📊Edd Webster(@eddwebster)的足球分析项目、数据和分析的集合,包括足球分析社区发布的公开可用资源的精选列表。

fbref 开源项目推荐(45 个)
fbref 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 45 个仓库搜索来自Club Elo、ESPN、FBref、Football-Data.co.uk、Sofascore、SoFIFA、Understat和WhoScored的足球数据。
一个用于从FBref、Transfermark、Understat提取世界足球(足球)数据的包装器
足球实体注册。在Transfermarkt、FBref、UEFA、Sofascore和25+数据提供商中绘制球员、球队和教练身份的地图。
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.
A simple package providing football data
Predicting match eXpected Goals (XG) for Premier League teams
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.
⚽ 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
Sofascore Scraper gets you Sofascore data ⚡ fast, 🎯 100% accurate and 🔍 ridiculously detailed — as clean JSON. 1,000 free calls/month ❤️
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.
📊 Interactive Tableau dashboard analyzing team-level performance across the top 5 European football leagues using FBref data.
A machine learning pipeline that predicts UEFA Champions League and Big-5 domestic league match outcomes (Home / Draw / Away), built end-to-end from raw web scraping through a trained, evaluated, and served prediction model.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/fbref。
- 该话题在 GitHub 上共有 45 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 5930 Star,覆盖 5 种主要语言,数据更新于 2026-11-07。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。