Net Gains: Inside the Beautiful Game's Analytics Revolution

by Ryan O'Hanlon

This in-depth examination of soccer takes listeners on a tour across the world and throughout history, introducing the many people who have attempted to shine a light onto and innovate a sport that, in many ways, is still stuck in the Dark Ages. This deep dive into the rise of analytics in soccer―a sport where tradition reigns supreme―shows how revolutionary tactics and underexplored metrics are breaking the beautiful game wide open. By exploring how massive institutions built on billions of dollars can function for so long without any kind of introspection―and what happens when people from the outside attempt to question the status quo―author Ryan O'Hanlon, a staff writer at ESPN, shows how time and again experts, managers, coaches, players, and fans feel they know the best approach for any given team or player and yet get undermined by the complexity of the game―and human behavior. To tell this globe-trekking story, O'Hanlon takes listeners inside the front offices and analytics departments of the top professional leagues’ most cutting-edge clubs and profiles a misfit cast of number-crunchers, behavioral economists, tech insiders, and managers all working to move beyond the philosophical side of soccer and uncover the hard truths behind possession, goals, and developing talent.

Genres: Sports, Soccer, Football, Nonfiction, Audiobook, Mathematics

288 pages, Kindle Edition

First published January 1, 2022

Reviews

[Jesse · Rating 3 out of 5]

Very likable, but it raises a metaphysical question. Let's posit

a) that Moneyball is the most successful rise-of-analytics book, commercially and culturally (disappointingly, "Soccernomics" has not yet inflated itself into a trope)

b) because its argument is emotionally appealing but at best semi-true.

Michael Lewis has an amazing talent for pushing his reader to root against people who fail to appreciate chunky walk-prone hitters or left tackles or short-sellers or whatever, even if you'd had no feelings whatsoever about these positions before you opened the book. But if part of the Moneyball A's' (how does one punctuate that?) success derived from chunky walk-prone hitters, another major part came from its trio of highly-drafted aces, evaluated and chosen through the, you know, standard scouting process that correctly identified Hudson/Mulder/Zito as good prospects. So most analysts have noted that at best a mix of old and new, despite the morality play Lewis constructs, accounts for the relative level of success the team enjoyed. (As Billy Beane famously admitted, his stuff didn't work in the playoffs.)

So how do we rate something that's more accurate, not couched in a manipulative good guys/bad guys paradigm, and...doesn't deliver the same narrative/emotional oomph? How much do irrational factors affect our enjoyment of analytics stories, and has some smart person already derived a metric (reading enjoyment over expectation, say, or rEOA) that calculates some objective measurement of this? I don't think that's the only issue here--I kind of lose the thread after a while, as the story moves back and forth and around in time and place and ideas, so we get an extremely diffuse sense of the innovations that have happened and are still happening. The extremely global spread of thinkers--everywhere from midwestern kids to Indian teenage bloggers--is fascinating, but there just isn't enough narrative here, both between and within chapters, and so I ended up knowing a bunch of bits of things about various innovations and attempts to measure success, as well as getting a window into consistent rethinking of what there even was that should be measured.

But I got what felt like a clearer, and not overblown, sense of narrative from Inverting the Pyramid and Zonal Marking, which made the point that every tactical innovation wore out its welcome, so this does not coalesce for me as well as I would have liked.

[Sebastian Gebski · Rating 4 out of 5]

It was much more interesting than "Zonal Marking" - more practical and informative.
Instead of focusing on nostalgia, it traverses the topic of "measuring" football - how to tell which team/player/tactic is more effective in a particular context or in general. A lot of space is dedicated to explaining why football is more complex (less prone to standard analysis) than baseball or basketball - actually, I've found these considerations very interesting.

