Automated Force-Velocity Profiling of NFL Athletes via High-Frequency Tracking Data

Abstract

The ability to measure key physical parameters of athletes is becoming increasingly critical for today’s sports organizations. Force-velocity profiling is a well-understood and studied technique for measuring the relationship between speed and output force in sport-specific contexts. Accurate force-velocity profiling systems can enable a wide variety of applications for sports organizations to improve player performance, cater better training programs, and potentially reduce injury rates in the long term. A current limitation of many of these systems is that they can require context-specific testing that impacts workflows for players, coaches, and trainers. Given the recent rise of wearable sensor technologies that track player movement in dynamic contexts, there is a clear opportunity to leverage new data streams to enhance this process.

We present a novel system for automated force-velocity profiling using publicly available high-frequency tracking data of NFL players. We demonstrate that our derived force-velocity envelopes match observed position and player performance, and provide a proof of concept framework that would allow teams to leverage automated force-velocity profiling in their internal operations.