Soccer Analytics with Machine Learning

Preface

Soccer has always been a game driven by passion, intuition, and endless debate. For decades, it has been the world’s most watched and discussed sport, supported by the largest global fan base on the planet. Fans love it not only for its results, but for the stories, emotions, memories, and moments of uncertainty—or what we sometimes call miracles—that it creates.

In recent years, this traditional way of enjoying soccer has been joined by something new: data. Advances in artificial intelligence (AI) and machine learning, combined with the growing availability of high-quality sports data and modern computing infrastructure, have made rigorous analysis accessible far beyond professional clubs and research labs. Today, fans and practitioners alike can explore tactics, evaluate performance, and make predictions—sometimes out of curiosity, sometimes for strategic insight, and sometimes as part of casual, responsible betting. With these tools, independent analysis is no longer limited to professionals.

What excites us most about this shift is not only the technology itself but also what it enables. Data-driven methods encourage clearer thinking, more disciplined reasoning, and a deeper appreciation of soccer’s complexity. They do not replace passion or intuition; they sharpen them.

This book sits at the intersection of two fast-moving worlds: soccer and machine learning. Soccer provides rich, imperfect, and fascinating data; machine learning offers principled ways to engage with ...