This is the first topic that I am starting on this forum. It is something I believe is very important with regards to the future of this club. I have not seen another topic like it on these forums. I have collected several quotes from Damien Comolli about our new policy. I urge you all to read the book ‘Moneyball’ if you have not already done so. What moneyball tries to do is to show the importance of statistics in sport and how it can be used to find value. "The whole principle is about creating value, and managing to find a player in the market who is underestimated financially compared to his stats," Comolli told Les Specialistes. Recently I saw an article in which Comolli explained that when he first started out he bought a player merely based just on statistics but it didn’t work out and he saw the error of his ways but still believes statistics are very important. "It's about creating value and making right decisions," Comolli says. "Base your decisions on something that is objective and not only subjective. And there are three aspects of that. One: The use of analytics. Two: The use of scouts. Three: Check background, check the personality and character and attitude. … I didn't invent anything. I watched how baseball teams acted. I thought it was an absolute waste of money and time and talent to not to try to use it in football." As mentioned above a lot of sabermetrics (soccernomics) is about is creating value. In moneyball they try to find undervalued players that are very cheap as they a small market baseball team. When John Henry took over the Boston Red Sox he employed the idea’s of sabermetrics but as the Red Sox are a big market team (much like Liverpool) they were able to get the best players who had the best statistics, that still representing value for money. A player may have outstanding statistics but may not represent value for money. "People seem to think, especially here in the UK, the 'Moneyball' concept is that you don't spend anything and you are successful," Comolli says. "It's not right. To me the 'Moneyball' concept also applies to what the Red Sox are doing. They've got a lot of resources that they use properly, they create value and are very competitive. There isn't only one way of applying the 'Moneyball' principles. There are a lot of ways. That's why I think if we do it well, we'll be able to compete against clubs that are spending more money than us." A lot of our recent signings have been bought for what some people think is more than what they are worth. These days wages are a very important factor. Some people argue that Andy Carroll and Sergio Aguero both cost £35m but the difference in wages earned is staggering. And the opposite can be said if we get a player for a small sum relative to his worth he maybe be offered better wage packet. They will look at the transfer of a player in terms of both the transfer fee and wages earned combined. Selling players (not Gerrard or Carra obviously and possibly Reina) that are beginning to decline where they still have market value to other teams. "[Wenger] looked at it from a perspective of 'when does he need to sell players?' " Comolli says. "He started using statistics, and I'm sure he was the first one, to look at players and see when they started to decline physically, especially in fitness. When I left Arsenal and went on my own, I grabbed his philosophy and I wanted to do more with it." It is not only statistic’s with regards how a player plays is what we are looking into. Recently when reading an article about 2 chinese youth players that will be joining us next year Comolli said "Statistically we think there will be good players coming out of these countries. With China being the biggest one and football being the most popular sport amongst young people, we feel it is an opportunity to find a quality player." After the summer transfer window he said “The two most difficult positions to fill in football are left full back and central defender because there is a shortage of talent worldwide, and that's why we're delighted to get the two we got in Sebastian Coates and Jose Enrique.†Along with this I remember reading that forwards were statistically the dearest players to buy (quite obvious). We will see a big investment with regards the forward positions within our youth set-up along with left back and centreback. When we bought players in the summer a lot was mentioned on 1 particular statistic. Chances created. Downing, Adam and Henderson all did very well last year in this aspect. Something that we should probably keep an eye on this year. “I think the best team over 38 games without playoffs always wins. And throughout the season you can almost track which are the best teams. And the best teams are the one who are most successful at passing the ball." I don’t think we can use these as determining players that we will buy but we can be sure they won’t buy players that don’t fit into their criteria. Players who are injury prone will not be bought. "For Luis, I looked at the stats over the last three years, notably the number of games played which is an important factor," he told France Football earlier this year. "We turn enormously toward players who don't get injured. We also took into account the number of assists, his performances against the big teams, against the smaller clubs, in the European Cup, the difference between goals scored at home and away." A recent article showed 10 things that soccernomics states. This is a rough guideline. 1. New managers waste money, ergo, limit their say in transfers. 2. Draw opinion from several people from different backgrounds. 3. Avoid stars of recent international tournaments. 4. Avoid certain nationalities (e.g. Brazilian, Dutch) as they are overpriced. 5. Buy players in their early twenties; older players are overvalued and youngsters aren’t fully developed. 6. Sell a player either before buyers see deterioration in his game or when a club offers more than he’s worth. 7. Replace your best players before selling. 8. Never buy strikers because they are overpriced; develop them instead. 9. Buy players with personal problems , then help them deal with their issues. 10. Help new players relocate. This is only a snippet of the information available out there. I hope this leads to a good discussion about statistics in football, our new transfer policy, our future etc….
