📊⚽ 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.

QY70 (XG level 1) MIDI instruments for Dirtywave M8

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

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

封装腾讯信鸽推送SDK

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.

A repository of sports analytics experiments.

The objective for this task is to demostrate the ability to build ML regression and clasification model and evalute its performance by prediting the required features

Java XG-Editor