📊⚽ 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.

An extendable Statsbomb API wrapper for data-pipelines

Statball - Football soccer stats analyser from top 5 european leagues with data obtained by web scraping from Fbref and Statsbomb

Code and Shiny App to Generate "Entries into Final 3rd" Soccer viz. (StatsBomb event data).

Player and Team analysis using Machine Learning models with useful charts to help GMs and Coaches on decision-making situations ⚽️

The top teams in the English Premier League in the 2021-22 season, Manchester City and Liverpool FC, have gone ahead during this off season to add classic NO.9s to their already stellar attack options. Let's see how these two player stack up against each order using radar plot. Data source is FBref via Statsbomb.

Final Ironhack project: an analysis of the Lionel Messi era at Barcelona - Analysis of Messi's season-by-season output / Using regression to predict Messi's future output / Using Machine learning to predict if a shot will result in a goal or not.

A football analytics tool to analyse statsbomb data and predict xG for FA Women's Super League

A short tutorial on football analytics that demonstrates how to extract and visualise deep completions.

2018 World Cup prediction and visualization project that uses Statsbomb data and Streamlit.

Data Analysis in football Projects

A match analysis suite designed to automate performance analysis in soccer, using StatsBomb data.

Building xG and xGOT based on Statsbomb World Cup 2022 Open Data

Collection of football projects and analysis of teams and individual players utilising Python, SQL and Statsbomb publicly available data.

Classification model for expected goals (xG) in women's club soccer, predicting the likelihood that a shot will score using data extracted from StatsBomb.

Simple functions for plotting relevant informations.