No one wants to talk about something that is so obviously a big part of how Liverpool as a football club operates. ...................
Baseball sabremetrics stats will not transfer to Football imo and hence after big talk when the guys came in there is little said about it now. Buying young players with potential for big money is not moneyball,its not sabremetrics,its simply a good transfer policy.
You posted this thread yesterday when I think its fair to say not many had any interest in football never mind sabermetrics and soccernomics. BTW its been discussed on here plenty of times before.
Billy Beane was on Radio 5live last week discussing about statistics in football. I agree with you that it won't translate fully to football but it is something that John Henry, Damien Comolli and Co are trying to use to gain an advantage in a competitive environment. If you listen to the 5live show( sure its on a podcast) you will hear about all the people within football that are already using statistics. We have to use whatever we can to compete with the spending power of Man City and Utd. A lot can be considered common sense but it is common sense that is backed up by statistics. bobby benitez can you post a link of where it was discussed before because I am not able to search the forum and I don't have the time to sift through 200 pages of threads.
Prime example, Adebayor, Tevez, Robinho, Ronaldinho and Adriano, all great players who's heads aren't right, all available at some point for a bargain. On form mentally sound Tevez is worth 40mil, yet he could be gotten for less. If you can get it right your onto a winner.
My point is always will people stop saying moneyball is genius and sabremetrics like they know what they are talking about. If anyone can show me where era,war,etc and etc can be replicated in football.Baseball and soccer are so different in how you get players,what players do and the static nature of Baseball and the skills of the players. In Baseball there is players who are brought in to close games,there are lefties for lefties,clutch hitters,players who are runnings and bunters etc. The nature of the game of baseball means that it is perfect for stat geeks The same cannot be said of football. Yes buying young players or bargain lunatics is a great idea but thats not the basis of sabremetrics or moneyball. And can i repeat Billy Beane never won The question isn’t whether or not Moneyball, the movie, is a good piece of filmmaking. Rather, it is whether the film should even have been made, when you realistically look at the job Billy Beane has done as the general manager of the Oakland Athletics. He was considered the precursor of the trend that has swept the baseball world—sabermetrics. The Theo Epsteins, Jon Daniels, and Andrew Friedmans of the world might not be household names today without Billy Beane. The idea behind the concept of what he was trying to do was to maximize performance without spending the big bucks by finding players that slip through the cracks. On-base percentage was his mantra, but it’s not like it didn’t exist before he came around. You can give him credit for taking a small market team to the playoffs five times since he took over in 1998, but what did they accomplish? The A’s won only one playoff series under his watch, and haven’t participated in postseason play since 2006. In fact, they have reached the .500 mark only one time since then, and have been well under .500 other than that. This year they are on pace to lose around 90 games. You have to ask if he deserves all the praise he has received. Where is the evidence that he has been successful? This movie should have come out four to five years ago. Who are the players he has drafted and developed who have turned into stars? Much was made of his 2002 draft where he had nine selections in the Top 98, including seven in the Top 39. His top successes were Nick Swisher, Mark Teahen, and Joe Blanton, but there is nothing earth-shattering there as far as star power goes. You don’t have control of where your picks end up, but you do control who you end up with. Of players he could have drafted who were taken in the first three rounds, Beane passed on Cole Hamels, Jeff Francoeur, Matt Cain, James Loney, Denard Span, Joey Votto, Jon Lester, Jonathan Broxton, Brian McCann and Curtis Granderson. His selections don’t look quite as good when you think of the guys he could have had. He had a dream list of 20 players that he would take if money didn’t matter and he could draft anyone he wanted. In addition to the players that I mentioned he selected, the best of the rest he would have picked were Khalil Greene and Jeff Francis. That is even more damning, because he also didn’t mention B.J. Upton, Zach Greinke, and Prince Fielder for his dream 20. So the guy Moneyball made out to be a genius thought the best players in the draft were Swisher, Teahan, Blanton, Greene, and Francis, and a bunch of guys you’ve never heard of. One of the players the book focused on was the “fat catcher,†Jeremy Brown, who Beane said was the best catcher in the draft. He ended his career with ten major league at-bats. You noticed I mentioned Brian McCann earlier, who obviously was the best catcher in the draft and one of the best in the game for the last several years. He also gave away young players like Andre Ethier and Carlos Gonzalez, and has nothing to show for them. Aren’t they the type of players who fit the Moneyball image? He received the recognition he did because of the book. Take it away, and he’s just another average general manager. The reason his teams had the success they did in his earlier years was because of pitchers Tim Hudson, Mark Mulder, and Barry Zito; and Hudson and Zito were already in the system when he took over. From 2001 to 2004, their average record was 66-33. How many games do the other guys have to win for you to make the playoffs when three starters are putting up those numbers? When you break it down, without them, there wouldn’t have been a book or a movie. That’s why his teams haven’t made the playoffs since the last of them left after 2006. I give Billy Beane two stars. Definitely not a must-see, but worth a look when it comes to video.
