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Football Hackers: The Science and Art of a Data Revolution
The future of football is now. Football's data revolution has only just begun. The arrival of advanced metrics and detailed analysis is already reshaping the modern game. We can now fully assess player performance, analyse the role of luck and measure what really leads to victory. There is no turning back. Now the race is on between football's wealthiest clubs and a group of outsiders, nerds and rule-breakers, who are turning the game on its head with their staggering innovations. Winning is no longer just about what happens out on the pitch, it's now a battle taking place in boardrooms and on screens across international borders with the world's brightest minds driving for an edge over their fiercest rivals. Christoph Biermann has moved in the midst of these disruptive upheavals, talking to scientists, coaches, managers, scouts and psychologists in the world's major clubs, traveling across Europe and the US and revealing the hidden - and often jaw-dropping - truths behind the beautiful game. 'A book full of exciting ideas and inside views on modern football. The most exciting book in an exciting time for football.' Thomas Hitzlsperger
304 pages, Paperback
First published May 30, 2019
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3144 people want to read
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Displaying 1 - 30 of 119 reviews
August 3, 2019
The book is about the rise of data-driven technologies around football told through a collection of neatly stacked stories about people who strived to get a better understanding of the sport, and people who wanted to influence the sport through their unique analytical insights, disregarding their background.
The book will definititely help you look at the game more objectively, helping you to factor out the role of chance. More importantly, it helps develop a more tolerant attitude towards singular events, or a series of them which can sometimes span through the better part of a season!
The author also shows why football's complexity makes it extremely hard for a Moneyball-like model to dominate to the level that it does in other major sports.
The author's range of experiences with people from different backgrounds and tiers of the leagues is impressive. I particularly enjoyed the author throwing light on the entrepreneurial efforts of these people along with their technical approaches. His love for the sport clearly shows up in his writing, although I would have preferred some of the subsequent stories to be more crisply written.
It's a must read for anyone who follows the sport. I hope it inspires someone do a Freakonomics for football myths using data-driven analyses.
The book will definititely help you look at the game more objectively, helping you to factor out the role of chance. More importantly, it helps develop a more tolerant attitude towards singular events, or a series of them which can sometimes span through the better part of a season!
The author also shows why football's complexity makes it extremely hard for a Moneyball-like model to dominate to the level that it does in other major sports.
The author's range of experiences with people from different backgrounds and tiers of the leagues is impressive. I particularly enjoyed the author throwing light on the entrepreneurial efforts of these people along with their technical approaches. His love for the sport clearly shows up in his writing, although I would have preferred some of the subsequent stories to be more crisply written.
It's a must read for anyone who follows the sport. I hope it inspires someone do a Freakonomics for football myths using data-driven analyses.
April 9, 2022
Thoroughly enjoyable and insightful read. I thought it would be a book “just” on statistics in football, but it was so much more. As all data and statistical analysis should be, it was contextualised alongside the modern history of this growing aspect of the game, and struck a balance between the traditional approach to analysis in football, and the more modern advanced statistical analysis. Written by someone who clearly loves the game, and wants to know more about it - and I’d highly recommend the book to anyone who identifies as such.
September 10, 2019
First off, the book is pretty poorly edited." There are a bunch of annoying grammar mistakes (simple things every now and then like substituting “that” for “which) and redundancies throughout the text (I am not sure how much of this is down to the translation from English to German). Some thoughts that don’t really get wrapped up properly and the subject tends to jump around occasionally. He sometimes gets off on tangents and un-needed details which can cause you forget the subject of the chapter. It's not that the side topics he discusses are bad, they would just be better utilized as footnotes so they don't fill up several paragraphs and cause the topic of the chapter to appear somewhat disjointed. Because of this, the anecdotal portions suffer a little bit.
But if you can push past these errors there is a LOT of good and useful stuff to be found. The book does a good job of making use of Danny Kahnemann and Amos Tversky’s work into decision theory and heuristics & biases (I got all excited when the author mentioned them because I had just barely finished the Undoing Project). He makes soccer stats very approachable and easy to grasp. He also explains how every metric for judging performance can be put into practical application. Its filled with tons of graphs and data sets (as you would expect). Aside from the main focus of the book - the more recent innovations in soccer data analytics (xG plots, spatial tracking, xGA, xA, PPDA, etc.) - there is not a whole lot that will be new to you if you have already read something like soccernomics.
But if you can push past these errors there is a LOT of good and useful stuff to be found. The book does a good job of making use of Danny Kahnemann and Amos Tversky’s work into decision theory and heuristics & biases (I got all excited when the author mentioned them because I had just barely finished the Undoing Project). He makes soccer stats very approachable and easy to grasp. He also explains how every metric for judging performance can be put into practical application. Its filled with tons of graphs and data sets (as you would expect). Aside from the main focus of the book - the more recent innovations in soccer data analytics (xG plots, spatial tracking, xGA, xA, PPDA, etc.) - there is not a whole lot that will be new to you if you have already read something like soccernomics.
February 21, 2022
The first time we watch football, we probably see it as twenty people running frenzied after a ball. At some point, you may notice the nuances, the subtle tactics, the mazy runs and the different ways athletes control the ball.
Christoph Biermann makes sure you see past this as well. Forget boomerisms like "tenacity" or "grit". They didn't win because "they wanted it more" or they were "in form"
What really matters is the data: the dangerousity, the npxG, the Pressure Passing Efficiency Index. Of course, there's a tremendous amount of sheer luck involved. But Biermann tells accounts of hundreds of people who attempt to situate football analytics away from fate. The end-product is a cold efficient model that dives deeper into the game, free from cognitive biases and kismet.
Christoph Biermann makes sure you see past this as well. Forget boomerisms like "tenacity" or "grit". They didn't win because "they wanted it more" or they were "in form"
What really matters is the data: the dangerousity, the npxG, the Pressure Passing Efficiency Index. Of course, there's a tremendous amount of sheer luck involved. But Biermann tells accounts of hundreds of people who attempt to situate football analytics away from fate. The end-product is a cold efficient model that dives deeper into the game, free from cognitive biases and kismet.
January 30, 2023
If you are interested in data's growing use in football, this is simply a must read. No other book comes close.