Why not five stars then? I wish the author would have dived much deeper - into particular coefficients & stats - even the ones specific to a position or play style. Yes, the most important ones were covered (with famous xG in the very first place), but I has just whetted my appetite for more (which I didn't get - sadly). I also liked how O'Hanlon has mentioned a few key sources of football statistical data (like Statsbomb) - but as the majority of these are very expensive & virtually inaccessible to fans, it'd be nice to know if there are any (even limited) alternatives for amateurs & passionate fans.

In general - nice & pleasant read. Recommended.

[Ellis Sriram · Rating 3 out of 5]

This book is overall pretty decent, but I felt that it was a bit too long (hence why it took so long for me to read). It seemed to have an identity crisis about whether it wanted to be an analytics book or a history book, and it tried to be both. I thought a lot of it was interesting, but there were areas that were entirely too in depth, and also areas that I thought didn’t get enough love. Overall I’m glad I read it but it didn’t change my life.

[Nick Fanelli · Rating 5 out of 5]

This book was interesting. I really liked learning about the different ways that analytics has had an impact on soccer.

[Cheenu · Rating 2 out of 5]

This book is mostly a miss.

It is mainly an amalgamation of profiles of various personalities and companies working in the sports analytics industry.

There is no deep, or even a medium, dive into the actual analytics. There are a few interesting ideas proposed by the people interviewed for this book.

However, the author does not give any supporting data in the book itself for the ideas (I'm sure these people would have been happy to provide it to the author) and very rarely refers to papers or articles that explore the ideas in depth.

Lots and lots of ancedota though. Admittedly though, it's fun reading ancedota on a subject you are enthusiastic about.

I feel like this book ideal audience would be a manager or a top level decision maker at a football club, to convince him to hire one of the people (or their firms) interviewed in the book.

Honestly, if I wasn't such a football geek I really doubt I would have finished this book. If this was written about basketball of which I know nothing except the rules and a few player names, it would have been a DNF.

Recommend only if you want to get an overview of all the companies in this industry. Otherwise, give it a miss.

[Andrew Wiser · Rating 4 out of 5]

Back in 2016 or 2017, I listened to O'Hanlon on a podcast and found him annoying. He was a Liverpool fan, and I felt that his insistence that Liverpool was good (despite being in 6th or 7th in the league) to be clear homerism. Then, over the next 5 years, I watched Liverpool become one of the 2 or 3 best team in the world. Needless to say, I was wrong, and he was right.

So, when I heard he was writing a book, I was immediately interested. Even though I had a good understanding of most of the concepts discussed, he does a great job giving the history behind the models and concepts dominating soccer analytics.

I think that the book is especially well written. It's quick and funny. He uses anecdotes to make the book more interesting, but doesn't use those anecdotes to make pop psychology conclusions or sweeping generalizations. I also think that it's the perfect length. Not too long and no chapter drags on too much.

I think the book would work for anyone who has any sort of interest in soccer.

[Michael Martz · Rating 4 out of 5]

I'm a big baseball fan who has bought into the value of analytics in the national pastime. I've always had an interest in soccer, attending a college powerhouse in the St. Louis area way back when the city was the epicenter of the sport in this country. During the pandemic and the following years my interest turned into a full-blown love affair and I routinely watch a half dozen matches a week during the season. "Net Gains" sounded like it'd be right up my alley, as I'd been focused on learning the nuances of the game but hadn't paid much attention to the analytics.

The author, Ryan O'Hanlon, is very open up front about the challenges of applying analytics to soccer. Although the seminal "Moneyball" is mentioned many times throughout the book, he's careful to explain why the baseball classic is not the recipe for how numbers can be used in the world of soccer. The author uses examples and anecdotes to explain concepts and issues and provides a number of real world stories to prove his points.

All-in-all, Net Gains is a very worthwhile, well-written (and researched) book that does a great job explaining the challenges and benefits of applying data analysis to soccer. If you're a fan or a numbers person, you'll enjoy it.

My apologies for using "soccer" instead of "football" in this review, but I'm guessing most folks who read it are Americans....

