Athlete Load and Fatigue Forecasting

This application area focuses on predicting athletes’ internal load and fatigue responses—such as perceived exertion and heart rate variability—based on their training and match workloads. Instead of relying solely on after‑the‑fact, subjective measures, teams use historical and real‑time data (GPS, accelerations, minutes played, drills, intensity metrics) to forecast how taxing a given session or match will be on each player. The models provide individualized projections of perceived exertion, fatigue, and short‑term recovery, often with explainable outputs so coaches can see which aspects of load are driving the response. This matters because poor load management is a major driver of overtraining, soft‑tissue injuries, under‑recovery, and performance volatility. By forecasting internal load and fatigue, practitioners can proactively adjust training plans, rotations, and recovery protocols to keep players in an optimal performance and health window. The same tools also help justify decisions to athletes and management by grounding them in data, improving trust and adoption of sports science recommendations.