July 19, 2019
A very interesting book about the various ways in which analysts and coaches are attempting to use the increasing amount of data available to them.
It appears there is no 'one' model for assessing players but rather multiple ways of interrogating the data according to the philosophy of the analysts and coaches.
In my view, use of such data is an aid to judgement and not a replacement for it. And interestingly that's how Borussia Dortmund used it under Klopp.
A very worthwhile read
It appears there is no 'one' model for assessing players but rather multiple ways of interrogating the data according to the philosophy of the analysts and coaches.
In my view, use of such data is an aid to judgement and not a replacement for it. And interestingly that's how Borussia Dortmund used it under Klopp.
A very worthwhile read
March 22, 2020
Highly insightful for someone who wants to understand the game from a different perspective. However, certain sections seemed superficial and lacked detailed explanations.
"Data tells a story of the game - not the story, but often a new and better one than the one we have all become used to."
"Data tells a story of the game - not the story, but often a new and better one than the one we have all become used to."
September 20, 2021
If you love football (soccer) and math at the same time, you will like this book. It tells you how you can use analytics into the game.
January 29, 2023
Przez FPL siedzę dość głęboko w statystykach piłkarskich, ale i tak wyciągnąłem całą masę nowych informacji. Nawet te fragmenty, które były dla mnie oczywistością, czytało się strasznie przyjemnie i bez znużenia, w czym na pewno zasługa pióra Biermanna. Pozycja obowiązkowa dla każdego kto interesują się piłką nożną.
April 25, 2020
Es un libro que explica cómo el desarrollo del análisis de datos se ha convertido en una área que día a día genera nuevos conocimientos en el campo del fútbol.
Hay historias interesantes sobre cómo los equipos han aplicado diferentes métricas y han conseguido buenos resultados, como también otros que no han logrado lo esperado debido a lo inestable que es el fútbol.
Hay historias interesantes sobre cómo los equipos han aplicado diferentes métricas y han conseguido buenos resultados, como también otros que no han logrado lo esperado debido a lo inestable que es el fútbol.
July 16, 2022
È un bel gasare
September 6, 2023
Biermann’s book is very much the precursor to Rory Smith’s Expected Goals, but where the latter explores the chronological story of data, Biermann travels around looking at the various methods and uses being applied by clubs and includes a bit more about Midtjylland, Brighton and Brentford. Biermann also affords us to views charts and tables to compare different metrics for players across the big leagues in Europe and there is a bigger focus on his native Germany.
Biermann is open minded enough not to foist opinions on what he presenting and let us decide if things make sense or are applicable to the game. It would seem at this point in time there isn’t a clear Moneyball stat that’ll let teams play the game in a more efficient way overall, but there are likelihoods attached with every action which will correspond with the xG and other similar stats. The biggest thing appears to be with transfers completed utilising data with Brighton an early adopter of the strategy exemplified by their signing of Pascal Gross in the book.
There is plenty of crossover between the two books as they explore what is somewhat of an outsider community even as the prevalent data departments crop up in every major football club around the world.
Biermann is open minded enough not to foist opinions on what he presenting and let us decide if things make sense or are applicable to the game. It would seem at this point in time there isn’t a clear Moneyball stat that’ll let teams play the game in a more efficient way overall, but there are likelihoods attached with every action which will correspond with the xG and other similar stats. The biggest thing appears to be with transfers completed utilising data with Brighton an early adopter of the strategy exemplified by their signing of Pascal Gross in the book.
There is plenty of crossover between the two books as they explore what is somewhat of an outsider community even as the prevalent data departments crop up in every major football club around the world.
September 20, 2019
A good overview about how Clubs are starting to look at data for tactical decisions. Covers lot of breath but not enough depth.
September 8, 2020
Можно верить или не верить в XG, но нельзя отрицать, что наличие детальных данных помогает футболу. XG до сих пор не объясняет весь футбол, но это всего лишь промежуточная стадия в поисках лучшей метрики, которая позволит выйти футболу на новый уровень. Ибо инновации не случаются сразу.
October 2, 2019
Interesting but lacks depth, especially for those already interested in the soccer analytics space.
August 11, 2020
For anyone, like me, who thought that analytics and football do not mix well, this book is really an eye opener. Not only do they blend well but also achieve good results. The book presents some new metrics devised to analyze player and club performance. The initial goal was simply to help with odds and betting but, afterwards, some clubs started to embrace a data-driven approach to have answers for questions like: How to choose a new player for your club? We have lost 3 games in a row. Are we that bad or simply out of luck? Are we really efficient when we have ball possession? As football is a very conservative (and gut based) sport, it is difficult to push for an analytical approach as told by some of the stories in the book. Overall, it was a nice read and made me put a couple of other books/articles about the subject on my radar.
March 14, 2020
These are the things I learnt from this book or strated to think about:
How do you rate football players on their performances? As Biermann demonstrates journalists (professional football ones) differ in their judgements from 2 to 5 during one single game.
How would that then work in refereeing - how do you really make a difference between a good referee and a great one as subjective feelings are always misleading.
Why really good teams go through bad patches even if they are not playing that badly?
Or why then some good referees go though bad games and decisions?
Is there a fairer way to measure the quality of a team performances over the result or standard things like possession and attempts of goal. Something like Expected Points or Expected Goals?
To be successful you have two ways to go about it - either be the best in the business in whatever field you are in or try to solve the issue from a completely different angle. Like in high-jumping Dick Fosbury reverted to the now universally used "flop" style.
The biggest change in football and how it is understood and interpreted has come from the rise of video analyses. Firstly it has enabled brilliant coaches like Guardiola or Van Gaal or Tuchel or Klopp to study extensive videos on their oppositions and their own team performances to come up with new ways of succeeding. It has also enabled them to learn from other coaches and derive how successful their methods are.
Secondly they now have material to show the players exactly what they want them to see and explain their methods. Gone are the days when "tactical training" required tedious sit-throughs of whole games. With the help of video analysts this has now been cut significantly to only those moments that matter.
FC Bayerns Head of Department of Match Analysis (8 people) Michael Niemeyer says: "For me a good coach is also a good analyst"
It is fascinating though that if in 2010 when video analyses and big data really went widespread - the world of soccer statistics seemed to be the future. However today still the big leap into big data and statistics has not happened. There are a few teams making use of it (like FC Midtjylland in Denmark as one example.), but generally football looks at it with suspicion.
