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The Expected Goals Philosophy: A Game-Changing Way of Analysing Football
The Expected Goals method is football’s best-kept secret. The metric gives unparalleled insight into which teams and players are performing at the highest level.Professional gamblers have used Expected Goals to make millions through football betting. Club scouts have used Expected Goals to identify hidden gems in the transfer market. And the media have recently started using Expected Goals to offer more profound insight in their broadcasts.Despite this, most ordinary fans still don’t understand what the Expected Goals method is – or appreciate the significant impact that it is set to have on the sport in coming years.Expected Goals (otherwise known as xG) was originally conjured up by a small corner of the online football analytics community. It didn’t take long for professional gamblers to begin using xG to predict match outcomes. These bettors utilised the Expected Goals method to turn over hundreds of millions of pounds from the bookmakers.Before long, football clubs had caught on to the ground-breaking insight given by xG. Brentford FC were leaders in this field; their data-driven approach has led them to a first ever promotion to the Premier League. In the last five years, the small West London side have turned over more than £150m in transfer revenue from their use of the Expected Goals method in player recruitment.More recently, the Expected Goals method has been adopted by the media as a form of insight. Fans are finally catching on to the pioneering means of football analysis. Soon enough, anyone who doesn’t understand the Expected Goals philosophy will be left behind.“This is worth a read for anyone sceptical about xG” – Jamie Carragher“An excellent choice for any level of knowledge and interest on the subject. I cannot recommend it enough” – The Good Gambling Guide“A great read” – David Jones (Sky Sports presenter)
222 pages, Kindle Edition
Published November 6, 2019
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February 1, 2021
This is a long review. TL;DR: I do not recommend this book to anyone.
The Good: the topic is interesting and is becoming increasingly important in the world of football, and the book is very easy to understand that, like the author said, anyone who has completed elementary school can follow along.
The Bad (there's a lot):
1) My absolute largest problem with the book: expected goals is never actually shown to be predictive. Now, I do think xG is useful and a better metric than a lot of the current ones, but if you're an author clearly trying to appeal to regular football fans who don't care for statistics, then the burden is on you to show "here is why xG is a good metric for long-term success." Throughout the book, we're inundated with "xG is a better predictor of long-term performance than the points table" and "xG cuts out the randomness of the sport to measure real performance," yet, we are never actually shown why this is! I was baffled by this. All I ask for is perhaps a scatterplot with xG on the x-axis and actual goals on the y-axis, for all teams in many of the top European leagues, over a long-period (5 years). If xG is such a good metric for long-term performance that eliminates randomness, then the R^2 value should be reasonably high for this plot, no? Why doesn't the author do anything close to this? The idea of R^2 can be explained to a beginner within a page, so it is not like it is too complicated. The only part of the book where the author supports the idea that xG is a good predictor in long-term performance is when he says that every player (bar Messi) does not consistently overperform his xG over a few years. BUT THE AUTHOR NEVER GIVES ANY QUANTITATIVE EVIDENCE FOR THIS. This single claim is the most interesting sentence in the entire book, but the author just tells the reader to look it up themselves if they don't believe it. Not even joking. How can I take this book seriously when it makes so many claims about how xG is a great metric and then shows close to ZERO numerical evidence for it???
2) This "book" could easily be fit into one or two articles on a blog, no exaggeration. Within each chapter, the information is repeated so many times that I honestly believe each chapter could be at least a third or half of its size. For some reason, the author likes to start a lot of the chapters with a somewhat detailed description of what he is about to write about, then the author goes on to elaborate slightly on what he has already explained pretty well in the introduction, and then tends to end the chapter by once again summarizing the same exact points but with no new profound conclusion. The actual formatting of the book makes it obvious that it was trying to fluff the content to reach 200 pages: child-like large font, huge white-spaces between chapter subsections, entire full-page chapter cover page, very elaborate algebraic steps, etc. Some of the chapters are entirely repeated throughout the book to the point where you don't need to read them in the first place. All in all, this book could be shortened to around 30 pages of regular-font text, instead of the 200 pages I had to read.
3) The book's tone comes off as simultaneously condescending and as victimized. Half the book is the author saying that all the media pundits, managers, and even fans are stupid because they let their biases affect their judgements instead of just relying on statistics. The other half of the book is the author complaining that the average fan doesn't like xG. Perhaps if the author didn't talk like he was superior to others for using statistics, the average fan wouldn't feel so opposed to such a metric. On a personal note, I disagree with how the author approaches the ideal use of xG. Somehow, the author completely ignores that football is first and foremost a sense of identity and shared entertainment for fans, not an intellectual debate about who can judge team performances more accurately. So, when the author verbatim says that fans should encourage their clubs to have a high turnover rate of players because it would be more efficient for maximizing profits per xG, it completely disregards that fans have emotional attachment to players and for many, having the identity of the club be one that cares for it players and fosters fan-player relationships is more important than marginally better on-field results or profits. In the chapter about scouting, the author fawns over the Brentford owner who, and I quote from the book, "doesn't view each player as a player, but as an amount of money. Each player represents an intrinsic value of worth, like stocks in the stock market." Who can read this and not take a step-back and realize how dehumanizing and, frankly, boring it is to view football this way? No wonder xG has, according to the author, faced so much resistance from fans and pundits if the outcome is seeing a fully human player as simply a statistic, or even worse, a bag of money. This is real-world football, not the game Football Manager. This reminds me of that Nike 2014 World Cup ad titled "Risk Everything" that was about a scientist who created perfect football-playing robots that made no mistakes, always made the most accurate play, etc. They quickly replaced the real "flawed" football players of the world, but with their departure also went the fans, since the game became boring. After reading this book, part of me thinks the xG revolution described in this book will cause fans to turn away from the sport. And to be honest, after reading this book, I partly want to see xG fail and not gain any traction in the mainstream, since the vision presented by the author is one of numbingly boring statistics replacing all emotional aspects of the game.