[Alessandro Pugliese]

Very stellar overview of the ongoing data analytic revolution in the world’s most popular sport. Tons of overlap from my Soccer Analytics course. O’Hanlon does well to synthesize & simplify the many ideas & concepts for an American audience.

[Jeb Burnell · Rating 4 out of 5]

I liked this one. I got 3/4 thru it and thought “when is he going to mention Liverpool?” LFC Only got a page at the end which honestly was right decision. Was better to focus on the smaller clubs using more avant-Garde approaches. Author even brought up the lack of Liverpool content in his acknowledgements

[Erik · Rating 4 out of 5]

Having become mildly obsessed about analytics in my job recently, this book immediately called to me.

Although I have enjoyed playing many different sports, soccer has been a lifelong love and will always be my favorite. I even came out of retirement in my late 30s to play in an open men's league. After a memorable and joyful four-year run, my playing days sadly came to an end after an unfortunate ACL tear.

In any event, I have long wondered if analytics could one day yield more insights into the Beautiful Game. Net Gains helped me to fully grasp its history, technological and cultural challenges, and potential future opportunities. I really enjoyed it.

[Ashley Jane Barlow · Rating 3 out of 5]

This book really had me hooked in the beginning but it lacked a clear focus and organization which made it hard to follow. I felt like the author repeated himself a lot, which I think came because there isn't a book's worth of material on this subject. With that said, there were nuggets of stuff I found interesting and captivating and I'm excited to see how the beautiful game continues to evolve.

[Pete · Rating 5 out of 5]

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.

[Nelson · Rating 4 out of 5]

SOCCER SUCKS!!!

Just kidding. I'm trying to get into soccer analytics, and there are a few choices on where to start. I decided on this book due to some familiarity: author is an ESPN writer, while the others were European. After reading, I realized I'd made the right choice--he draws a lot of comparisons with American sports--sports I'm more familiar with. He does discuss European soccer a lot, and I momentarily lose interest because I'm not a fan. I'm not a fan of professional football, baseball, or basketball either, but at least I once was, so I could follow. The other books probably talk about Euro soccer endlessly.

This book is like Moneyball for soccer. In fact, it IS Moneyball for soccer. It's narrative, not an instruction manual. It's written in an engaging tone, to the point of being sensational. It tries to portray a group of innovative people creating upheaval in a ludditic sport, like Moneyball. And like Moneyball, it makes a couple of major errors, one one statistical one factual.

He became obsessed with the three-pass rule: "Not more than three passes," Reep told the BBC in 1993. "If a team tries to play football and keeps it down to not more than three passes, it will have a much higher chance of winning matches. Passing for the sake of passing can be disastrous." So too, could confusing correlation with causation. Since he had observed that 77.8 percent of goals scored came from three passes or fewer, Reep concluded that it was desirable to avoid passing the ball more than three times.

O'Hanlon then goes on to explain that 91.5 percentage of all possessions are three passes, which makes 77.8 of goals seem like it's less effective. That's not confusing correlation with causation; that's missing a control group.

The other error O'Hanlon mistaking the movie "Moneyball" to be 100 percent factual, LOL.

No, the people Beane inspired were more akin to his deputy in Oakland: Paul de Podesta, the nebbish Yale grad portrayed by Jonah Hill in the film.

In real life, Paul de Podesta went to Harvard, not Yale. In the movie, his name was Peter Brand. Actually, I think Peter Brand was a c0mposite character of Paul DePodesta, JP Ricciardi, and one other person. Depo played football and baseball at Harvard and is good-looking.

Much of what I learned in this book is that soccer is mighty hard to quantify, due to the random, chaotic nature of the game. For example, take the traditional statistic of batting average. It's got an 80% correlation with runs score. Some of the new sabermetrics have upwards of 95%. The best metric that analysts have found in soccer to be correlated with score is Expected Goals, which has a 52% correlation with goals.

