Overall, I enjoyed Net Gains. I found myself wanting to come back to it and read more and discover more about the analytical revolution in soccer. I’ve been a hardcore baseball fan my entire life, and this year I jumped in to soccer full force (mostly due to issues with baseball, which actually does have something to do with this book). Having been around (and supportive) of the analytical revolution in baseball, I was curious to see what it would look like in soccer, especially because I lack the depth of knowledge that I have for baseball. I assumed that the analytics revolution would be similar to that of basketball’s, but I found I was wrong. Due to the stodginess of soccer, there’s a lot of overlap with baseball and the acceptance of data and how to use. However, there’s a much better reason- soccer is crazy. People constantly in motion, reacting off of each other, making second by second decisions- it adds up to a wild game within the game, even for the teams that prefer to sit back and bleed you to death.

That craziness makes it extremely hard to get data, as O’Hanlon explains over and over. He dives deep into the history of soccer analytics, and tries to find an overarching truth to them, but is forced to admit (from time to time) that we may not be able to carry out a data revolution in the same way. While basketball seems to be a match, I didn’t take into account how basketball may look like chaos, it’s got a lot of set pieces and coaches who can run every little thing.

I liked that O’Hanlon was open about the fact that there isn’t a solid answer to everything yet, and to concerns that an analytical revolution could streamline the game in the name of efficiency, give us a generic style of play, much like baseball is struggling with (or if you want to get really analogous, like what we’ve seen with cars and car design as we get more info on how to be as gas efficient as possible). Overall, very enjoyable, and a good intro for people getting into soccer after the World Cup. I do feel like it’s also got the depth to satisfy hardcore soccer fans, but since I’m in my first year as a Serious Fan, I can’t say that for sure. My quibbles mostly come with editing choices. I felt as though certain phrases/sentences or ideas were repeated over and over without adding anything new. Some parts of the book felt like padding, which I don’t think it needed. The human connection was critical, but sometimes O’Hanlon would veer off into an anecdote that, while interesting, didn’t serve to enlighten the reader in regards to data, analytics, and soccer. It didn’t happen a lot, but I do feel that the book could have had more impact if it was a little more trim.

NET GAINS

Of the many reasons Ryan O'Hanlon provides in his book Net Gains: Inside the Beautiful Game’s Analytics Revolution as to why data analytics has yet to take hold in professional football to the same degree as other professional sports, the one that resonated the most with me was the issue of sample size.

Data-driven approaches to team management have changed the dynamics of professional sports ever since its proof of concept in professional baseball famously documented by Michael Lewis in Moneyball. Yet inasmuch as such have yielded noteworthy results in professional baseball, basketball, and American football, it has yet to truly take root in football (or soccer to Americans like O'Hanlon). Net Gains offers some insight as to why and recounts some of the challenges that analysts, players, and teams have had to quantify the world's most popular sport.

As mentioned, O'Hanlon presents various perspectives and lived experiences of the fits and starts of the data revolution in football. Essentially, much of the wariness that football's "old guard" harbor towards data reads like a greatest hits of the usual objections about quantifying, well, anything. There are just too many variables. No two situations/players/pitches are alike. It's too much effort for too little benefit. And so on.

Yet the matter of there being too few games to constitute a decent sample struck me not just as a fair point but a compelling one. After all, professional football at an elite level only has so many games each year. The English Premiership, for instance, only lasts thirty-eight games each season, and even if one were to factor other tournaments that a team might play throughout the year, albeit rotating players within a squad, it certainly doesn't sound like much data to work with in a statistically significant sense.

Ultimately this is why analysts have had to be especially creative in quantifying the beautiful game, trying to tease out what metrics really matter for the sport (and how to reasonably capture them). O'Hanlon does excellent work of framing the challenges and the potential payoffs, and is served well both by his experience as a former player himself and the occasionally irreverent tone that adds to the character of his reportage. It would arguably be unfair to label Net Gains as "Moneyball but for football!" because the revolution in a sense has still to really take off. But by O'Hanlon's account it is getting there.

A fine book for those who want to understand how area expertise and data analytics come together. Overall, I would recommend this to a soccer fan, a data geek, or the newcomer to both fields.

Really interesting book about soccer analytics. I recently started work for a soccer analytics company so this was a great title for me to read!

Net Gains: Inside the Beautiful Game’s Analytics Revolution (2022) by Ryan O’Hanlon is a really interesting look at how analytics are changing soccer. O’Hanlon now writes for ESPN and has previously written for FiveThirtyEight and other places and also used to host a podcast. He also played soccer at US college level.

Basketball, American Football and Baseball are all games where analytics has had a huge impact. In soccer a similar analytics driven change is yet to manifest itself but people have been trying to perform analysis on soccer for many decades. The games flow and complexity has made this difficult.

I got to read this book from Netgalley as a pre-release and have highly enjoyed it.

Net Gains is very fair in pointing to the work of Stefan Szymanski that says that the league position correlates very well to the pay of the players and that people haven’t managed to do something like Moneyball to soccer yet. O’Hanlon also highlights the impact of Alex Ferguson and Arsene Wenger who managed to slightly beat their expected league position. Manchester United’s failure to win a league title since Ferguson left after winning 13 in 21 seasons also shows that if it’s not very carefully employed money will still not bring titles.

The book also has a chapter on Charles Reep who is often brought up as a showing how hard soccer analytics are how they can fail. However in Net Gains the chapter is far more interesting as it includes an interview with Richard Pollard, a mathematician and statistician who co-authored papers with Reep and also knew him well. Reep’s conclusion, that you should quickly hoof the ball upward because most goals are scored with three or less passes was flawed, but he did capture a huge amount of data that was very valuable and had more insight to his thought than is usually characterized.

The book features a number of modern mathematical analysts such as Luke Bornn and others. Expected Goals (xG), expected Assists(xA), expected possession value (EPV) and the packing number (players passed) are very well explained.

The work of various coaches, including Jesse Marsch, Jurgen Klopp and Pep Guardiola are also described in detail as are their impacts. The chapter on Jesse Marsch and the Red Bull clubs RB Salzburg and RB Leipzig is particularly interesting. Leipzig’s coaches and their use of analytics and their impact on the Bundesliga is fascinating. They seem the closest to doing something like Moneyball in soccer and Leipzig’s rise in Germany has been spectacular, however they are yet to win a major title. But this looks likely to change in the next few years.

For anyone who is interested in the application of statistics and analytics in soccer Net Gains is a must read. The book would also be worthwhile for anyone interested in how statistics can be applied to improve performance in a complex environment. For anyone interested in soccer it’s also an excellent book to read that captures just how difficult soccer is to quantify. O’Hanlon is a good writer and the book is an easy read. Net Gains is really an excellent book that many soccer fans will enjoy.