But he DID win the same number of games that season as the Yankees did, and on the smallest budget in MLB history. Plus he turned down becoming the highest paid manager/coach in the HISTORY of ALL sports with the Red Sox in favour of staying with the oaks, so I have a lot of respect for the guy on that front.
The Marlins have won 2 world series and they were/are smaller than the A's. The A's won 6 world series in their history and none with Beane.He missed on loads of super talented players in favour of picking players based on their sabremetrics analysis. Tampa Bay reached the world series with a payroll of 43.8m compared to A's 48m The Marlins won...i emphasise won a world series with a payroll of 63m compared to A's 56m What Billy Beane did was great but he didnt win,never came close to winning and during his time 6 teams have won a world series who never won before. Every team uses some type of stats but Beane is made out to be a genius who works magic. His best seasons at the A's were helped by having a player like Giambi in the prime of his career,a player who was on the roster before he arrived. Beane messed up the 2002 fabled draft.Hamels,Fielder,Granderson were all there and he went for a guy who had 10 at bats his entire career. He was a very good Gm but genuis or that it will work in soccer...i remain to be convinced.
I agree with the last line. I jsut said I have huge respect for him. Regarding Giambi, they were on a terrible streak until he decided to trade him, then went onto 20 games won in a row, which I believe is still the all time MLB record?
Rules and Stats are fine as a tool but watching the players over time is more important 8. Never buy strikers because they are overpriced; develop them instead. Suarez £18.4m plus £4m in add on's Value today £40-50m Carroll £35m Value today £15-25m IMO ( hopefully will increase with time) Sometimes rules just dont pan out and sometimes they do Just saying all the rules and stats are just a tool but seeing the player with your own eyes is key
That's Jeremy Giambi. His brother was Jason who left during free agency before the season started. I agree with you Raven. But you have too much focus on Billy Beane. He only put into practice stuff that had been said by the stats geeks long before it. Sabermetrics has since evolved and Billy Beane has really been left behind. I can see what you are saying about payroll but I want to compare us with the Boston Red Sox. They embraced sabermetrics when John Henry took over but they didn't live and die by it. In 'Moneyball' players were not allowed to steal bases or bunt but the in the Red Sox they allow it when in certain situations where it will help. The problem with sabermetrics it that it keeps evolving. Instead of on base percentage there is now wOBA and OPS. I think Rocco hits the nail on the head with what I am trying to say is that we should only use it as a tool. But it is a very important tool. Again this is what Comolli said. "Base your decisions on something that is objective and not only subjective. And there are three aspects of that. One: The use of analytics. Two: The use of scouts. Three: Check background, check the personality and character and attitude. … " The rules I put in are from an article and not rules that you have to always go by. I think Andy Carroll was an exception as he was bought on the last day of the transfer window after losing Torres. Thanks Malzheimer. I meant I cant search because of my low postcount not because I wasn't able.( just in case)
Something I have gone about for years and even though i thought Joe Cole is talented if fit I wanted us to stay clear and invest in a younger player on cheaper wages and watch him increase in value and performance than taken on Bosmans with injury records Players who are injury prone will not be bought. Golden rule imo
An oldish Article but some great points and prime examples. ------------------------------------------------------------- Every tiny aspect of a football match can now be recorded and scrutinised. FT Weekend Magazine commissioned artist Giles Revell to create a series of images of the recent Champions League Final between Barcelona and Manchester United, using exclusive data extracted from the game by the analysis company Prozone I recently visited Manchester City’s tranquil training ground in the village of Carrington. It was a glorious sunny morning, and outside the gates hired hands were washing footballers’ SUVs and sports cars. The defender Kolo Touré coasted past in a giant black contraption straight out of The Godfather. Carrington is used to cars like that: Manchester United train in the village too. View the slideshow “Abu Dhabi Travellers Welcomeâ€, said the message on the façade of City’s sky-blue training centre. Abu Dhabi’s ruling family owns Manchester City, and one thing it has done since buying the club is hire a large team of data analysts. Inside the building I found Gavin Fleig, City’s head