4) A certain word repeated throughout the book irritated me to no end, and that was the word "deserved." The author would constantly claim, "xG shows which team deserved to win" and "the xPoints table shows which teams deserve to be top of the league." First of all, something being deserved is ultimately a subjective statement, but the author acts like it can be objectively determined. But I get it, random-chance events (luck) shouldn't count for what a team deserves or not, I guess. But then prove to me that xG completely cuts off luck and all that we're left with is pure team/player skill. This goes back to my first point in this review: we're never shown why xG is actually a good metric. I'd be happier if the author just said "the xPoints table shows where we would expect the team to be points-wise if they had average players taking their shots." Now that's a statistically-accurate and neutral statement about what xG and xPoints actually measures, not what is deserved or not. Perhaps the author simply uses the word "deserved" to be more concise and applicable to average non-statistically-inclined fans, but it also makes the statement subjective and, going back to my third point in this review, even condescending.
5) The book is full of contradictions in its messaging that makes me think the author just came up with arguments for xG as he was writing the book, with no long-term planning. The most egregious one came right at the end of the book. After spending quite literally the entire book criticizing all types of humans in football (managers, pundits, fans) for having biases when judging players and teams, and that instead they should rely purely on statistics (xG), the author then casually reveals that Smartodds, the statistics-aggregator company the author bats for, actually uses humans to judge what the xG of an attack should be. Am I crazy for thinking this goes completely against what the author talks about throughout the entire book? The author defends this saying that it is good because it is a blend of computer statistics and human intuition. But why should this be good? The author makes no effort to not constantly criticize non-statistics driven decision-making within the sport, but now when it's a multi-millionaire bet-adjacent company doing it, it's not only fine but actually better than using only computers?
Another one of my big gripes was the chapter on player xG. The author spends the first few pages of the chapter talking about how difficult it is to measure the ability of a player because of all the randomness and the team aspect of the game. Plus, determining who is better is often subjective. Then towards the end, the author uses xG and xA to show why Messi is such a statistical anomaly. Ok, Messi is unbelievable, I agree with that. But then the very last two sentences of the chapter annoyed me to no end. They read, "Our eyes have told us for years that Messi is the best player in the world. The Expected Goals data proves it." Look, I'm not a statistician, but I remember from middle-school science that you can't just say "this data proves a subjective claim." The section just came off as childish. Yes, the data strongly supports that Messi is more clinical with his shots than other players, or that his teammates are less clinical than you'd expect them to be given Messi's passes to them, but to then use that and say "this proves he is the greatest player in the world" seems like a bit of a jump into a realm of subjectivity the author is not well equipped for.
Also, the author waits until the end of the book to describe the flaws of xG, which include the fact that defensive formation and positioning during the shot aren't taken into account when calculating xG. The author quickly mentions this point and then moves on, but I was left thinking about it for a while. Isn't this extremely important? Isn't the location of defenders and goalkeepers perhaps even more important than the position of the shot? You will find no sufficient answer to this question in this book.
6) The book uses a surprising amount of anecdotes to talk about a subject which is about large aggregated data. The scouting chapter focuses almost entirely on one club that uses xG; the player xG chapter focuses on certain players like Ronaldo, Hazard, Mane, and a few others; the first half of the book seems to revisit the same Arsenal-Manchester City match a thousand times. Expected goals is a statistic based on aggregated averages, so why not use more examples that incorporate that? Ironically, the author seems to bring up more examples that contradict the power of xG as a predictive tool (like the aforementioned Arsenal-Manchester City match), so, since the author never shows sufficient empirical support for xG as a predictive tool, the anecdotes included in the book only made me more suspicious of xG. It really is laughable.
7) The writing style is mundane and unexciting, and there are a few grammar errors and typos, one of which was so obvious it makes me think no one actually proof-read the book before publishing.
8) Just when the book is about to get into an exciting topic, like how xPoints is actually calculated from xG, the author writes a very vague statement about how the problem is approached (in the xP example, he just says a "computer simulation" is done to predict how many times a team would win given the xGs in the match. Ok? So talk about standard deviation and variance. Talk about how those are calculated and how they're incorporated into the simulation.) Someone who already knows the basics of xG will find no value in this book.
I've never before written such a long review for a book, but in the middle of reading this book, I found myself getting irrationally angry at the way the author chose the talk about this otherwise fascinating topic. I do not recommend this book for anyone.
