FightLens

FightLens is an app that helps viewers understand what is happening in boxing and MMA, and why the balance of a fight is changing. It brings fighter tracking, exchange analysis, and win-probability estimates into one interface, with corresponding video moments viewers can revisit to inspect the evidence. Our event-driven pipeline separates fast action detection, contextual video understanding, and decision updates. YOLO acts as an always-on sentinel, tracking fighters and flagging potential attacks. When an exchange is detected, NVIDIA Cosmos receives a clip with context before and after the trigger to interpret the action and generate an explanation. This design aims to reduce redundant video-model calls without missing brief exchanges. VAST Data organizes video features, real-time events, and related data into shared context for prediction. The Jev architecture with clef-flash supports rapid updates to the estimated advantage. Each exchange, explanation, and probability update is linked so viewers can follow the reasoning. The displayed probabilities are prototype estimates, not yet validated or calibrated. Next, we plan to use historical fight videos to evaluate and improve the workflow, measuring end-to-end latency and prediction quality separately. Our team combines boxing experience, AI research, and product development to make combat sports easier to follow.