In the world of football, evaluating the performance of offensive players and the rushers who tackle them can prove challenging, even for seasoned experts. Player reactions unfold in fractions of a second, and their performance in these lightning-fast exchanges is difficult to track, let alone quantify. Metrics such as how close a defender came to the offensive lineup can offer coaches insights into the strength of their plays.
The NFL collects data for these AI-driven processing tools using proprietary field-installed equipment. In each NFL venue, an array of 20-30 ultra-wideband receivers are embedded in the field, while radio-frequency identification (RFID) tags are affixed to players’ shoulder pads and other game equipment, including balls and goalposts. These data transmitters capture information relayed in real-time through a graphic neural network model (GNN). AI then transforms this data into meaningful insights.
These insights manifest as interactive graphics on the Next Gen Stat game landing page. Users can access detailed breakdowns of individual player movements in any given game using 2D models and graphs. For example, they can track the trajectories of players and the ball during a 40-yard passing play in a game between the San Francisco 49ers and the New York Giants on September 21.