of performance analysis, a polite sandy-haired man in a neat black City sweater. Hardly anyone outside Carrington has heard of him, and yet Fleig is a prime mover in English football’s data revolution. Largely unseen by public and media, data on players have begun driving clubs’ decisions – particularly decisions about which players to buy and sell. At many clubs, obscure statisticians in back-rooms will help shape this summer’s transfer market. Fleig gave me the sort of professional presentation you’d expect from a “quant†in an investment bank. Lately, to his excitement, City had acquired stats on every player in the Premier League. Imagine, said Fleig, that you were thinking of signing an attacking midfielder. You wanted someone with a pass completion rate of 80 per cent, who had played a good number of games. Fleig typed the two criteria into his laptop. Portraits of the handful of men in the Premier League who met them flashed up on a screen. A couple were obvious: Arsenal’s Cesc Fà bregas and Liverpool’s Steven Gerrard. You didn’t need data to know they were good. But beside them was a more surprising face: Newcastle’s Kevin Nolan. The numbers wouldn’t immediately spur you to sign him. But they might prompt you to take a closer look. In recent years, after many false starts, the number-crunchers at big English clubs have begun to unearth the player stats that truly matter. For instance, said Fleig, “The top four teams consistently have a higher percentage of pass completion in the final third of the pitch. Since the recruitment of Carlos Tévez, David Silva, Adam Johnson and Yaya Touré to our football team, in the last six months alone, our ability to keep the ball in the final third has grown by 7.7 per cent.†Wenger used the Top Score computer program while at Monaco in the late 1980s That stat had not necessarily driven their recruitment, Fleig cautioned. Indeed, there are probably clubs that lean far more on stats than Manchester City do. I recently toured several actors in football’s data revolution, and was struck by how far it had progressed. “We’ve somewhere around 32 million data points over 12,000, 13,000 games now,†Mike Forde, Chelsea’s performance director, told me one morning in February in the empty stands of Stamford Bridge. Football is becoming clever. Dennis Bergkamp: Wenger would produce the stats: ‘Look Dennis, after 70 minutes you began running less. And your speed declined’ Probably ever since the personal computer arrived, a few pioneers in football have tried to use data to judge players. Among the first was Arsenal’s future manager, Arsène Wenger, an economics graduate and keen mathematician. In the late 1980s, as manager of Monaco, Wenger used a computer program called Top Score, developed by a friend. A less likely pioneer was the late, great vodka-sodden Ukrainian manager Valeri Lobanovski. When I visited Kiev in 1992, Lobanovski’s pet scientist, Professor Anatoly Zelentsov, had me play the computer games that Dynamo Kiev had developed to test players. When Lobanovski said things like, “A team that commits errors in no more than 15 to 18 per cent of its actions is unbeatable,†he wasn’t guessing. Zelentsov’s team had run the numbers. But the broader breakthrough came in 1996, after the Opta Index company began collecting “match data†from the English Premier League, explains the German author Christoph Biermann in Die Fussball-Matrix, the pioneering book on football and data. For the first time, clubs knew how many kilometres each player ran per match, and how many tackles and passes he made. Other data companies entered the market. Some football managers began to look at the stats. In August 2001 Manchester United’s manager Alex Ferguson suddenly sold his defender Jaap Stam to Lazio Roma. The move surprised everyone. Some thought Ferguson was punishing the Dutchman for a silly autobiography he had just published. In truth, although Ferguson didn’t say this publicly, the sale was prompted partly by match data. Studying the numbers, Ferguson had spotted that Stam was tackling less often than before. He presumed the defender, then 29, was declining. So he sold him. As Ferguson later admitted, this was a mistake. Like many football men in the early days of match data, the manager had studied the wrong numbers. Stam wasn’t in decline at all: he would go on to have several excellent years in Italy. Still, the sale was a milestone in football history: a transfer driven largely by stats. At Arsenal, Wenger embraced the new match data. He has said that the morning after a game he’s like a junkie who needs his fix: he reaches for the spreadsheets. In about 2002 he began substituting his forward Dennis Bergkamp late in matches. Bergkamp would go to Wenger to complain. “Then he’d produce the stats,†Bergkamp later recalled. “‘Look Dennis, after 70 minutes you began running less. And your speed declined.’ Wenger is a football professor.