One of the problems of football data has been its non-uniformity. Numbers are gathered but not in the same way and not measuring the same exact things - thus they are not always reliable. Or you can look at statistics from a match (Like Brazil vs. Germany in 2014 WC semi-final 1-7) and see that Brazil won all of the statistical battles like possession, shots, tackles, corners, dangerous attacks and still suffered the heaviest defeat in the WC semi-finals ever.
In short the answer to using statistics then is to collect even more data, and try to analyze it from others aspects and from different angles. Come up with models that really demonstrate effectiveness on the field of play. "Packing" is one such possible metric. For example in the EURO2016 34 of 51 games were won by teams who had bypassed more players (essence of packing) than the opponents and only 3 teams lost and there is a much stronger correlation between packing and winning than between possession or passing stats. Another similar metric is "controlling space" (how much space you have around you when you receive the ball and how much space you allow your opposition when they get the ball) and "dangerousity" (how much danger did a team create and how much were they exposed to).
As computers learn they will do all the measuring work and provide data which then can be interpreted and analyzed and put to use by clubs and coaches.
One field in football that already today heavily relies on data is scouting and the best scouts (using the best systems) are heavily sought after like Sven Mislintnat (from Borussia to Arsenal).
Cognitive football
Hoffenheim coach Nagelsmann makes his training sessions so complicated that his sports psychologist Jan Mayer says about the players "We want their head to spin during training" - and you only learn when your brain has to work hard.
Sandro Wagner on Nagelsmann "He takes a complicated game, takes it apart into different sections, rehearses those and then puts it all back together, step by step"
Together with SAP Hoffenheim have created game apps that aim to improve perception, understanding and decision-making for the players. Some players like goalkeepers come in twice a week, youth team once a week, outfield players when they want to.
Another really interesting trend (used by Midtjylland and Tuchel for example) is psychological profiling of players and how different players work together. So that your team needs a balanced amount of fighters, artists, engineers and social workers on the field (similar to Belbin).
Future strategies
Really interesting idea is that of Ghosting - a game is played and based on the data feed into the computer previously - the computer offers an ideal route for the player to take in that situation. So for a defender to either close down the opposition or stay put on the 16m area line. And you can see live the difference between the two. Same can be applied to refereeing if we know from which positions referees make the best calls - so with ghosting we could teach referees where to position.
It is clear however that the more detailed the analyses gets, the more expensive it gets and the danger is that the top clubs (Liverpool, Bayern etc) buy the systems and work with them behind closed doors so taking them out of the public domain. Could that happen in refereeing so that the smaller countries will stay more behind the leading ones?
How do you rate football players on their performances? As Biermann demonstrates journalists (professional football ones) differ in their judgements from 2 to 5 during one single game.
How would that then work in refereeing - how do you really make a difference between a good referee and a great one as subjective feelings are always misleading.
Why really good teams go through bad patches even if they are not playing that badly?
Or why then some good referees go though bad games and decisions?
Is there a fairer way to measure the quality of a team performances over the result or standard things like possession and attempts of goal. Something like Expected Points or Expected Goals?
To be successful you have two ways to go about it - either be the best in the business in whatever field you are in or try to solve the issue from a completely different angle. Like in high-jumping Dick Fosbury reverted to the now universally used "flop" style.
The biggest change in football and how it is understood and interpreted has come from the rise of video analyses. Firstly it has enabled brilliant coaches like Guardiola or Van Gaal or Tuchel or Klopp to study extensive videos on their oppositions and their own team performances to come up with new ways of succeeding. It has also enabled them to learn from other coaches and derive how successful their methods are.
Secondly they now have material to show the players exactly what they want them to see and explain their methods. Gone are the days when "tactical training" required tedious sit-throughs of whole games. With the help of video analysts this has now been cut significantly to only those moments that matter.
FC Bayerns Head of Department of Match Analysis (8 people) Michael Niemeyer says: "For me a good coach is also a good analyst"
It is fascinating though that if in 2010 when video analyses and big data really went widespread - the world of soccer statistics seemed to be the future. However today still the big leap into big data and statistics has not happened. There are a few teams making use of it (like FC Midtjylland in Denmark as one example.), but generally football looks at it with suspicion.
One of the problems of football data has been its non-uniformity. Numbers are gathered but not in the same way and not measuring the same exact things - thus they are not always reliable. Or you can look at statistics from a match (Like Brazil vs. Germany in 2014 WC semi-final 1-7) and see that Brazil won all of the statistical battles like possession, shots, tackles, corners, dangerous attacks and still suffered the heaviest defeat in the WC semi-finals ever.
In short the answer to using statistics then is to collect even more data, and try to analyze it from others aspects and from different angles. Come up with models that really demonstrate effectiveness on the field of play. "Packing" is one such possible metric. For example in the EURO2016 34 of 51 games were won by teams who had bypassed more players (essence of packing) than the opponents and only 3 teams lost and there is a much stronger correlation between packing and winning than between possession or passing stats. Another similar metric is "controlling space" (how much space you have around you when you receive the ball and how much space you allow your opposition when they get the ball) and "dangerousity" (how much danger did a team create and how much were they exposed to).
As computers learn they will do all the measuring work and provide data which then can be interpreted and analyzed and put to use by clubs and coaches.
One field in football that already today heavily relies on data is scouting and the best scouts (using the best systems) are heavily sought after like Sven Mislintnat (from Borussia to Arsenal).
Cognitive football
Hoffenheim coach Nagelsmann makes his training sessions so complicated that his sports psychologist Jan Mayer says about the players "We want their head to spin during training" - and you only learn when your brain has to work hard.
Sandro Wagner on Nagelsmann "He takes a complicated game, takes it apart into different sections, rehearses those and then puts it all back together, step by step"
Together with SAP Hoffenheim have created game apps that aim to improve perception, understanding and decision-making for the players. Some players like goalkeepers come in twice a week, youth team once a week, outfield players when they want to.
Another really interesting trend (used by Midtjylland and Tuchel for example) is psychological profiling of players and how different players work together. So that your team needs a balanced amount of fighters, artists, engineers and social workers on the field (similar to Belbin).