The Good: the topic is interesting and is becoming increasingly important in the world of football, and the book is very easy to understand that, like the author said, anyone who has completed elementary school can follow along.
The Bad (there's a lot):
1) My absolute largest problem with the book: expected goals is never actually shown to be predictive. Now, I do think xG is useful and a better metric than a lot of the current ones, but if you're an author clearly trying to appeal to regular football fans who don't care for statistics, then the burden is on you to show "here is why xG is a good metric for long-term success." Throughout the book, we're inundated with "xG is a better predictor of long-term performance than the points table" and "xG cuts out the randomness of the sport to measure real performance," yet, we are never actually shown why this is! I was baffled by this. All I ask for is perhaps a scatterplot with xG on the x-axis and actual goals on the y-axis, for all teams in many of the top European leagues, over a long-period (5 years). If xG is such a good metric for long-term performance that eliminates randomness, then the R^2 value should be reasonably high for this plot, no? Why doesn't the author do anything close to this? The idea of R^2 can be explained to a beginner within a page, so it is not like it is too complicated. The only part of the book where the author supports the idea that xG is a good predictor in long-term performance is when he says that every player (bar Messi) does not consistently overperform his xG over a few years. BUT THE AUTHOR NEVER GIVES ANY QUANTITATIVE EVIDENCE FOR THIS. This single claim is the most interesting sentence in the entire book, but the author just tells the reader to look it up themselves if they don't believe it. Not even joking. How can I take this book seriously when it makes so many claims about how xG is a great metric and then shows close to ZERO numerical evidence for it???
2) This "book" could easily be fit into one or two articles on a blog, no exaggeration. Within each chapter, the information is repeated so many times that I honestly believe each chapter could be at least a third or half of its size. For some reason, the author likes to start a lot of the chapters with a somewhat detailed description of what he is about to write about, then the author goes on to elaborate slightly on what he has already explained pretty well in the introduction, and then tends to end the chapter by once again summarizing the same exact points but with no new profound conclusion. The actual formatting of the book makes it obvious that it was trying to fluff the content to reach 200 pages: child-like large font, huge white-spaces between chapter subsections, entire full-page chapter cover page, very elaborate algebraic steps, etc. Some of the chapters are entirely repeated throughout the book to the point where you don't need to read them in the first place. All in all, this book could be shortened to around 30 pages of regular-font text, instead of the 200 pages I had to read.
3) The book's tone comes off as simultaneously condescending and as victimized. Half the book is the author saying that all the media pundits, managers, and even fans are stupid because they let their biases affect their judgements instead of just relying on statistics. The other half of the book is the author complaining that the average fan doesn't like xG. Perhaps if the author didn't talk like he was superior to others for using statistics, the average fan wouldn't feel so opposed to such a metric. On a personal note, I disagree with how the author approaches the ideal use of xG. Somehow, the author completely ignores that football is first and foremost a sense of identity and shared entertainment for fans, not an intellectual debate about who can judge team performances more accurately. So, when the author verbatim says that fans should encourage their clubs to have a high turnover rate of players because it would be more efficient for maximizing profits per xG, it completely disregards that fans have emotional attachment to players and for many, having the identity of the club be one that cares for it players and fosters fan-player relationships is more important than marginally better on-field results or profits. In the chapter about scouting, the author fawns over the Brentford owner who, and I quote from the book, "doesn't view each player as a player, but as an amount of money. Each player represents an intrinsic value of worth, like stocks in the stock market." Who can read this and not take a step-back and realize how dehumanizing and, frankly, boring it is to view football this way? No wonder xG has, according to the author, faced so much resistance from fans and pundits if the outcome is seeing a fully human player as simply a statistic, or even worse, a bag of money. This is real-world football, not the game Football Manager. This reminds me of that Nike 2014 World Cup ad titled "Risk Everything" that was about a scientist who created perfect football-playing robots that made no mistakes, always made the most accurate play, etc. They quickly replaced the real "flawed" football players of the world, but with their departure also went the fans, since the game became boring. After reading this book, part of me thinks the xG revolution described in this book will cause fans to turn away from the sport. And to be honest, after reading this book, I partly want to see xG fail and not gain any traction in the mainstream, since the vision presented by the author is one of numbingly boring statistics replacing all emotional aspects of the game.
4) A certain word repeated throughout the book irritated me to no end, and that was the word "deserved." The author would constantly claim, "xG shows which team deserved to win" and "the xPoints table shows which teams deserve to be top of the league." First of all, something being deserved is ultimately a subjective statement, but the author acts like it can be objectively determined. But I get it, random-chance events (luck) shouldn't count for what a team deserves or not, I guess. But then prove to me that xG completely cuts off luck and all that we're left with is pure team/player skill. This goes back to my first point in this review: we're never shown why xG is actually a good metric. I'd be happier if the author just said "the xPoints table shows where we would expect the team to be points-wise if they had average players taking their shots." Now that's a statistically-accurate and neutral statement about what xG and xPoints actually measures, not what is deserved or not. Perhaps the author simply uses the word "deserved" to be more concise and applicable to average non-statistically-inclined fans, but it also makes the statement subjective and, going back to my third point in this review, even condescending.
