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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.

Searchable football data provider documentation for AI coding agents. Like Context7 for football data.

Football data analytics toolkit for Claude Code. Covers Opta, StatsBomb, Wyscout, SportMonks, and free sources.

QY70 (XG level 1) MIDI instruments for Dirtywave M8

Global Football (Soccer) Dataset: 367K+ matches, 102 leagues, 182K players, 10M appearances (2012-2026). CSV & Parquet.

Machine Learning models to predict goals in football games.

Several datasets are manipulated, visualized, and analyzed with well-known ML Algorithms to make predictions, clustering, or classifications.

AI-powered football prediction engine using probabilistic modeling, Poisson goal simulation, and tactical analysis inspired by Opta & FiveThirtyEight. Built for World Cup 2026 match forecasting, simulation, and analytics.

General MIDI instrument names: MIDI to string / string to MIDI

Pipeline that ingests football match/event data from the InStat API into PostgreSQL and trains a RandomForest expected-goals (xG) model.

Full-stack football match analysis platform. Search any team, scrape live event data from WhoScored, and generate a interactive shot maps, pass networks, zone entries, defensive actions & advanced metrics.

Production-grade football analytics API — VAEP, xT, XGBoost predictions, Claude AI scouting reports, WebSocket live updates, 472 tests passing

⚽ Système d'analyse de matchs de football en Python (POO) — Calcule VAEP, xG, xT à partir de données réelles StatsBomb (FUS Rabat vs FAR). Héritage · Polymorphisme · Encapsulation

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.

封装腾讯信鸽推送SDK

A structured knowledge hub explaining football statistics, performance metrics, match data, and analytical concepts.

StatsBomb açık verisiyle eğitilmiş canlı xG (Expected Goals) tahmin motoru — XGBoost + Streamlit + Gemini Flash, GCP'de serve edilen uçtan uca MLOps projesi. - Live Expected Goals (xG) prediction engine on StatsBomb open data — XGBoost + Streamlit + Gemini Flash, an end-to-end MLOps project served on GCP.

Three-layer Expected Goals model with Bayesian player calibration, real-time CV pipeline (YOLOv8/RT-DETR + ByteTrack), GNN tactical analysis, and Streamlit dashboard.

Java XG-Editor