Roboflow Sports is a sports video analysis system that combines object detection and tracking with bird's-eye field visualization. Its core pipeline detects and tracks players, referees, and balls across video frames, then maps those tracked positions onto a radar-style overhead view of the playing field.
The system goes beyond basic detection by localizing field boundaries and key landmarks such as pitch lines and corners, enabling spatial mapping of player positions relative to the field geometry. It classifies detected players by team affiliation through visual feature extraction and clustering, and maintains consistent identities across frames using motion prediction and re-identification to handle occlusions. Semantic segmentation of playing surfaces further supports tactical and spatial analysis.
These capabilities are built on one-stage object detection, keypoint regression networks, homography-based view projection, and unsupervised feature clustering—all provided as a configurable Python library for sports analytics workflows.