5) The book is full of contradictions in its messaging that makes me think the author just came up with arguments for xG as he was writing the book, with no long-term planning. The most egregious one came right at the end of the book. After spending quite literally the entire book criticizing all types of humans in football (managers, pundits, fans) for having biases when judging players and teams, and that instead they should rely purely on statistics (xG), the author then casually reveals that Smartodds, the statistics-aggregator company the author bats for, actually uses humans to judge what the xG of an attack should be. Am I crazy for thinking this goes completely against what the author talks about throughout the entire book? The author defends this saying that it is good because it is a blend of computer statistics and human intuition. But why should this be good? The author makes no effort to not constantly criticize non-statistics driven decision-making within the sport, but now when it's a multi-millionaire bet-adjacent company doing it, it's not only fine but actually better than using only computers?
Another one of my big gripes was the chapter on player xG. The author spends the first few pages of the chapter talking about how difficult it is to measure the ability of a player because of all the randomness and the team aspect of the game. Plus, determining who is better is often subjective. Then towards the end, the author uses xG and xA to show why Messi is such a statistical anomaly. Ok, Messi is unbelievable, I agree with that. But then the very last two sentences of the chapter annoyed me to no end. They read, "Our eyes have told us for years that Messi is the best player in the world. The Expected Goals data proves it." Look, I'm not a statistician, but I remember from middle-school science that you can't just say "this data proves a subjective claim." The section just came off as childish. Yes, the data strongly supports that Messi is more clinical with his shots than other players, or that his teammates are less clinical than you'd expect them to be given Messi's passes to them, but to then use that and say "this proves he is the greatest player in the world" seems like a bit of a jump into a realm of subjectivity the author is not well equipped for.
Also, the author waits until the end of the book to describe the flaws of xG, which include the fact that defensive formation and positioning during the shot aren't taken into account when calculating xG. The author quickly mentions this point and then moves on, but I was left thinking about it for a while. Isn't this extremely important? Isn't the location of defenders and goalkeepers perhaps even more important than the position of the shot? You will find no sufficient answer to this question in this book.
6) The book uses a surprising amount of anecdotes to talk about a subject which is about large aggregated data. The scouting chapter focuses almost entirely on one club that uses xG; the player xG chapter focuses on certain players like Ronaldo, Hazard, Mane, and a few others; the first half of the book seems to revisit the same Arsenal-Manchester City match a thousand times. Expected goals is a statistic based on aggregated averages, so why not use more examples that incorporate that? Ironically, the author seems to bring up more examples that contradict the power of xG as a predictive tool (like the aforementioned Arsenal-Manchester City match), so, since the author never shows sufficient empirical support for xG as a predictive tool, the anecdotes included in the book only made me more suspicious of xG. It really is laughable.
7) The writing style is mundane and unexciting, and there are a few grammar errors and typos, one of which was so obvious it makes me think no one actually proof-read the book before publishing.
8) Just when the book is about to get into an exciting topic, like how xPoints is actually calculated from xG, the author writes a very vague statement about how the problem is approached (in the xP example, he just says a "computer simulation" is done to predict how many times a team would win given the xGs in the match. Ok? So talk about standard deviation and variance. Talk about how those are calculated and how they're incorporated into the simulation.) Someone who already knows the basics of xG will find no value in this book.
I've never before written such a long review for a book, but in the middle of reading this book, I found myself getting irrationally angry at the way the author chose the talk about this otherwise fascinating topic. I do not recommend this book for anyone.
November 15, 2019
Unbearable amount of repetition in the text. Some of the details are wrong or misleading at best like smartodds won hundreds of millions "from the bookmakers".
Read Christoph Biermanns book if you want an overview on the subject.
Read Christoph Biermanns book if you want an overview on the subject.
December 20, 2019
Despite the book striving to, it is not near Michael Lewis's "Moneyball". Neither the content nor the writing style can match Lewis's classic. While the author has some insights from his professional carrier to offer, I could not but feel like he lacks a deeper understanding of the statistical foundations underlying the quantitative analysis of sports. The one thing I did however really enjoy about this book was the anecdote on Matthew Benham and Brentford FC. Nevertheless, I had to ask myself from which sources the author took his knowledge on Benham, Brentford and their analytical approach since he never explicitly states so.
January 24, 2024
Interesting subject, poorly written
Unnecessary repetition. Some good anecdotes but could have been at least 50 pages shorter.
Unnecessary repetition. Some good anecdotes but could have been at least 50 pages shorter.
January 8, 2023
I don't understand the ott negative reviews on this page for this book.
This is a self-described introductory text on the Expected Goals concept. It's only meant to be a useful, basic, guide accessible to casual football fans who are understandably skeptical of the idea.
More sophisticated books and overviews of the use of data analytics in football/sports are of course available, but I don't think that detracts from the merits of this simpler one.
This is a self-described introductory text on the Expected Goals concept. It's only meant to be a useful, basic, guide accessible to casual football fans who are understandably skeptical of the idea.