A lot of the book was contradictory and confusing. For example, in one chapter he illustrated how the Reeper philosophy of playing bombs away isn't effective. In another, he stressed the usefulness of a goalie who has a strong leg and can basically boot the ball far like a punter.

It seemed like he supported the usefulness of a cross, then in a later chapter said it was overrated. If he didn't do that, then I had trouble following.

Ultimately, I gave the book 4 stars instead of 3 because (1) it's very useful. The fact he mentioned, that online sports databases drive a lot of traffic presents a possible business opportunity, and (2) it provides a lot of references for further research that will come in handy.

[Joe · Rating 4 out of 5]

I received a free copy of this book from NetGalley in exchange for a fair review.

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.

[Paul Hagerty · Rating 5 out of 5]

This book couldn't have come at a better time in my life as a former blog reader. Thank you Ryan. I got a stress fracture in my foot from playing football (soccer) which required surgery and off my feet for 8 weeks with only but time on my hands. I couldn't have read this any faster as your writing style is part storytelling, part facts which makes it a fun read.

I went into this book thinking that I was going to learn how to review data to look at and analyze teams. That's not what it ended up being about and let me tell you a story to show why:

It was a while ago that my eyes were opened to whoscored.com by Ryan and I have used it to track my favorite teams and players. This was one of the reasons I fell in love with Leeds United (before they brought in one of my other favorites from Philly Union - B. Aaronson) through Patrick Bamford. Bamford is one of the best xG creators and hard-working stickers but underperforms in finishing but just works hard and creates opportunities. Ryan wrote an article on him in the past which was stellar https://nograssintheclouds.substack.c.... These articles reviewed ideas and players which had inciteful data mixed with the art of football which was genuine insight. No it's not to the quantity or quality of a top level professional club's resources, but it was one man and his ideas on how to improve the beautiful game. THIS is the reason Ryan wrote this book, to demonstrate what one man and a computer can accomplish.

Ryan's blog and journey as a content creator is different than most in the industry. He is resetting the stage for the data revolution in soccer analytics. I truly believe he wrote this book for the following reasons:
1. Document the history of soccer data, paying homage to prior leaders
2. Inspire the next generation of thinkers in the sport
3. Provide knowledge of the free access that exists
4. Inspire people to apply for jobs in the industry
5. AND MOST of all - INSPIRE THE NEXT GENERATION OF ANALYTIC FOOTBALL MINDS

I'm inspired to question my own football narrative and use the data tools provided. Once again, thank you Ryan and looking forward to your next work.

[Tony · Rating 4 out of 5]

This engaging history of soccer analytics is well worth picking up by anyone with the remotest interest in the topic. O'Hanlon opens the book by talking about his own career as a player who made it to the Division I college level, thus establishing his bona fides as someone who's thought about the game from a higher playing level than probably 0.1% of his readership. He then dives into a very readable history of efforts to use data to improve team performance, tactics, and player valuation, starting with the earliest rudimentary efforts of a few obsessives like Charles Reap in the 1950s and 60s. It's worth noting that the book somewhat in conversation with the work of Stefan Szymanski (Soccernomics), whose writings more or less say that the only analytic that you need to look at for club soccer is the payroll, which, anomalies like Leicester aside, predict success at a very high rate.

As anyone who's followed soccer over the past decades knows, it isn't really until the last ten years that analytics really have taken hold throughout soccer. Some of that has to do with the same kinds of resistance to analytics other sports have seen (most famously recounted in the baseball book, Moneyball), but also the higher level of modeling complexity soccer involves. As a sport with 22 players moving without restriction, it's not until recently that the technology (cameras, GPS systems, cloud computing, etc.) has evolved to enable sophisticated modeling tools to be built. What becomes very clear over the course of his presentation of several personalities, bloggers, and teams, is that we are still in the early stages of soccer analytics. Some of the new metrics (such as Expected Goals) have been gaining currency, but the book provides plenty of case studies of where models and metrics aren't quite providing breakthroughs. For example, I quite liked the section where there is widespread agreement throughout soccer royalty that Sergio Busquets was an invaluable player, and yet there is no model or statistic that can really explain why.

