📊⚽ 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.
- Updated
Oct 9, 2025 - Jupyter Notebook
📊⚽ 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.
⛏⚽ Scrape soccer data from Club Elo, ESPN, FBref, Football-Data.co.uk, FotMob, Sofascore, SoFIFA, Understat and WhoScored.
A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat
Flatiron School Capstone project. Trying to find out how well players' on-field performance metrics can be used to predict their transfer values.
Statball - Football soccer stats analyser from top 5 european leagues with data obtained by web scraping from Fbref and Statsbomb
A Python package for fetching live football/soccer stats from multiple online sources (Sofascore, FBref, Promiedos and others).
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.
A Jupyter Notebook project to scrape detailed football data from FBref, covering various leagues. The repository includes both the data collection process and a final cleaned dataset for immediate use in analysis. Ideal for football data science projects, including xG, passing metrics, and tactical insights.
Scrape and analyze FBREF data with kickR.
⚽ Predict match outcomes in LaLiga using data analysis and machine learning for strategic insights and winning opportunities.
Predicting match eXpected Goals (XG) for Premier League teams
⚽ App Django pour visualiser scores et calendriers des matchs de football obtenus par web scraping. Extraction depuis FBref, ETL personnalisé et stockage SQLite. Focus Premier League, architecture évolutive. 🏆 #Python #Django #WebScraping #FootballData
A scraper that directly gives football(not soccer) data from FBRef website directly to Pandas dataframe. Major teams and leagues supported.
📊 Interactive Tableau dashboard analyzing team-level performance across the top 5 European football leagues using FBref data.
A small plotly dashboard to visualize football stats from FBref
A simple package providing football data
A statistical analysis to summarize the evolution of the goalkeeper in football
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