More sophisticated books and overviews of the use of data analytics in football/sports are of course available, but I don't think that detracts from the merits of this simpler one.
November 20, 2019
As a de facto Intro to Expected Goals, this book is best suited for those who know little about the advanced soccer statistic, or are curious about its general use and purpose. Those who are deeper into soccer analytics will find some interesting backstory related to betting syndicates and such.
February 10, 2021
It's difficult to say that the information in this book isn't eye opening and extremely fascinating for fans of the sport at any level. Before reading Tippet's xG Philosophy, I knew little about the method of analyzing the game and had only heard it in passing from begrudging analysts and friends who were fans and ahead of the curve in this regard. But the science and statistics laid out in this book make it difficult to imagine that the xG method of analyzing soccer will not grow swiftly over the next few years.
That said, James Tippet really needs to find himself a new editor. The amount of spelling and grammar mistakes in this book–a published book!–are enormous and hard to miss. Good read overall for any fan of the sport.
That said, James Tippet really needs to find himself a new editor. The amount of spelling and grammar mistakes in this book–a published book!–are enormous and hard to miss. Good read overall for any fan of the sport.
January 4, 2023
A must read for football fans.
July 2, 2022
Great info, entirely to repetitive. If you received a nickel each time the author repeated a sentence/thought, you’d be able to pay for the book and then some.
This entire book could have been a blog post. Awesome information, but just Google xG if you’re curious.
This entire book could have been a blog post. Awesome information, but just Google xG if you’re curious.
January 15, 2020
I was coming from the author's previous book on the subject, The Football Code, which was a disappointment. I found it too general, too simplistic, way too repetetive. Thus, my hope was that this book would offer a deeper look at Expected Goals, its applications and foundations. Yet, again, I was disappointed.
In many ways, he has written two identical books. They are similar, up to the point that even the examples are copy+paste. Perhaps unsuprisingly, no great "secrets" from Smartodds are revealed. While Expected Value and "Variance" are treated ad nauseam, the distributional properties and assumptions of football goals (never mind Expected Goals) are not mentioned at all. Important work that would back up the book up in this regard (i.e. Dixon-Coles paper) is not found in its bibliography, casting doubt on the depth of research conducted for this book. The style is endlessly repetetive, and seldom to the point.
Makes one wonder whether about its editing. Lucklily, it does not have the seemingly random structure which "The Football Code" had.
These two books' contents could be summed in one article - even the same article. Considering the amount of blogs covering this, a well-written introdoctury blog article on Expected Goals would probably give you more than these two books combined.
Never mind "Moneyball", this book does not come close to other introductory popular science books on football analytics I enjoyed, such as "Soccermatics" by Sumpter, "The Numbers Game" by Anderson and "Football Hackers" by Biermann.
In many ways, he has written two identical books. They are similar, up to the point that even the examples are copy+paste. Perhaps unsuprisingly, no great "secrets" from Smartodds are revealed. While Expected Value and "Variance" are treated ad nauseam, the distributional properties and assumptions of football goals (never mind Expected Goals) are not mentioned at all. Important work that would back up the book up in this regard (i.e. Dixon-Coles paper) is not found in its bibliography, casting doubt on the depth of research conducted for this book. The style is endlessly repetetive, and seldom to the point.
Makes one wonder whether about its editing. Lucklily, it does not have the seemingly random structure which "The Football Code" had.
These two books' contents could be summed in one article - even the same article. Considering the amount of blogs covering this, a well-written introdoctury blog article on Expected Goals would probably give you more than these two books combined.
Never mind "Moneyball", this book does not come close to other introductory popular science books on football analytics I enjoyed, such as "Soccermatics" by Sumpter, "The Numbers Game" by Anderson and "Football Hackers" by Biermann.
January 25, 2021
Really interesting and accessible introduction to expected goals. I managed to get through the book in a 24 hour period. I was thoroughly gripped and learnt a lot. I found the comparisons between Moneyball and Brentford revealing and insightful, particularly how Brentford have utilised xG to exploit the transfer market. Tippett explores the differences between results and performance in an engaging and easily understandable way. The graphics, data and presentation of maths was easy to follow.
I would have loved to heard more about defense and goalkeepers and how to measure their performance in terms of xG. Also, a bit more about how strikers such as Michu and Benteke were briefly overvalued due to one good season. This is mentioned once but not really explored any further.
I would certainly recommend to those who may have heard about or seen xG when watching football and wanting a bit more information. It's easy to bypass these stats when you see them on the screen, but having this book as a reference point is invaluable.
I would have loved to heard more about defense and goalkeepers and how to measure their performance in terms of xG. Also, a bit more about how strikers such as Michu and Benteke were briefly overvalued due to one good season. This is mentioned once but not really explored any further.
I would certainly recommend to those who may have heard about or seen xG when watching football and wanting a bit more information. It's easy to bypass these stats when you see them on the screen, but having this book as a reference point is invaluable.
