📊⚽ 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

A repository of sports analytics experiments.

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.

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