sanjeevnara7/FootballPassPrediction
Football/Soccer Pass Receiver Prediction using Object Detection/Graph Neural Networks (GNNs)
This project helps sports analysts, coaches, and scouts understand player movement and passing strategies by predicting who an attacking player will pass to next in a soccer game. It takes broadcast footage frames as input and identifies players, their teams, and the ball, then outputs the most probable pass receiver. The primary users are professionals involved in soccer analytics and tactical planning.
No commits in the last 6 months.
Use this if you need to analyze soccer game footage to predict potential pass receivers for tactical analysis or performance evaluation.
Not ideal if you need a real-time solution for live game analysis, as this system is designed for processing short, pre-recorded video clips.
Stars
39
Forks
3
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Apr 30, 2024
Commits (30d)
0
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