February 8, 2020
Another book that desperately needed a good editor. The writing style is pretty mundane, too. And the book is 50 pages too long, at least. The description of the xG method seemed weak to me, not bothering to discuss the issues with the approach until right at the end of the book: the last twenty pages were easily the most interesting. Football analytics is a fascinating area, and I've been following it ever since Moneyball, and expecting a data revolution on football, which has now arrived. But it'll be a lot more than xG, and almost certainly is already at a club like Liverpool.
February 2, 2021
Rough read. Extremely repetitive and poorly written. I was able to skip whole paragraphs, and even whole pages, and keep up with what was going on.
If I had to sum it up quickly, the whole book could have been written in a long form article somewhere online. Very little quantitative discussion, and even the main points are vaguely explained. I would recommend skipping this and just google the subject.
If I had to sum it up quickly, the whole book could have been written in a long form article somewhere online. Very little quantitative discussion, and even the main points are vaguely explained. I would recommend skipping this and just google the subject.
June 2, 2021
It has never been a good book, and it's becoming obsolete very quickly (I have read it 1.5 years after publication, and most of the few insights it provided are already very well known)
I can't even figure out who could be a good audience for this book. An average fan, trying to dip his toe into advanced statistics? The book litters him with way too much numbers while teaching precious little. Someone, who is more interested in the depth of football and/or advanced statistics? The deepness of the actual coverage of xG here is extremely shallow, offers almost no insights on modeling, mathematical or any other level. I can't picture anyone who would like more than a third of this book.
Besides the numerous typos (quite unacceptable) in the book while working with numbers, it also fails to incorporate some well-known phenomena which could make the book a bit more insightful. For example, it mentions the importance of shooting from stronger/weaker foot several times, but fails to mention a single time that two-footed players (somewhat unsurprisingly) tend to have a better chance outperforming their xG (Heung-min Son, Mason Greenwood).
The only part of real interest for me was how Brentford uses Smartodds for scouting and how differently Smartodds are gathering data compared to other companies such as Opta. However, this section was mysterious, wrongly explained and left open questions. All we know is that Smartodds uses humans to gather 'predictive' xG, but only for teams, as players' statistics are unreliable. Brentford picks the best teams, and acquires the best players from them. How they pick the best players? We'll never know.
I can't even figure out who could be a good audience for this book. An average fan, trying to dip his toe into advanced statistics? The book litters him with way too much numbers while teaching precious little. Someone, who is more interested in the depth of football and/or advanced statistics? The deepness of the actual coverage of xG here is extremely shallow, offers almost no insights on modeling, mathematical or any other level. I can't picture anyone who would like more than a third of this book.
Besides the numerous typos (quite unacceptable) in the book while working with numbers, it also fails to incorporate some well-known phenomena which could make the book a bit more insightful. For example, it mentions the importance of shooting from stronger/weaker foot several times, but fails to mention a single time that two-footed players (somewhat unsurprisingly) tend to have a better chance outperforming their xG (Heung-min Son, Mason Greenwood).
The only part of real interest for me was how Brentford uses Smartodds for scouting and how differently Smartodds are gathering data compared to other companies such as Opta. However, this section was mysterious, wrongly explained and left open questions. All we know is that Smartodds uses humans to gather 'predictive' xG, but only for teams, as players' statistics are unreliable. Brentford picks the best teams, and acquires the best players from them. How they pick the best players? We'll never know.
February 22, 2023
This book challenges us to think differently about the game we took for granted. Tippett offers Expected Goals as, ‘ not simply a statistic which can be used to analyse performance. It is a philosophy that challenges the rigid, entrenched and outdated way we talk about the beautiful game.’ He highlights how conservative the game often is, closed off to differing insights and approaches where ’those lobbying for analytics to become more mainstream have been met with stiff opposition.’
Tippett challenges the ‘glaring inefficiencies’ of football’s mainstream analysis and predictions’
where it is often, ‘more important to be recognisable than to be intelligent’. The key concept at play is to give us better insight not only about what happened but also, ‘what should have happened’ a method Tippett sees as ‘an antidote to the disease of randomness.’
Much of his manifesto feels jarring at first but it is hard to disagree how, far too often, ‘in football, the result dictates the narrative.’ We as “fanalysts” are often consumed by fandom over analysis.
A central tenet of his philosophy is of providing, ‘a new, smarter language with which fans, pundits and players can talk about football.’You will baulk at this approach then reflect and realise that Tippet is arming us with a new perspective to see a game we thought we knew so well with fresh eyes.
March 22, 2023
This is a great introduction to the latest development in football analysis: Expected Goals.
Tippet explains how XG is calculated and why this statistic is important in analysing football results, teams and players.
The most interesting elements of this text explore the Justice Table that shows were teams deserve to be. Interestingly, it debunks the old adage that "the table doesn't lie". The justice table uses XG and expected points XP to work out where teams should be in the table. It really helps to highlight how important luck is in football.
The teams who have been quickest to adopt XG as a method of scouting (most notably Brentford) have achieved success so there is clearly a benefit there. Brentford and their owners methods have to be begrudgingly admired for the way they have overachieved through the use of XG.
The parts about gambling and how to make money were the least interesting as that isn't why I watch football. It seems like only the rich syndicates will ever make.money from that.
