Learn to Code with Soccer

Soccer provides the data; Python provides the tools to ask better questions of it. In Learn to Code with Soccer, Nathan Braun uses the sport as a practical thread through programming, data analysis, and statistics, connecting technical concepts to examples that are easier to picture than abstract exercises alone.

Availability note: The author’s current website offers the book at no cost. This page describes the publication; it does not imply that Digital Delights is authorized to resell or distribute the author’s file.

Follow the data from raw numbers to insight

The book starts with tooling and an introduction to data analysis, then builds through Python and Pandas before turning to SQL, web scraping, and APIs. That progression gives readers a route from handling information to finding, combining, and examining it.

Learn through soccer-focused examples ⚽

Examples named in the contents include world-football data, the Fantasy Premier League API, and shot charts. Using a familiar sport as the setting helps anchor topics such as filtering, joining datasets, visualization, and statistical modeling in concrete questions about the game.

Explore analysis, visualization, and models

Later chapters cover charts made with Python and Seaborn, relationships between variables, regression, classification trees, and random forests. The book also includes end-of-chapter exercises, appendices on data sources and software setup, and an Anki section.

Who may find it useful?

This title is relevant to readers who want to learn Python or develop data-analysis skills using soccer statistics as their subject. Its contents also make it a fit for soccer fans curious about how data can be collected, organized, visualized, and analyzed.