance.
Sources that can provide data on an athlete’s performance include video imagery, wearable health monitors and GPS trackers. Coaches and team support staff are often limited in their capacity to analyse this data, and they also risk influencing the analysis through their own experiences and prejudices.
Machine learning provides an objective way to rapidly analyse and make sense of available sports data to help inform coach decision-making and help to reduce bias.
Computer vision systems powered by machine learning can be used in sports science to:
- Analyse sports video footage
- Track how the ball and players move around the court/field.
When combined with deep learning and optimisation techniques, machine learning can be used to:
- More efficiently collate and process data collected from various sensors
- Automatically generate player performance statistics
- Analyse player performance statistics
- Model player interactions
- Develop tactics
- Optimise training regimes.
AIML has worked with Champion Data to develop machine learning techniques to:
- Analyse AFL sports video footage and record detailed information about each player, including their location on the field and their involvement in significant events
- Analyse video footage and track player interactions to develop better tactics.
Connect with AIML to find out how your organisation can benefit from machine learning.