Overall this is a really interesting insight into XG that should be read by the football fan who wants to be informed rather than just opinionated.
Tippet explains how XG is calculated and why this statistic is important in analysing football results, teams and players.
The most interesting elements of this text explore the Justice Table that shows were teams deserve to be. Interestingly, it debunks the old adage that "the table doesn't lie". The justice table uses XG and expected points XP to work out where teams should be in the table. It really helps to highlight how important luck is in football.
The teams who have been quickest to adopt XG as a method of scouting (most notably Brentford) have achieved success so there is clearly a benefit there. Brentford and their owners methods have to be begrudgingly admired for the way they have overachieved through the use of XG.
The parts about gambling and how to make money were the least interesting as that isn't why I watch football. It seems like only the rich syndicates will ever make.money from that.
Overall this is a really interesting insight into XG that should be read by the football fan who wants to be informed rather than just opinionated.
This entire review has been hidden because of spoilers.
August 13, 2023
Expected Goals (xG) is a really useful method for calculating the likelihood that a shot will result in a goal. Basically, shots from central areas inside the box when the ball is on the ground have the highest percentage chance of resulting a goal; conversely, long distance shots from wide areas have very little chance of resulting in a goal. (But don't tell that to the parents that wanted me to encourage their kid to take those long shots at every chance. 🤦🏻)
I use a version of this approach in my own coaching. I always want to help my players find the best possible spaces in which to create the most dangerous possible chances. From that perspective, this book and xG approach is helpful.
However, I would've liked a more detailed description of how xG is actually calculated rather than just the categories used (e.g., location of the shot, strong vs. weak foot, cross vs. entry pass, air vs. ground, etc.). Plus, there are a bunch of grammatical errors, and that drives me nuts.
But still an interesting read!
I use a version of this approach in my own coaching. I always want to help my players find the best possible spaces in which to create the most dangerous possible chances. From that perspective, this book and xG approach is helpful.
However, I would've liked a more detailed description of how xG is actually calculated rather than just the categories used (e.g., location of the shot, strong vs. weak foot, cross vs. entry pass, air vs. ground, etc.). Plus, there are a bunch of grammatical errors, and that drives me nuts.
But still an interesting read!
November 6, 2021
Read it from start to finish in the course of a single 2 hour flight. The writer simply doesn’t have enough insight to be able to fill a book on this subject so he rather painfully drags out every single sentence, paragraph and chapter to hit the necessary page count.
Endless repetition, superfluous explanations, and an unbearable style of finding the longest possible way to say absolutely anything. Once he’d exhausted the limits there, he then fills more pages with utterly irrelevant information, such as the structure of a betting company and then Brentford FC.
When that still wasn’t enough, he resorted to all the classic tactics of any high school student: multiple graphs, large font and generous line spacing.
I gave it two stars rather than one because ultimately I have come away with a better understanding of xG. But for anyone else, you could achieve the same in about 15 minutes by reading a couple of explanations online.
Endless repetition, superfluous explanations, and an unbearable style of finding the longest possible way to say absolutely anything. Once he’d exhausted the limits there, he then fills more pages with utterly irrelevant information, such as the structure of a betting company and then Brentford FC.
When that still wasn’t enough, he resorted to all the classic tactics of any high school student: multiple graphs, large font and generous line spacing.
I gave it two stars rather than one because ultimately I have come away with a better understanding of xG. But for anyone else, you could achieve the same in about 15 minutes by reading a couple of explanations online.
June 20, 2021
This is a nice introductory guide to xG, although if you are aware of its existence and like it, there is a limited amount to take from this.
There is a lot of padding out of ideas and repetition which feels like it adds 25% to the book.
I found Expected points and the standard deviation chapter interesting and I understand this now rather than just trusting the outcome of a xP table.
There was some interest around Brentford’s methodology but it lacked detail as the key information is kept secret by the owner.
I thought this would provide insight into valuing players and recruitment techniques but it was fairly obvious stuff.
It’s clearly written to appeal to the general fan who wants to know a bit more, rather than someone that has already embraced data in their footballing lexicon.
There is a lot of padding out of ideas and repetition which feels like it adds 25% to the book.
I found Expected points and the standard deviation chapter interesting and I understand this now rather than just trusting the outcome of a xP table.
There was some interest around Brentford’s methodology but it lacked detail as the key information is kept secret by the owner.
I thought this would provide insight into valuing players and recruitment techniques but it was fairly obvious stuff.
It’s clearly written to appeal to the general fan who wants to know a bit more, rather than someone that has already embraced data in their footballing lexicon.
February 15, 2024
The topic is interesting and growing, and perhaps good for people only just discovering the concept of xG. However, unfortunately, I felt the book was not written particularly well. There was too much repetition and I also felt it was not balanced enough view on the topic. I didn’t feel like I learnt much new from the book, and I think there’s not always appropriate context applied to some of the examples used. For example the author would often claim that a certain team deserved to win a game because they had a slightly higher xG. In this example the author fails to apply context to this, fails to apply other advanced metrics and also fails to talk about things like gametsate. I did learn some interesting new things, but not enough for me personally
February 26, 2021
Interesting concept and I have learned a lot from reading this book, however, it is a bit unfocused and clearly not proof read. Really interesting insights are often lost on the reader by virtue of oblivious repetition. Example being the metaphor of the Brentford leadership team and hands on a clock. This is mentioned and then repeated almost verbatim on next page. Having read this I do feel more informed about not only the expected goals philosophy but also the wider repercussions of this methodology but it feels like the content has been padded out to meet a word count. Potentially fascinating book but relatively poorly executed.