Future strategies
Really interesting idea is that of Ghosting - a game is played and based on the data feed into the computer previously - the computer offers an ideal route for the player to take in that situation. So for a defender to either close down the opposition or stay put on the 16m area line. And you can see live the difference between the two. Same can be applied to refereeing if we know from which positions referees make the best calls - so with ghosting we could teach referees where to position.
It is clear however that the more detailed the analyses gets, the more expensive it gets and the danger is that the top clubs (Liverpool, Bayern etc) buy the systems and work with them behind closed doors so taking them out of the public domain. Could that happen in refereeing so that the smaller countries will stay more behind the leading ones?
March 15, 2025
An absolute triumph! Thank you Christoph - an immense amount of research completed. A joy to read as it is written with humour. After you read this, I would highly recommend James Tippett “xGenius” as a follow on book which stands on the shoulder of Christoph’s superb book
April 15, 2025
A fantastic side of football, written in the write amount of detail and wonder.
March 26, 2022
Es un poco extraño que este libro de Christoph Biermann llamara mi atención cuando me topé con el en la sección de remates de mi librería local. No soy, ni por accidente, un aficionado del fútbol. Los goles no me inspiran ninguna sensación sublime ni tampoco me apasiona discutir las mejores estrategias en la cancha, por lo que suelo esquivar las grandes polémicas del balón, como la reciente decisión del árbitro en el partido entre Perú y Uruguay en Montevideo.
Sobre tecnologías de información, análisis de probabilidad y la 'revolución de la data', como la llama Biermann en este libro, tampoco estaba muy enterado. Quizá fue esa doble ignorancia la que me atrajo a la posibilidad de introducirme en ambos temas a través de una crónica de las profundas transformaciones que ocurren en el paisaje deportivo en los últimos quinquenios. Este libro es un relato de un experimentado periodista sobre el advenimiento y proliferación de variopintas métricas y modelos estadísticos para hacer otorgar sentido a sets de datos y lograr predecir resultados con un poquito más de certeza frente a la "eterna predisposición del fútbol a los eventos aleatorios" (p. 187)
A lo largo del libro el autor se entrevista con varios de los protagonistas de esta revolución, llevándonos alternadamente por famosos estadios, canchas de clubs de segunda división y salas de conferencias de startups en Alemania, Inglaterra y los EEUU para presentarnos a una serie de iluminados personajes. Asi conocemos las historias de innovadores DTs y outsiders --entre académicos advenedizos, blogueros aficionados y exiliados de otros deportes más matematizados como el basket y la Fórmula 1-- dispuestos a acabar con los sesgos cognitivos que dominan las discusiones, y no pocas veces, decisiones futbolísticas.
Aunque la informacion sobre victorias y derrotas, goles acumulados, pases exitosos, tiros atajados y tiempo de posesión de pelota nunca ha sido escasa, la tabulación de estos datos no ha sido siempre esclarecedora. Hasta ahora. Contra las falaces expectativas de que un equipo ganador necesariamente repetirá el éxito con facilidad, Biermann contrapone la percepción del fútbol como un deporte "parecido al ajedrez pero con dados" (p. 46). ¿Cómo entender, entonces, el azar? Apertrechados con sensores corporales, múltiples cámaras a lo largo de la cancha y software de análisis espacial, los nuevos "hackers" tratan de dar vuelta a la incertidumbre con modelos que le otorgan nuevo sentido a la data acumulada. Así, métricas como el "Peligro Esperado" u "Oportunidades Creadas" cruzan varias fuentes de información para producir cifras que permiten cuantificar y comparar dimensiones del juego que antes podían resultas imperceptibles o confundidas en un vago sentido de suerte o incluso destino.
La métrica que más aparece en el libro es una que no sé como traducir. "Packing", inventada por el ex-jugador Stefan Reinartz es un buen ejemplo de como la data está transformando el deporte. Segun explica Biermann, packing mide la calidad de un pase a partir del número de oponentes gambeteados por un jugador determinado. Biermann nos cuenta la historia de sus origenes, así como su popularización tras ser adoptada por un popular comentarista televisivo. Al extenderse más allá de los camerines de los técnicos deportivos, las métricas han transformado no solo la estrategia de los equipos, sino también la manera en que se discute el juego entre aficionados y tahúres profesionales.
Como lección de sus observaciones y entrevistas en el campo, Biermann concluye que la data, ya sea cruda o cocida mediante estadísticos que condensan en cifras objetivas diversos aspectos del juego, no es suficiente para tomar decisiones correctas ni para juzgar con justicia a un equipo o jugador individual. Se necesita siempre del contexto para su correcta interpretacion (p. 166) y, mas que números mágicos que desentrañen el secreto final del éxito, la data debe ser utilizada como un soporte de pequeñas mejoras sostenidas en el tiempo.
En general se trata de un libro entretenido e informativo, producto de un erudito del deporte. Incluye muchas referencias a jugadores históricos y equipos de diversas ligas que los aficionados, estoy seguro, reconoceran inmeditamente. Por mi parte, lo encontré a veces un poco excesivo en su recurso a la anécdota. Podría haber sido editado un poco más, ya que algunos capítulos son excesivamente largos y contienen muchas digresiones que distraen del tema central.
Sobre tecnologías de información, análisis de probabilidad y la 'revolución de la data', como la llama Biermann en este libro, tampoco estaba muy enterado. Quizá fue esa doble ignorancia la que me atrajo a la posibilidad de introducirme en ambos temas a través de una crónica de las profundas transformaciones que ocurren en el paisaje deportivo en los últimos quinquenios. Este libro es un relato de un experimentado periodista sobre el advenimiento y proliferación de variopintas métricas y modelos estadísticos para hacer otorgar sentido a sets de datos y lograr predecir resultados con un poquito más de certeza frente a la "eterna predisposición del fútbol a los eventos aleatorios" (p. 187)
A lo largo del libro el autor se entrevista con varios de los protagonistas de esta revolución, llevándonos alternadamente por famosos estadios, canchas de clubs de segunda división y salas de conferencias de startups en Alemania, Inglaterra y los EEUU para presentarnos a una serie de iluminados personajes. Asi conocemos las historias de innovadores DTs y outsiders --entre académicos advenedizos, blogueros aficionados y exiliados de otros deportes más matematizados como el basket y la Fórmula 1-- dispuestos a acabar con los sesgos cognitivos que dominan las discusiones, y no pocas veces, decisiones futbolísticas.
