About This Project
The Soccer Analytics Textbook is a free, open-source educational resource dedicated to teaching football analytics using R and Python.
Our Mission
We believe that understanding football through data should be accessible to everyone. Whether you're an aspiring club analyst, a passionate fan, or a data scientist curious about sports analytics, this textbook provides the knowledge and skills you need to analyze the beautiful game.
What You'll Learn
Foundations
Data wrangling, visualization, and working with football data sources like StatsBomb, FBref, and Understat.
Expected Goals
Deep dive into xG, xA, xGChain, xGBuildup, and how to build your own expected goals models.
Machine Learning
Player similarity models, match prediction, recruitment optimization, and neural networks for football.
Career Skills
Industry-standard methods, portfolio building, and career guidance for breaking into football analytics.
Why Free & Open Source?
Football analytics education shouldn't be locked behind paywalls. The democratization of football data (thanks to providers like StatsBomb) has opened up incredible opportunities for learning and research.
By making this textbook free and open source, we hope to:
- Lower the barrier to entry for aspiring analysts
- Provide a comprehensive, structured curriculum
- Enable contributions and improvements from the community
- Support the growth of football analytics worldwide
The Curriculum
Our textbook covers 60 chapters organized into 8 parts, with 900+ code examples and 55+ exercises.
| Part | Topics | Chapters |
|---|---|---|
| I. Foundations | Setup, Data Wrangling, Visualization | 1-5 |
| II. Core Analytics | xG, Passing, Defending, Set Pieces | 6-12 |
| III. Positional | GK, Defenders, Midfielders, Forwards | 13-20 |
| IV. Advanced | Tracking Data, ML, Custom Metrics | 21-30 |
| V. Tactical | Formations, Team Style, Match Analysis | 31-40 |
| VI. Recruitment | Scouting, Transfers, Youth Development | 41-48 |
| VII. Business | Fantasy, Betting, Broadcasting, Careers | 49-55 |
| VIII. Specialized | Historical, Regional, Future Trends | 56-60 |
Acknowledgments
This project wouldn't be possible without the incredible work of the football analytics community. Special thanks to:
- StatsBomb for their open data initiative
- FBref / Sports Reference for comprehensive statistics
- The developers of mplsoccer, worldfootballR, and other open-source tools
- The countless analysts, researchers, and content creators who share their knowledge freely
Get Involved
This textbook is a living document that grows and improves over time. Here's how you can contribute:
Contribute Code
Submit pull requests for improvements, fixes, or new content.
Report Issues
Found an error or bug? Let us know through GitHub issues.
Share
Help spread the word to fellow football enthusiasts.