📊⚽ 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

Java XG-Editor

This repository contains a project developed in R aimed at creating a new model for evaluating Expected Goals (xG) in football.

A repository of sports analytics experiments.

NutriSight is a website which utilizes machine learning and image processing to analyze and detect the stage of Diabetic Retinopathy from the Eye fundus images of the user. Based on severity of the condition, it analyzes restaurant menu through online web-scraping and recommends the most diabeties friendly dishes suitable for the user.

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

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).

Interactive Premier League analytics dashboard built with Streamlit. Compare team performance, xG trends, attacking/defensive metrics, and more.

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.

Developed a predictive model for the Golden State Warriors to estimate optimal ticket purchase timing for individual customers. Utilized Python, scikit-learn, and time-series modeling techniques to enhance sales forecasting and marketing efficiency.