wTVision: Broadcast-grade AI systems for global sports events

Context

Modern sports broadcasting demands real-time analytics, visually rich graphics, and operational reliability under strict live-production constraints. Systems must work across diverse stadium conditions, integrate seamlessly with broadcast graphics pipelines, and scale across tournaments with tight setup timelines and limited on-ground infrastructure.

What we built

• Real-time 3D player tracking systems for live cricket broadcasts using fixed and terrace-mounted cameras.
• Computer vision pipelines optimized for low-latency, broadcast-safe deployment on constrained hardware.
• CricStats: a unified platform for live scoring, statistics ingestion, and graphics delivery to broadcast systems.
• Annotation and dataset-generation workflows supporting large-scale model training and continuous improvement.
• Operational tooling to support repeated deployments across tournaments with minimal setup overhead.
• Broadcast-ready integrations ensuring analytics outputs were reliable, explainable, and safe for live on-air use.

Outcomes

• Successfully deployed AI-driven broadcast systems across major international tournaments including ICC events, Asia Cup, IPL, and domestic leagues.
• Enabled consistent, real-time player analytics and graphics during live matches.
• Reduced operational complexity and setup time compared to traditional camera-heavy or sensor-based approaches.
• Delivered measurable operational savings through centralized tooling and repeatable broadcast workflows.
• Proved reliability of AI systems in high-pressure, live broadcast environments.