Readers who enjoy the stats and analytics of sports should definitely pick this up, as should anyone with a serious interest in soccer. It also works as a nice complement to the classic history of soccer tactics, Inverting the Pyramid.

[John Holmes · Rating 3 out of 5]

A good tour through some of the ideas shaping analytics in football, but often one that feels meandering and inconsistent. The author clearly wants to get across the idea that football is a complex system that does not lend itself to definitive analyses, while still providing some sense of where analytics can make a contribution. This is a tricky line to tread and often the argument drifts towards berating clubs for not taking analysts seriously enough while being slightly unclear what it is that they should be adopting that they have not done so already. The structure of the book does not help with this. Instead of building an argument and then exploring it's limitations, the book drifts around the globe introducing largely forgettable individuals who have offered new perspectives in football analytics. But the chapters often don't seem to have a clear narrative beyond 'here are some interesting and vaguely connected things'.

That's not too say there is not good material here. The sections on how games are coded by stats companies, the early history of this and its links to England's long ball obsession, and, yes, some of the key metrics are all engaging. And the author does towards the end, try to make a case for what clubs should be doing. Some of the anecdotal material is also fun, particularly about the author's own experiences in football.

However, too much is not said here. Either to keep the text simple or because the information is proprietary, many of the metrics are not fully explained. I'm still not quite sure what goes until expected goal models or other metrics like them. So I'm still not sure how much weight I should really put on the analytical claims.

[Manfred · Rating 3 out of 5]

Rated 5/10. The author attempted to make a ‘Freakonomics’- or Malcolm Gladwell-style book out of soccer data analytics (heady facts and figures simplified by sharing them in the context of creative story-telling). However, he had two problems that kept this from being a really interesting and memorable book: how he structured the book and how he shared stories.

As to the structure … for me, it would have been more impactful if he had provided a bit of background on analytics in sports, analytics in soccer, and then, given the data that exists, analyzed traditional strategic and tactical hypotheses around winning soccer. And dedicated a specific chapter to each AND titled them as such (for example, ‘Hire Elite Managers’, ‘Field One or More Superstars’, ‘Spend More Money’, ‘Utilize Long Balls and Counterattack’, ‘Focus on Passing & Possession’, ‘Shoot More Often’, ‘Get a Great Goalkeeper’, ‘Get Great Midfielders’, ‘Utilize 4-4-2 Formations’, ‘Practice Set Pieces More’, …). Instead, every chapter covered some element around the uncertainty of data analytics in soccer, some history around people who’ve pioneered the processes, and embedded SOME hypothesis, but it wasn’t always clear what was being analyzed and how the stories related, because …

As to the stories … rather than clear, entertaining stories, the author knitted together stories, within stories, within stories, introducing characters, who knew characters, who worked with characters, until the reader was left uncertain as to what we’re actually supposed to be focusing on in any particular chapter. AND the reader was often left wondering … “so DOES this correlate or DOESN’T it correlate?”.

He did, at the start of Chapter 10, summarize his conclusions, but they weren’t the easiest to mine just from reading the book. The book had such potential. It just needed an author who better organized his writing and wrote with more precision & clarity.

[Aldo Rodio · Rating 1 out of 5]

This is really a book for Americans who are completely oblivious of European football and its dynamics.
If you are a proper football fan and you've seen more than 3 matches with your audio on, you already know 80% of what this book is trying to teach you. 99% of it was already old news in 2022.
I mean, the personal stories of the people who worked on the models are interesting, but that's the only good part of the whole thing.
What really got me angry is that up till the end there's no doubt about the fact that these models might have been just wrong (like all models are, as you know if you study this stuff) and the fact that there is some advanced math just makes it universal!
This is only the last attempt to look at European phenomena through American lenses, thinking that somehow there is an hidden truth that only people who studied in Ivy League Collages can extract, please just stop.
This rant is not to say that data are useless in football, but the advanced use of tactics and the individual skills of the players are still far far far more useful, in fact the most useful use of numbers still is the understanding of HOW a team or a player plays, not to find THE RIGHT WAY of playing.
Football is not Basketball, it is more like Chess, and there is no right way to play Chess.