Aunque la informacion sobre victorias y derrotas, goles acumulados, pases exitosos, tiros atajados y tiempo de posesión de pelota nunca ha sido escasa, la tabulación de estos datos no ha sido siempre esclarecedora. Hasta ahora. Contra las falaces expectativas de que un equipo ganador necesariamente repetirá el éxito con facilidad, Biermann contrapone la percepción del fútbol como un deporte "parecido al ajedrez pero con dados" (p. 46). ¿Cómo entender, entonces, el azar? Apertrechados con sensores corporales, múltiples cámaras a lo largo de la cancha y software de análisis espacial, los nuevos "hackers" tratan de dar vuelta a la incertidumbre con modelos que le otorgan nuevo sentido a la data acumulada. Así, métricas como el "Peligro Esperado" u "Oportunidades Creadas" cruzan varias fuentes de información para producir cifras que permiten cuantificar y comparar dimensiones del juego que antes podían resultas imperceptibles o confundidas en un vago sentido de suerte o incluso destino.
La métrica que más aparece en el libro es una que no sé como traducir. "Packing", inventada por el ex-jugador Stefan Reinartz es un buen ejemplo de como la data está transformando el deporte. Segun explica Biermann, packing mide la calidad de un pase a partir del número de oponentes gambeteados por un jugador determinado. Biermann nos cuenta la historia de sus origenes, así como su popularización tras ser adoptada por un popular comentarista televisivo. Al extenderse más allá de los camerines de los técnicos deportivos, las métricas han transformado no solo la estrategia de los equipos, sino también la manera en que se discute el juego entre aficionados y tahúres profesionales.
Como lección de sus observaciones y entrevistas en el campo, Biermann concluye que la data, ya sea cruda o cocida mediante estadísticos que condensan en cifras objetivas diversos aspectos del juego, no es suficiente para tomar decisiones correctas ni para juzgar con justicia a un equipo o jugador individual. Se necesita siempre del contexto para su correcta interpretacion (p. 166) y, mas que números mágicos que desentrañen el secreto final del éxito, la data debe ser utilizada como un soporte de pequeñas mejoras sostenidas en el tiempo.
En general se trata de un libro entretenido e informativo, producto de un erudito del deporte. Incluye muchas referencias a jugadores históricos y equipos de diversas ligas que los aficionados, estoy seguro, reconoceran inmeditamente. Por mi parte, lo encontré a veces un poco excesivo en su recurso a la anécdota. Podría haber sido editado un poco más, ya que algunos capítulos son excesivamente largos y contienen muchas digresiones que distraen del tema central.
March 24, 2025
This is an excellent book and is applicable to just about all parts of life.
To begin - the author introduced the concept that humans use stories to understand things. The author wrote:
Which means that many times, a single narrative “story” might not fully explain something that has multiple inputs. In the game of football, things ranging from wind, grass condition, the player’s mood, weather, the crowd etc will all have an impact on the game result. Yet, human’s single mindedness of focusing on a single-narrative and cohesive story means people can be very opinionated with only one variable in mind and filter out anything else. The author wrote:
The author named the first chapter “Why Opinions are Annoying” because due to the structure problem of human narratives, opinions are often worse than useless because there are too many unknown unknowns in “expert opinions” as well as too much emotion is woven into those opinions, the author wrote:
This obviously applies to all ways of life: people always believe they’re entitled to voice their opinions even though they rarely objectively measure if their opinions over a long period of time result in high accuracy (they don’t). In addition, the way they use opinions to make decisions also means that binary thinking will be the default option of the crowd: either something is good or bad, nice or terrible, the right thing to do or the wrong thing to do. Uncertainties do not factor into the decision making process because opinions are not probabilistic but rather deterministic.
The way our brain works also means that we only focus on things that we remember the most. As if the major turning point of a word event lies on just a few focal points (rather than the build up beforehand) for a simple reason that we often forget the build up - we only remember what we remember, after all.
The book’s many ideas are similar to what Annie Duke has hashed out on her poker themed book, Thinking in Bets thus I won’t elaborate further. The book also explained why good football scorers tend to have higher likelihood of scoring, the author wrote:
(Warren Buffett also talked extensively about a good baseball player only hit the ball when odds are in his favor, which would apply to all parts of life.)
To begin - the author introduced the concept that humans use stories to understand things. The author wrote:
There is a deep-seated human need to mould everything into one sweeping, seemingly coherent narrative… Humans are hard-wired to make sense of things by telling stories, even if that’s rarely the most helpful way to analyse problems and arrive at solutions.
Which means that many times, a single narrative “story” might not fully explain something that has multiple inputs. In the game of football, things ranging from wind, grass condition, the player’s mood, weather, the crowd etc will all have an impact on the game result. Yet, human’s single mindedness of focusing on a single-narrative and cohesive story means people can be very opinionated with only one variable in mind and filter out anything else. The author wrote:
We tend to filter out information that doesn’t chime with pre-existing notions.
The author named the first chapter “Why Opinions are Annoying” because due to the structure problem of human narratives, opinions are often worse than useless because there are too many unknown unknowns in “expert opinions” as well as too much emotion is woven into those opinions, the author wrote:
... a game made of emotions, is rarely prone to too much rational discourse; arguments are mostly informed by feelings rather than facts.
This obviously applies to all ways of life: people always believe they’re entitled to voice their opinions even though they rarely objectively measure if their opinions over a long period of time result in high accuracy (they don’t). In addition, the way they use opinions to make decisions also means that binary thinking will be the default option of the crowd: either something is good or bad, nice or terrible, the right thing to do or the wrong thing to do. Uncertainties do not factor into the decision making process because opinions are not probabilistic but rather deterministic.
The way our brain works also means that we only focus on things that we remember the most. As if the major turning point of a word event lies on just a few focal points (rather than the build up beforehand) for a simple reason that we often forget the build up - we only remember what we remember, after all.
