NFL Uses AI Simulations to Predict Injuries
The NFL is now leveraging AI simulations and digital twins to predict and prevent high-impact player injuries. The system uses physics-based modeling to simulate different scenarios and identify potential risks. These advances in explainable AI and scenario simulation offer a model for how insurance analytics teams can build more auditable and actionable risk models.
- The initiative, officially named the "Digital Athlete," is a joint venture between the NFL and Amazon Web Services (AWS) that formally began in 2019, building upon their existing "Next Gen Stats" partnership. - Data is collected through a multi-faceted system in each stadium, including 38 5K cameras that create 3D virtual skeletons of players, RFID sensors in shoulder pads to track location and speed, and mouthguards with sensors to measure the force and location of head impacts. - The system processes approximately 500 million data points on a weekly basis, a massive increase from the roughly 500 million data points generated by the Next Gen Stats platform over an entire season. - Computer vision algorithms map each player across 29 unique body points 60 times per second, allowing models to detect subtle biomechanical changes like shifts in gait or rotational instability that may indicate fatigue or heightened injury risk. - Beyond individual players, the technology has been used to simulate 10,000 virtual seasons to model the effects of rule changes. This data directly led to the implementation of a new kickoff format and a ban on the hip-drop tackle. - Since the program's full implementation, practice-related lower-extremity strains have dropped by about 14%, and the technology contributed to a 17% decrease in concussions recorded in 2024.
