NFL Big Data Bowl

The NFL wants to reduce the risk of non-contact injury to professional athletes. This analysis statistically evaluates the influence of playing surface on non-contact injury risk using hypothesis testing and logistic regression. Geospatial data was recorded every 0.1 seconds (10 Hz) for different positional players across 267,000+ plays and modeled in GCP. New metrics quantifying injury risk were developed and a resnet-50 computer vision neural network was utilized to classify movements for a stratified analysis. The combination of statistical hypothesis testing, logistic regression, and deep learning enabled a stratified analysis that identified surface-related risk factors and produced actionable metrics for reducing non-contact injury.