The book’s many ideas are similar to what Annie Duke has hashed out on her poker themed book, Thinking in Bets thus I won’t elaborate further. The book also explained why good football scorers tend to have higher likelihood of scoring, the author wrote:
... Ronaldo was scoring eight to ten more goals than the average striker per person, simply by taking up better shooting positions. The numbers for other top strikers follow a similar pattern. They’re top because they shoot often, and form positions with high probabilities of success.
(Warren Buffett also talked extensively about a good baseball player only hit the ball when odds are in his favor, which would apply to all parts of life.)
April 15, 2020
This fell somewhere between Soccernomics and one of Michael Calvin's books, as Biermann explored the metrics that are now being used to analyse football, but also gained access to people at the vanguard of using them.
Soccernomics was the first mainstream book that looked at data to explain football, and given the frenzy to emulate the Oakland A's it is perhaps surprising that it's still seen as a bit nerdy 10 years on. As Biermann interviews many men (as he says, it's always men) involved in analytics, the reader is given the impression that clubs employ the analysts, but only a proportion actually use them. Biermann starts off the book by noting that a lot of football results can be attributed to luck, but Chris Anderson doesn't help the geeks' cause. After writing The Numbers Game he is interviewed in the book, and appears surprised that running a football club in the third tier actually involved practical aspects of the job, rather than playing Football Manager in real life. Less flippantly, the best analysis in the world still requires a coach willing to implement the ideas.
A lot of the focus was understandably on the author's homeland of Germany, but he also got access to Midtjylland as well as discussing Liverpool, and it was written well enough that it didn't matter. The section on Lucien Favre I found really interesting, and gave me the sense that analysis is partly finding patterns in data, and partly improving the metrics you generate. Packing was quite interesting, but it was also quite difficult to work out whether making it a target would improve a team's performance, or whether it was merely a reflection of performance. When fewer stats were available, possession was deemed a great KPI, before it was found that merely increasing the stat didn't improve performance in itself.
The author recommends three books as further reading, but having read all of them I think this was the best. It didn't try to draw snappy conclusions like The Numbers Game but still felt closer to the actual world of football than Soccernomics or Soccermatics. Partly this was the access, but as he related it to individual matches at times this covered the big picture and the details, and though it didn't have any explosive revelations, it did give a fascinating insight into one part of the sport.
Soccernomics was the first mainstream book that looked at data to explain football, and given the frenzy to emulate the Oakland A's it is perhaps surprising that it's still seen as a bit nerdy 10 years on. As Biermann interviews many men (as he says, it's always men) involved in analytics, the reader is given the impression that clubs employ the analysts, but only a proportion actually use them. Biermann starts off the book by noting that a lot of football results can be attributed to luck, but Chris Anderson doesn't help the geeks' cause. After writing The Numbers Game he is interviewed in the book, and appears surprised that running a football club in the third tier actually involved practical aspects of the job, rather than playing Football Manager in real life. Less flippantly, the best analysis in the world still requires a coach willing to implement the ideas.
A lot of the focus was understandably on the author's homeland of Germany, but he also got access to Midtjylland as well as discussing Liverpool, and it was written well enough that it didn't matter. The section on Lucien Favre I found really interesting, and gave me the sense that analysis is partly finding patterns in data, and partly improving the metrics you generate. Packing was quite interesting, but it was also quite difficult to work out whether making it a target would improve a team's performance, or whether it was merely a reflection of performance. When fewer stats were available, possession was deemed a great KPI, before it was found that merely increasing the stat didn't improve performance in itself.
The author recommends three books as further reading, but having read all of them I think this was the best. It didn't try to draw snappy conclusions like The Numbers Game but still felt closer to the actual world of football than Soccernomics or Soccermatics. Partly this was the access, but as he related it to individual matches at times this covered the big picture and the details, and though it didn't have any explosive revelations, it did give a fascinating insight into one part of the sport.
October 21, 2022
[4/5] This is one of those books I expected to love. I love football and data, after all. I really liked it in the end, but it didn’t start great.
The author spends a lot of time in the beginning on xG and people who created mathematical models that could not be properly presented or explained. Then gets to the norm-breakers and talks about Tuchel and Guardiola, but towards the end of that section (with the importance of set pieces) it starts getting more interesting.
The part after that is far more interesting as he dives into more advanced xG concepts, PPDA, various packing metrics, dangerosity, then the various scouting tools and finally how teams are using data and technology to improve the mental aspects of their players’ game.
It is an interesting overview (and history) of looking at football through numbers and I thought the author did really well considering his lack of knowledge in the general data/tech area. To me as an analyst it also brought up many interesting questions that seem to pop up no matter which industry you’re in - is more complex always better and how can we still get value from all of these metrics and models? How do we get from descriptive to prescriptive? How do we get the stakeholders’ buy-in?
A few years into the future, it’s interesting to see where some of the mentioned people ended up, most notably Brentford as a stable PL team, Ankersen is now at Southampton, statsbomb and Ted Knutson outgrew their then status of a blog to become a huge player in the industry and are competing with the likes of opta.
It would be nice to read an updated version of this book at some point, to see how far it has all come since the original, but for now this one is more than enough to make any football and data fan happy.
The author spends a lot of time in the beginning on xG and people who created mathematical models that could not be properly presented or explained. Then gets to the norm-breakers and talks about Tuchel and Guardiola, but towards the end of that section (with the importance of set pieces) it starts getting more interesting.
The part after that is far more interesting as he dives into more advanced xG concepts, PPDA, various packing metrics, dangerosity, then the various scouting tools and finally how teams are using data and technology to improve the mental aspects of their players’ game.
It is an interesting overview (and history) of looking at football through numbers and I thought the author did really well considering his lack of knowledge in the general data/tech area. To me as an analyst it also brought up many interesting questions that seem to pop up no matter which industry you’re in - is more complex always better and how can we still get value from all of these metrics and models? How do we get from descriptive to prescriptive? How do we get the stakeholders’ buy-in?
A few years into the future, it’s interesting to see where some of the mentioned people ended up, most notably Brentford as a stable PL team, Ankersen is now at Southampton, statsbomb and Ted Knutson outgrew their then status of a blog to become a huge player in the industry and are competing with the likes of opta.
It would be nice to read an updated version of this book at some point, to see how far it has all come since the original, but for now this one is more than enough to make any football and data fan happy.
