AI Project 07 / 07
AI-Powered Player Recognition and Tactical Tracking System
This project focuses on the design and development of a computer vision system for automated player identification in football match videos.
Overview
About the project
This project focuses on the design and development of a computer vision system for automated player identification in football match videos. Its main objective is to detect and track players, recognize their names and tactical roles using jersey number OCR, and map their trajectories onto a 2D top-down pitch. The platform provides coaches and analysts with an interactive dashboard that overlays player profiles on raw footage while generating precise coordinate logs, addressing key challenges such as visual occlusions, camera pose calibration, and noisy jersey number readings.
Capabilities
Key features
Audience
Who is it for?
FAQ
Frequently asked questions
How does AI recognize football players in video?
The system detects and tracks each player, reads jersey numbers with OCR to identify names and roles, and maps their movements onto a 2D pitch.
What challenges does the system address?
It handles visual occlusions between players, camera pose calibration, and noisy jersey number readings to keep identification reliable.
About the author
Anas Skiti
Licensed football coach in Switzerland and IT professional. This project is part of ScrumSoccer’s research and development in AI-driven football analysis. The ideas behind it are explored in depth in the book Modern Football Intelligence, and coaches can learn the ScrumSoccer method in the ScrumSoccer course.
Interested in this project?
Book a call to discuss a demo, consulting or a research collaboration for your club, academy or organization.
Research & development
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