March 2, 2024
Clear explanation of Expected Goals (xG). Also contains chapter on how Brentford FC uses Moneyball insights.
Very good explanation why teams with the same xG might have different expected points. Team Coin with 4 shots and 50% chance to score per shot (xG=2) versus Team Die with 12 shots and 16% chance to score per shot (xG=2):
After conducting thousands of simulations of the match between Team Coin and Team Die, they discovered that Team Coin won 40% of the games, Team Die won 36%, and a draw occurred 24% of the time.
when two teams hold the same XG score against one another, it is the team who amassed fewer shots at goal who is more likely to win
Very good explanation why teams with the same xG might have different expected points. Team Coin with 4 shots and 50% chance to score per shot (xG=2) versus Team Die with 12 shots and 16% chance to score per shot (xG=2):
After conducting thousands of simulations of the match between Team Coin and Team Die, they discovered that Team Coin won 40% of the games, Team Die won 36%, and a draw occurred 24% of the time.
when two teams hold the same XG score against one another, it is the team who amassed fewer shots at goal who is more likely to win
July 23, 2020
It was fine, but not really what I expected. It would've been better titled, "Expected Goals for Dummies" - which can be a really useful and interesting book, but one I wouldn't have read as someone who's fairly familiar with expected goals. The analysis is fine - sometimes great sometimes poor - and the writing is clear and concise.
If you're looking to introduce yourself to football analytics or expected goals, specifically, I would definitely recommend the book. If you're someone who's fairly familiar with the concepts and ideas, I would look elsewhere.
If you're looking to introduce yourself to football analytics or expected goals, specifically, I would definitely recommend the book. If you're someone who's fairly familiar with the concepts and ideas, I would look elsewhere.
August 5, 2020
An interesting overview of the concept of xG and how it evolved, but it does feel like it only scratched the surface. There’s no discussion about xG’s accuracy as a predictive tool, only a repeated assertion that it is the best. There are plenty of insights, and the chapter on Brentford’s transfer dealings was really eye-opening. But there’s not a huge amount of detail on how the xG-based transfers notably improved their performance on the pitch.
Oh, and a word on repetition: the author loves to repeat and rehash the same basic principles or anecdotes over and over again. We get it.
Oh, and a word on repetition: the author loves to repeat and rehash the same basic principles or anecdotes over and over again. We get it.
January 11, 2021
There’s some interesting analysis of how stats can be used for transfers and what xG actually means, but the book is repetitive, badly edited, unnecessarily polemical, and reads as a puff piece for Smartodds/Matthew Benham. There are also a number of basic factual errors which come from it being an unedited opinion piece that is condescending to casual fans. Would love a much deeper analysis into how clubs use data to analyse players’ performances and potential transfers.
May 31, 2023
I have a pretty good understanding of xG, what the purpose is and what it does and was hoping for a bit of a history lesson and how it really came about and is calculated.
What this book actually is, is a repetitive, rambling body of text that comes across as extremely condescending towards the average football fan - essentially saying that anybody who is unwilling to learn about xG is a thicko.
Avoid.
What this book actually is, is a repetitive, rambling body of text that comes across as extremely condescending towards the average football fan - essentially saying that anybody who is unwilling to learn about xG is a thicko.
Avoid.
January 13, 2021
As good as any other pop science book, explains the basic machinery of the expected goals metric and shows off its consequences. I didn't gain any knew knowledge regarding how the metric actually worked/ how the data to measure it was gathered, but there were numerous insights in terms of what it had to say regarding certain players and teams as well as its use by betting firms.
November 5, 2021
This could easily have been whittled down into a blog post. Lots of repetition without building a strong case in favour of xG as a useful metric.
Other sources of insight found on YouTube or football blogs do a better a job of presenting the importance of data analysis (including xG) in football.
Other sources of insight found on YouTube or football blogs do a better a job of presenting the importance of data analysis (including xG) in football.
August 26, 2022
This is a good introduction for people who are completely naive with the concept.
To those familiar with the basics of football analytics it won't say much though and I was kind of dissappointed that the author refrained from going into more technical details for fear that his readership may not be able to follow.
To those familiar with the basics of football analytics it won't say much though and I was kind of dissappointed that the author refrained from going into more technical details for fear that his readership may not be able to follow.
October 2, 2022
A very interesting statistical approach to football metrics, particularly regarding the 'moneyball' exposition of Brentford FC and the use of xG over results as a measure of player/team performance.
This book needs another round of proofreading though, there's way too many spelling and grammatical mistakes, hence the 4 star rating.
This book needs another round of proofreading though, there's way too many spelling and grammatical mistakes, hence the 4 star rating.
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