DEVELOPMENT OF A REAL-TIME AUTOMATED WRESTLING MATCH ANALYSIS SYSTEM BASED ON YOLO26X-POSE AND ATHLETE RE-IDENTIFICATION

Abstract

. In this work a real-time wrestling match analysis system built on the YOLO26x-Pose detector is described. The system runs four modules in sequence: two-dimensional pose estimation for both wrestlers; appearance-based re-identification (ReID) using MobileNetV3-Small embeddings with Hungarian assignment and three-speed exponential moving average (EMA) updates; a heuristic finite-state machine (FSM) that assigns one of five match states: SEPARATION, CLINCH, TAKEDOWN_ATTEMPT, PAR_TERRE, DANGER from skeletal geometry; and a homography-based top-down minimap. The ReID module includes an entanglement-aware EMA freeze, anchor-drift protection, per-zone passivity timing, and per-frame CSV logging. On a standard GPU, without any wearable sensors, the system achieves a mean Identity Preservation Rate (IPR) of 90.1%, FSM accuracy of 85.0%, and 27.7 FPS throughput.