AI and injuries

One of the most underestimated problem in modern football is not tactics, but player load and preventing injuries.

The congested calendar and high intensity, especially in pressing systems, demand constant sprints, explosive movements, and rapid changes of direction. These actions are the biggest risk factor for muscle injuries, particularly in the hamstrings and adductors.

A clear example is Reece James, who missed 26 matches during the 2024/25 season due to injuries, including two serious hamstring issues. Even in the current season, he is already facing new setbacks and missing games again, which highlights a recurring pattern rather than an isolated case. This is a typical profile of a player exposed to high physical demands in a dynamic role involving frequent sprints and transitions.

This is where AI can change the game physiologically and strategically. Through GPS data and tracking systems, AI can monitor workload, sprint volume, and movement intensity in real time.

For example, if a player exceeds a critical threshold of high-speed actions, the system can flag an increased injury risk before it actually happens.

AI can also suggest concrete solutions such as squad rotation, reduced training load, or even tactical adjustments to minimize physical stress on key players.

In the near future, the most successful teams will not be those with the best tactics, but those who manage load, risk, and physical performance most effectively.