Basket-Analytics/BasketTracking
Basketball 🏀 action tracking and understanding using classical computer vision approaches and deep learning.
This project helps basketball coaches and analysts automatically track player movements and ball possession from game videos. It takes raw basketball game footage as input and outputs rectified player trajectories on a standard court, indicating who has the ball. Coaches, sports statisticians, and tactical analysts can use this to review game performance and optimize team strategies.
No commits in the last 6 months.
Use this if you need an automated way to analyze basketball game footage for player tracking and ball possession to inform tactical decisions or statistical analysis.
Not ideal if you require extremely high-performance, production-ready tracking with guaranteed accuracy for official statistics, as some components were developed with basic computer vision techniques.
Stars
72
Forks
19
Language
Python
License
MIT
Category
Last pushed
Oct 23, 2023
Commits (30d)
0
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