[Tejas Sathian · Rating 4 out of 5]

This was a pretty interesting book in both the soccer and sports analytics genres and I'd recommend it to most people looking to gain a deeper appreciation of soccer. It does a really good job of introducing the concept of analytics in soccer and why it's challenging - the nature of the game naturally opposing attempts at organization and measurement - and it's full of interesting profiles of personalities who have contributed to the growth of modern approaches to the game. Some of the best parts of the book are interviews with quirky and important figures such as Ted Knutsen and Michael Caley, whose iconoclastic approaches have advanced our understanding of the game. In fact these are the real heroes of this book, more so than any particular players or managers or insiders of the sport.

At times I think the book veers beyond this territory into commentary on tactics and other aspects of soccer, and I feel that it struggles in those areas because O'Hanlon isn't as deep into those aspects as writers such as Michael Cox.

I also think the narration of this audiobook should have been much better - it would help to have someone able to pronounce important European soccer names (Ajax, Arsenal, and Thierry Henry were all butchered throughout!).

[Hanson Ho · Rating 5 out of 5]

The only book I've read about sports analytics that meaningfully discusses the use of data in other sports while telling the story of the evolution of its use in its own sport. The compare and contrast really highlights the reason for the differences and also room where each has to grow.

It is definitely focused on football, but its American author and American slant in language and profile subjects might ruffle some feathers in the UK where I'd imagine an English book on the subject would find it's most natural target market, but its succinct breakdown on some of the most influential football metrics out there and how they were developed provided a fascinating read, even if you were well versed in the former.

There may be better reads out there if you only want to learn about football analytics, but O'Hanlon deftly puts its development into the proper context. It's a bit like the Blindside by Michael Lewis (great book, terrible movie FWIW) where the narrative does more than entertain, but enhances the book's main thesis, which I take to be that while football is chaotic, random, and hard to quantify in terms of numbers, it is because of that the pursuit is worthwhile, for both clubs and curious fans.

[Keagan James · Rating 4 out of 5]

This book is solid. It provides a well-written history of different actors in the development of statistical analysis in soccer. The author clearly describes some of the key metrics and innovations used by some clubs in today’s game. The book makes clear that statistics are not widely used by clubs. Those who do use them don’t give them too much weight. I think it was a bad look to spend a lot of time talking about an innovation and casually slipping in that a woman might have created it 8 years before. This book also does not include the manager’s perspective. It is quick to slam managers who do not use statistics widely enough. While, from a club’s standpoint, the integration of statistics can be wildly helpful, sometimes the effects are seen over time. The average tenure of a manager is around a year, so managers don’t have time for ‘the long run’. Thus, they might do things that are inefficient in the long run in order to potentially and perpetually preserve their job in the short turn. The author also spoke about his playing days a little too much. We were all college soccer players once, stop reminiscing in the book. Nonetheless, it was a really interesting book and it was otherwise written well.

[Kevin Thang · Rating 4 out of 5]

Net Gains is a history of analytics or lack there of in football (soccer). The author spends the first half telling briefly the long history of the game and introducing the analytic of expected goals (xG) based on shots taken on the field and its trajectory among other factors. The author being American based, constantly compares the slow progression of analytics in soccer to the rapid growth in football, baseball, basketball, & hockey. Also allows for an easier understanding if you’re more familiar with the latter sports.

Second half of the book is geared towards despite being one of the oldest sports in the world, football is still hesitant to embrace analytics unlike the many American sports. And for those that do, there is a moneyball advantage against those unwilling to catch up yet.

