PSV Becomes First Dutch Football Club to Use AI for Injury Prevention
Eindhoven, Wednesday, 14 January 2026.
PSV Eindhoven has partnered with Philips to implement groundbreaking AI technology that predicts player injuries before symptoms appear. The system uses wearables to detect early signs of respiratory infections and overexertion, analyzing data through Philips’ RATE algorithm to forecast health risks up to two days before players feel unwell. This innovation allows coaches to adjust training schedules and medical staff to intervene proactively, potentially preventing both individual injuries and team-wide infections that could sideline multiple players during crucial matches.
The Technology Behind Predictive Health Monitoring
The artificial intelligence system at the heart of this collaboration is Philips’ Rapid Analysis of Thread Exposure (RATE) algorithm, which specializes in early recognition of health issues [1]. The technology utilizes wearable devices to measure early signals of respiratory infections in players, providing data that feeds into predictive models [1]. What makes this approach particularly valuable is its ability to detect potential health threats up to two days before players experience any symptoms, a crucial window since virus transmission can occur during this asymptomatic period [1].
Strategic Implementation and Team Benefits
PSV’s technical director Earnest Stewart emphasized the importance of this proactive approach, stating that preparation is everything and that when a player is not ready, both individual and team performance suffer [7]. The system allows coaching staff to make informed decisions about training schedules, potentially adjusting intensity or duration to prevent overexertion before it becomes problematic [1]. Medical staff can also initiate earlier health checks for players showing concerning data patterns, creating multiple layers of preventive care.
Broader Impact on Sports Medicine and Performance
Philips characterizes the fight against often invisible infections as being at least as important as the battle against opponents on the field [1]. This perspective highlights a significant shift in how professional sports organizations approach athlete health management. The AI system can potentially prevent not only individual player health issues but also team-wide infections that could sideline multiple players simultaneously during critical periods of the season [1]. Such comprehensive health monitoring represents a new frontier in sports science, where data-driven insights enable more sophisticated approaches to maintaining team fitness and availability.