fbref

📊⚽ 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, Sofascore, SoFIFA, Understat and WhoScored.

A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat

The football entity register. Maps player, team, and coach identities across Transfermarkt, FBref, UEFA, Sofascore, and 25+ data providers.

A Python package for fetching live football/soccer stats from multiple online sources (Sofascore, FBref, Promiedos and others).

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

⛏⚽ Scrape soccer data from FBref.

Scrape and analyze FBREF data with kickR.

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.

Scraping FBref data and merging it into one CSV file

Football data scraper for fbref.com — extracts match reports, player, club and league stats (standings, fixtures, leaderboards) as JSON using a real Chrome browser.

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

Tactical football analysis platform: team S&W reports, heatmaps, pressing maps, player-role fit, and LLM-generated coaching insights. Powered by FBref, StatsBomb and Understat.

Player power score model across the Top 5 European leagues (2017–2024) — EDA, position-based scoring pipeline, and team analysis. WIP.

A scraper that directly gives football(not soccer) data from FBRef website directly to Pandas dataframe. Major teams and leagues supported.

End-to-end automated data pipeline extracting, transforming and loading Premier League statistics from FBref and Understat into PostgreSQL, with analytical insights on Arsenal FC across 5 seasons of Mikel Arteta's tenure. Built as a data engineering portfolio project.

A simple package providing football data