Sports

Turn match footage into performance insight.

Accelerate your sports technology with high-performance data for coaching and AI-powered analytics.

Applications

ai-refereeing.mp4 Live preview

Trajectory and field-line annotation trains automated refereeing; 2D/3D boxes and segmentation let algorithms capture competitive events precisely.

Annotate broadcast video, multi-camera feeds, and depth data together to capture the whole field.

Pre-label players and the ball, then hold track IDs across long match sequences.

Validation and review catch ID switches and missed events before data reaches training.

Split full-match labeling between annotators and reviewers, with role-based access.

Define custom classes for actions and events, and export to your analytics or ML stack via API.

Keep team and broadcast footage confidential, with on-premise deployment available.

Rectangular boxes that identify and continuously track players, referees, and equipment.

Points that fix the center of fast-moving objects or equipment markers to track trajectory.

Connected keypoints that model an athlete's skeleton for biomechanics analysis, technique assessment, and injury prevention.

Pixel-wise isolation of each athlete for broadcast overlays and player-density analysis.

Lines that mark field boundaries, touchlines, and zones, essential for automated refereeing.

3D boxes that place players and equipment in space so models compute projectile speed and object distances.

A mix of annotation methods built around your specific sports-analytics task.

Book a demo and we'll scope your performance dataset with you.

Custom solution? hello@keylabs.ai