January 5, 2021
A status report from 2019 of how football analytics is used. Many examples from German football.
A few of the things that stuck with me:
In the context of expected goals (xG), the result that the difference between Christiano Ronaldo and an avergage player is only about 2 percentage points (13.3% of his shots resulting in goals vs the league average of 11.1%, page 34). The reason he scores so many goals is that he shoots more, and from better positions, than the average player.
I also liked the graphs of how the xG changed over complete games from the 2018 World Cup. Quite illuminating, along with the figures for the match odds based on simulations of the shots (page 37 and onwards).
Also quite interesting was how Dortmund was 17:th in the table, but had had a lot of bad luck compared to all the chances they created.
There is also a lot of information on the clubs Midtjylland (Denmark) and Brentford (England) on how they are adopting "moneyball" for football. Also good was the discussion of "packing" - the number of players that are taken out by a pass or dribble, as well as the concept of "dangerosity".
Overall, a good book if you are interested in football analytics. The book meanders a bit through different subjects though, and it also feels like a snapshoot of the development at that point in time, more than a complete primer on football analytics. But that is mostly because there is a lot of development in this space.
If you are interested in football analytics, there is a course given by David Sumpter of Uppsala University that I really enjoyed. I've written about it here: https://henrikwarne.com/2020/11/25/ma...
A few of the things that stuck with me:
In the context of expected goals (xG), the result that the difference between Christiano Ronaldo and an avergage player is only about 2 percentage points (13.3% of his shots resulting in goals vs the league average of 11.1%, page 34). The reason he scores so many goals is that he shoots more, and from better positions, than the average player.
I also liked the graphs of how the xG changed over complete games from the 2018 World Cup. Quite illuminating, along with the figures for the match odds based on simulations of the shots (page 37 and onwards).
Also quite interesting was how Dortmund was 17:th in the table, but had had a lot of bad luck compared to all the chances they created.
There is also a lot of information on the clubs Midtjylland (Denmark) and Brentford (England) on how they are adopting "moneyball" for football. Also good was the discussion of "packing" - the number of players that are taken out by a pass or dribble, as well as the concept of "dangerosity".
Overall, a good book if you are interested in football analytics. The book meanders a bit through different subjects though, and it also feels like a snapshoot of the development at that point in time, more than a complete primer on football analytics. But that is mostly because there is a lot of development in this space.
If you are interested in football analytics, there is a course given by David Sumpter of Uppsala University that I really enjoyed. I've written about it here: https://henrikwarne.com/2020/11/25/ma...
July 27, 2019
Football Hackers: The Science and Art of a Data Revolution (2019) by Christoph Bierman is an excellent read about the modern application of statistics to soccer. Soccer, or football as it will be referred to from here on, is very difficult to apply statistics to. Possession, shots taken and passed made can all be deceptive.
Prior to the modern era of ubiquitous digital footage of thousands of games and the availability of cheap computing power coming up with better football statistics has not been possible. Charles Reep's simplistic counting of passes being the best known failed example. But today with annotations available for thousands of games a year being done more sophisticated analysis has become possible.
In the book Bierman talks to a number of modern football statistics innovators and describes their influence on the modern game. To anyone who is familiar with these ideas the first new metric Xg or expected goals should be familiar. But other concepts such as 'packing', PPDA, dangerousity and others are likely to be new. The book has lots of examples from Bierman's home country of Germany and quite a few from other places.
Football Hackers is well worth reading for anyone interested in how to apply statistics to a complex, flowing game. For anyone interested in getting a feel for what's coming in modern football it's highly recommended. It's also well written and flows well from concept to concept and person to person.
Prior to the modern era of ubiquitous digital footage of thousands of games and the availability of cheap computing power coming up with better football statistics has not been possible. Charles Reep's simplistic counting of passes being the best known failed example. But today with annotations available for thousands of games a year being done more sophisticated analysis has become possible.
In the book Bierman talks to a number of modern football statistics innovators and describes their influence on the modern game. To anyone who is familiar with these ideas the first new metric Xg or expected goals should be familiar. But other concepts such as 'packing', PPDA, dangerousity and others are likely to be new. The book has lots of examples from Bierman's home country of Germany and quite a few from other places.
Football Hackers is well worth reading for anyone interested in how to apply statistics to a complex, flowing game. For anyone interested in getting a feel for what's coming in modern football it's highly recommended. It's also well written and flows well from concept to concept and person to person.
March 23, 2024
This is a book that I have been looking at reading for a while now, and I finally found time to do so. Let me tell you, this is one of the best and most informative books I have ever read. I have been watching football (soccer) throughout my entire life, and over the course of 22 years, the sport has changed A LOT. Why has it changed? Data, analytics, science, arithmetic, etc. In today's game, these are all used throughout the footballing world, whether they are used for player signings, hiring a new manager, player performance, a Clubs trajectory, and so on.
Christoph Biermann gives the audience great insight on what goes on behind the scenes, and the faces that have helped change the science and art of data revolution throughout football. Labeled to some as "outsiders," these people have single handedly changed the way I, and so many others, view and approach the beautiful game. For example, you may have seen the term "xG" used more and more throughout these last few years after a match finishes, meaning expected goals. Expected goals is the probability a shot a player takes has of going in. Not always, but most of the time, this piece of data tells you which team created the better chances throughout the match. This is just one of MANY examples Christoph talks about throughout his book. As someone who is interested in becoming a manager within the beautiful game of football, this book is a great tool to have. MUST read.
Christoph Biermann gives the audience great insight on what goes on behind the scenes, and the faces that have helped change the science and art of data revolution throughout football. Labeled to some as "outsiders," these people have single handedly changed the way I, and so many others, view and approach the beautiful game. For example, you may have seen the term "xG" used more and more throughout these last few years after a match finishes, meaning expected goals. Expected goals is the probability a shot a player takes has of going in. Not always, but most of the time, this piece of data tells you which team created the better chances throughout the match. This is just one of MANY examples Christoph talks about throughout his book. As someone who is interested in becoming a manager within the beautiful game of football, this book is a great tool to have. MUST read.
October 21, 2025
This book is a reminder that while data has transformed football and sport in general, it hasn’t replaced its beauty. A Toni Kroos through ball is still art, and the numbers simply help us appreciate it even more.
