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📊⚽ A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.
Three-layer Expected Goals model with Bayesian player calibration, real-time CV pipeline (YOLOv8/RT-DETR + ByteTrack), GNN tactical analysis, and Streamlit dashboard.
Predict Fantasy Premier League (FPL) points using two models: a Random Forest regression (ML_xP.py) and a custom statistical model (xP_FPL.py). This project explores different approaches to predicting player performance, with a detailed comparison for Gameweek 5 of the 2024/25 EPL season.
Goalytics is a modern Python library designed for advanced football analytics, focused on calculating and predicting key performance metrics like xG (Expected Goals), xA (Expected Assists), and xT (Expected Threat).