[Owen · Rating 5 out of 5]

I love soccer and I’m a math geek. I enjoyed this book for many reasons. It discusses changes in strategy that are important. The evaluation of players in the transfer market it’s another great discussion.

It is amazing to learn how much data is collected for pro soccer games. If anything, I wished for more math formulas, numbers and discussion. To some degree expected possession value, EPV, evaluates defenders but overall I thought defensive values were being shortchanged. I also found it a little off that midfielders seem to suffer in these evaluations. That leaves me to wonder if the formulas are right and my impressions are wrong, or vice versa.

Interesting and thought-provoking.

[Nathan Tesfa · Rating 5 out of 5]

Great narrative of the history of analytics in soccer interspersed with more general narratives about "the beautiful game". Breaks down the development of soccer statistics in an easy to understand and engaging way, while also looking to the future. The limitations and issues of current methods are explored in an interesting way, while future statistical models are highlighted. This is a great book for a soccer fan, stats geek, or someone with little background in either. O'Hanlon does well to integrate personal stories with the overarching narrative. In an increasingly saturated data science and sports market, this book is a good consolidation of the nearing inflection point soccer is facing.

[Tamás Szajkó · Rating 3 out of 5]

A szerző - mentségére váljon - derekasan elismeri a könyv elején, hogy a foci, szemben a labdasportok nagy részével, nagyon nehezen modellezhető, és hiába a végtelen adat, a számokból kiindulva önmagában nem értelmezhető a játék. Ezt követően aztán mégiscsak elmélyülünk az analytics történelmében, amiben igazán korszakalkotó információkat nem feltétlenül sikerül találni (több lövés = jó), de valamennyire aranyos végigkövetni a blogger-tudósok előtérbe kerülését. Sajnos a könyv végére választ nem igazán kapunk semmire (nem is ígért mondjuk), de kis felületes olvasmányként élvezhető volt, bár a karakter-bővítési célú háttér-bioktól el tudtam volna tekinteni.

[Max Rizzuto · Rating 4 out of 5]

Really interesting read. I have a much better understanding and deeper interest in the world of soccer analytics after reading (as someone who’s already deeply interested in both).

The writing was a bit clunky and inaccurate at points, though. The word “data” was consistently used as singular when it’s plural. There were some blatantly obvious factual errors that I can’t stop thinking about, like saying that Chelsea won the 2008 Champions League or that FC Midjtylland has won the Champions League.

Overall, though, interesting read!

[Hunter · Rating 4 out of 5]

A good overview of the statistical analyses being undertaken in the modern game of soccer and their respective histories. This likely speaks more to the sport (very uncertain and variant) and the progress of analytics in the game (varied and minimal at best) but the book was more individual vignettes that linked up occasionally than one coherent thread about progress or improvement. Not a knock on the style, but made it hard to keep up with certain characters and ideas. Overall, not too technically deep but an enjoyable read for a big sports nerd.

[Sumeet · Rating 3 out of 5]

Was hoping for something closer to Seth Partnow’s The Midrange Theory, but it felt a bit lacking in substance. Focuses far too much on the history and the people. I guess it’s a difficult problem as an author given that football hasn’t embraced analytics the way American sports like baseball and basketball have, and the sport doesn’t lend itself to that kind of study as well. Great when grounded in the game itself, e.g. the bits on Midtjylland, set pieces, RB Leipzig, and the ambiguity of the midfield.

[Tyler · Rating 5 out of 5]

A well-balanced history of soccer's forays into analytics. O'Hanlon does a good job of keeping the timeline moving while introducing the main proponents along the way. He also is exhaustive in the spheres in which he gives credit and doesn't omit work done by bloggers, inside club teams or in academia.

I will note that this book had a larger than normal number of typos, spelling mistakes and poorly constructed sentences. Definitely needed some beta readers and further rounds of editing.