Most Insightful Soccer Statistics Books [Complete Guide 2024]

“The better team lost today”. We have heard this statement when teams think they’ve been the better team. How did they measure them being better? Did they do that objectively? Sometimes one team had the majority of the possession and the opposition had only one set piece, like a corner or a free kick. Would the statistics tell us that the first team should win the game? Well, if the first team passed between the goalkeeper and the center-backs, while the opposition had David Beckham take a free kick, then it means that the data didn’t tell us the full story. The best soccer statistics books can tell us the progress that soccer analysts have made over the past decades and where they are going.

Which data is important and which one is just noise? How can we evaluate the quality of the data and the true advantage that one team has over the other? Does the tactical approach drive the statistics of the game? Or can the data drive our tactics to victory? Is there something left to the naked eye that cannot be quantified by statistics?

What are the best soccer statistics books?

Soccer has become so big financially and the league structure for most leagues requires good performances. In Europe, teams have to perform well even if they have no chances for the title. They need to qualify for international competitions (lucrative incentives). Also, if they perform particularly badly, they get relegated, which can devastate the team, both financially and in terms of players who wouldn’t agree to play in the lower division. For these reasons, it is imperative for teams to win games, or at least not lose them.

To gain an edge, the top soccer clubs in the world hire soccer analysts, data scientists, and statisticians. Not only that, but soccer agents and their agencies hire them to identify the talent earlier. They synthesize data with methods from the best soccer statistics books, but also from books about data science from other sports and overall in the field of statistics. These are our picks of books that can significantly improve the way you look at the game through data analytics. They are not soccer books for kids or maybe even regular soccer fans – it is for the ones obsessed with numbers.

Net Gains by Ryan O’Hanlon

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.

Football Hackers by Christoph Biermann

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 Expected Goals Philosophy by James Tippett

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.

Signal and Noise by Nate Silver

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.

Moneyball by Michael Lewis

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.

Thinking in Bets by Annie Duke

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.

Decision time

With so many books on soccer statistics, you might think we know so much about it. I would disagree with this statement. We know the human stories of soccer players, but we are far from understanding the numbers. I think we are just starting with it. With the rise of AI and the influx of data through various sensors, we will see an explosion of it. We have even seen it in youth sports as young as U8s. Video systems can calculate possession, passes, shots, and even xGs. This is truly impressive and will drive the development of youth players in a different way.

As you saw from the books, many other industries are ahead of soccer. However, as soccer is so lucrative, clubs will invest more and more in technology over time. The best soccer clubs in the world already hire these kinds of job profiles: data scientists, programmers, AI/ML engineers, computer vision experts, computer infrastructure engineers, and so on. The soccer aspect will not stay a side gig or a niche, but it will become a legitimate track for these professionals. They will try to outsmart each other and give an edge to their clubs. Only a few will succeed, so it will be fascinating to see yet another battle between the soccer clubs.