Net Gains is probably the most comprehensive book on soccer analytics. The author has played Division I soccer in the US and has transferred his passion for soccer into his life as an ESPN staff writer. In addition to his personal story, he guides us through the history of using data to gain an edge in soccer. He starts in the 50s and 60s and the very basics of soccer statistics. In contrast, he shares information about the exponential growth of data inputs that we get today through video analysis, GPS tracking, cloud computing, artificial intelligence, and so on. However, he is also honest and questioning the models that we have today that cannot explain some phenomena today and how some players and some teams cannot be explained through data. If you plan to read only one book, then this is the one.

Perhaps a bit more current and Europe-focused, Football Hackers digs straight into the details of what you need to know about the world of soccer statistics. Analyzing the possession, shots taken, tackles, and so on, Biermann tries to help differentiate what is important and what is just empty data. Indirectly, he proves the rule that “If it’s important then it can be measured, but not all that can be measured is important”. The book can look very math-oriented and requires a genuine interest in soccer analytics and/or math and statistics. However, it’s a requirement for anybody who wants to get an edge or at least avoid being outsmarted based on accessible data.

The rise of Expected Goals (xG) in soccer analytics is evident, as many pundits share these statistics more than any other info to show how the game went. For example, a team can have dominant possession, but it can be defensive and not have a single chance. Similarly, a shot on goal from far away doesn’t mean it is a good chance. In contrast, a team can have a penalty and miss the goal, which is a great chance without a shot on goal. The book explains what xG is and how to quantify it. It makes the case of why it is a better indicator of the dominance in the game. The book doesn’t have the complexity of the other books on this list, but it gives the right framework so that you would understand the xG on a much better level when you see it in real life.

This does not naturally fall in the category of soccer statistics books. However, Nate Silver is the modern guru of statistics and his classic is something that every person who wants to understand data should read. His work in politics, in addition to his obsession with baseball, explains over and over again why probability is not certainty, and why only certain data is important. As we encounter variables in our analysis we have to assign appropriate weight to them. While this book will not teach us how to do that in soccer, it will help us think about the world of data. I have reread the book multiple times, pausing and thinking along the way with the new information and in the context of the recent games and seasons, of my teams that I coach and the professional ones that I have watched.

Possibly the most famous book on this list, helped by Brad Pitt starring in the movie. It shows how one of the poorest baseball teams in MLB went on the most impressive winning streak using data analytics to scout the sports talent. This is a true story that changed the way baseball teams use data. Obviously, this cannot be directly used in soccer, but certain aspects of it already are. With players playing key factors, it shows how there are no straight replacements in sports. One great player can be sold and two weaker players can be bought for that money. But the end result can be better or worse depending on the characteristics. The right data models can tell us which one is the better option. European soccer clubs like Leicester, Brighton, Borussia, Leipzig, and others have tried this approach. They cannot compete with the giants financially, so they have to be shrewd. I am certain we will see a soccer book like this in the upcoming years. Until then, enjoy Moneyball in the world of baseball.

Written by a professional poker player, we learn to think of our decisions as a process. It is not just the result that matters. Say we play against a better team overall, but we have taller players. We will try playing for set pieces and crosses. We might still lose the game, but we increase our chances of success. The book explains how we should think about maximizing our chances. That doesn’t guarantee success, but it makes us think in terms of probability. We naturally do that in our lives. I still travel by car, bike, and airplane. We limit our downside by wearing helmets and seatbelts. There would be unfortunate accidents, but we try to minimize them. Thinking in Bets will teach us exactly that. My only advice is to pause and reflect while reading the book. Think about your teams and matches, and how to maximize your chances of success.