Everyone in sport knows the Moneyball story, but over the years the retelling of the story has lost its important context. There are lots of factors which go into the understanding of why a team succeeds or even dominates, but do we ever get a definitive answer?
Christoph explores very well the journey that data has had throughout an industry where scouts and knowledge of the game has ruled for decades. His clear fascination and enthusiasm into the nuances of the beautiful game really resonates with me as someone who at the time of the rise of xG was very for it as a tool to further understanding the flow of a game - and it’s where the book begins and sets the tone.
Since the book was written there’s been so much more growth in this side of the game and even in the women’s game, so it was nice to understand the history of teams who have been cult heroes for success stories - your FC Midtjylland’s, your Brentford’s, your Brighton’s. I loved this books focus on rule breakers, people going against the grain even in times where others would have abandoned it all, it’s what sport is all about.
A follow up book would definitely be warranted, as so much has changed about the game in recent years. The average fan is 10x more clued up about the goings on and the tactical dynamics of modern coaching, how will this translate and shape the beautiful game in the next 10 years, where academy players have all of this available throughout their development? How has Pep’s dynasty with Man City shaped English football? Has the data around set-piece routines influenced Arsenal in the last 3 years that much or is it simply a case of lumping it to the big guy in the box?
Everyone in sport knows the Moneyball story, but over the years the retelling of the story has lost its important context. There are lots of factors which go into the understanding of why a team succeeds or even dominates, but do we ever get a definitive answer?
Christoph explores very well the journey that data has had throughout an industry where scouts and knowledge of the game has ruled for decades. His clear fascination and enthusiasm into the nuances of the beautiful game really resonates with me as someone who at the time of the rise of xG was very for it as a tool to further understanding the flow of a game - and it’s where the book begins and sets the tone.
Since the book was written there’s been so much more growth in this side of the game and even in the women’s game, so it was nice to understand the history of teams who have been cult heroes for success stories - your FC Midtjylland’s, your Brentford’s, your Brighton’s. I loved this books focus on rule breakers, people going against the grain even in times where others would have abandoned it all, it’s what sport is all about.
A follow up book would definitely be warranted, as so much has changed about the game in recent years. The average fan is 10x more clued up about the goings on and the tactical dynamics of modern coaching, how will this translate and shape the beautiful game in the next 10 years, where academy players have all of this available throughout their development? How has Pep’s dynasty with Man City shaped English football? Has the data around set-piece routines influenced Arsenal in the last 3 years that much or is it simply a case of lumping it to the big guy in the box?
March 18, 2022
I have undertaken a quest to further my knowledge of Football (soccer) from a ‘Moneyball’ perspective and was referenced this book from Soccermatics by David Sumpter. Where that book was more a Mathematicians take on Football this was truly an eye-opening overview of where Football is at as far as Analytics goes within the game. Sadly, the book was not available on Kindle so I had to purchase the paperback, making it the first physical book I have read in some time.
The author takes you on their personal journey through a quest to see if a Billy Beane can exist in the world of Football. Along the way you will see how Analytics has evolved within the game and where it is going. Concepts like the Packing, ghosting and an array of other metrics and views are brought about quite well. The author also brings up a host of innovative coaches who revolutionized the game with different outlooks on how the game should be played as well as scouting techniques used to find players to work within those systems. In addition, there is also some good reading material referenced as well.
Overall, this is a five plus star read. If you are a fan of Football and want to know more about where the game is heading this is the book to get. I have a feeling I will be reading this one a few more times and referencing it regularly.
The author takes you on their personal journey through a quest to see if a Billy Beane can exist in the world of Football. Along the way you will see how Analytics has evolved within the game and where it is going. Concepts like the Packing, ghosting and an array of other metrics and views are brought about quite well. The author also brings up a host of innovative coaches who revolutionized the game with different outlooks on how the game should be played as well as scouting techniques used to find players to work within those systems. In addition, there is also some good reading material referenced as well.
Overall, this is a five plus star read. If you are a fan of Football and want to know more about where the game is heading this is the book to get. I have a feeling I will be reading this one a few more times and referencing it regularly.
March 24, 2022
At first, I expected the book to be somewhat a copy of David Sumpter's Soccermatics , which I rated highly. It turned out to be rather interesting, with a very long chapter dedicated to a number of metrics we have tried, with various degree of success, to deconstruct the sport, chasing a dream of finding a surefire way to build a data-drive, Moneyball like success story..
One thing I do appreciate is the book's recognition for the capriciousness of the game and a complex system surrounding the pitch. The data will tell a story of the game - not the story, and most people inside and outside of the sports are still trying to understand what all these numbers are useful for. As the book suggests, the hardest part is not to come up with new concepts like Expected Goals, Packing, Dangerousity, but to be able to apply these mathematically-inspired insights in a system prone to irrationality and knee-jerk decisions.
One thing I do appreciate is the book's recognition for the capriciousness of the game and a complex system surrounding the pitch. The data will tell a story of the game - not the story, and most people inside and outside of the sports are still trying to understand what all these numbers are useful for. As the book suggests, the hardest part is not to come up with new concepts like Expected Goals, Packing, Dangerousity, but to be able to apply these mathematically-inspired insights in a system prone to irrationality and knee-jerk decisions.
October 21, 2019
This was a lovely read. The author provides a nice and concise overview of the development of new metrics to better understand football. The author brings with him a deep love of the game, a curiosity and drive to understand and explain and a human touch allowing him to really flesh out the many interesting figures he meets.
Where the area of football metrics once was the realm of a bunch of nerds, who were very willing to share their insights, football data analysis is now a competitive market, which means that the part on the most recent developments is a bit obfuscated by corporate secrecy. This is a shame, but you can’t fault the writer for this. It makes you wonder whether in ten years’ time there will be a book lifting the lid on the analyses that the world’s top football clubs are developing right now.
Where the area of football metrics once was the realm of a bunch of nerds, who were very willing to share their insights, football data analysis is now a competitive market, which means that the part on the most recent developments is a bit obfuscated by corporate secrecy. This is a shame, but you can’t fault the writer for this. It makes you wonder whether in ten years’ time there will be a book lifting the lid on the analyses that the world’s top football clubs are developing right now.
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