†Few would suspect it of West Ham’s new manager “Big Sam†Allardyce, and yet his somewhat neolithic appearance also conceals a professorial mind. As a player, Allardyce spent a year with Tampa Bay, Florida, where he grew fascinated with the way American sports used science and data. In 1999 he became manager of little Bolton. Unable to afford the best players, he hired good statisticians instead. They unearthed one particular stat that enchanted Allardyce. “The average game, the ball changes hands 400 times,†recites Chelsea’s Forde, who got his start in football under Allardyce. “Big Sam†would drum it into his players. To him, it summed up the importance of switching instantly to defensive positions the moment the ball was lost. More concretely, stats led Allardyce to a source of cheap goals: corners, throw-ins and free kicks. Fleig, another Allardyce alumnus, recalled that Bolton would score 45 to 50 per cent of their goals from such “set-piecesâ€, compared with a league average of about a third. Fleig said, “We would be looking at, ‘If a defender cleared the ball from a long throw, where would the ball land? Well, this is the area it most commonly lands. Right, well that’s where we’ll put our man.’†In 2003, football’s data revolution got a new impetus from across the Atlantic. Michael Lewis published his seminal baseball book Moneyball, and some people in English football read it and sat up. Moneyball recounts how the Oakland A’s general manager Billy Beane used new stats to value baseball players. Aided by data, the little A’s briefly punched far above their weight until bigger clubs began hiring statisticians too. The Boston Red Sox, owned by John Henry, himself a “numbers guy†who had made his fortune trading commodities, won two world series using “Moneyball†methods. This February I visited Beane at the Oakland Coliseum. We spoke in what looked like the junk room, but is in fact the dingy clubhouse where the A’s players change. Beane – soon to be portrayed by Brad Pitt in the movie Moneyball – was keen to talk about the data revolution in soccer. Like many Americans this last decade, Beane has embraced the European game with the almost unhealthy fervour of the convert. He can often be found sprawled on a dilapidated sofa in the clubhouse watching European soccer matches. Oakland A’s baseball players have been constantly ‘valued’ using stats He believes that just as baseball has turned into “more of a scienceâ€, soccer will too. Beane said, “If somebody’s right 30 per cent of the time using gut feel, and you can find a way to be right 35 per cent, you create a 5 per cent arbitrage, and in sports that can make the difference between winning and losing.†If using numbers gives you an edge, then everyone will end up having to do it, Beane thinks. Mike Forde, who had studied in Beane’s hometown of San Diego and followed American sports, made the pilgrimage to Oakland to quiz Beane about the uses of data. That proved tricky: Beane spent the first few hours of the conversation quizzing Forde about soccer. “In the last half an hour I managed to turn it around to talk about his role in baseball,†laughs Forde. He became friends with Beane, as did the Frenchman Damien Comolli, a former assistant of Wenger’s. In 2005, Comolli became director of football at Tottenham and began using data there. Comolli’s three years at Spurs encapsulated many of the early struggles of the data revolution. British football had always been suspicious of educated people. The typical football manager was an ex-player who had left school at 16 and ruled his club like an autocrat. He relied on “gutâ€, not numbers. He wasn’t about to obey a spreadsheet-wielding Frenchman who had never played professionally himself. Comolli was always having to fight “nerds versus jocks†battles. With hindsight, he unearthed some excellent players for Spurs: Luka Modric, Dimitar Berbatov, Heurelho Gomes and the 17-year-old Gareth Bale. Yet eventually Comolli was forced out. There was one question the nerds kept having to answer. Yes, the traditionalists would say, stats may well be useful in a stop-start game like baseball. The pitcher pitches, the batter hits, and that event provides oodles of clear data for nerds to crunch. But surely football is too fluid a game to measure? There are many obvious irrationalities in football: goalkeepers, such as Brad Friedel, have longer careers than forwards, yet earn less Forde responds: “Well, I think it’s a really genuine question. It’s one that we ask ourselves all the time.†However, the nerds can answer it. For a start, good mathematicians can handle complex systems. At Chelsea, for instance, one of Forde’s statisticians has a past in insurance modelling. Football – a game of 22 men played on a limited field with set rules – is not of unparalleled complexity. Second, in recent years the fluid game of basketball has found excellent uses for data. Beane says: “If it can be done there, it can be done on the soccer field.†And third, a third of all goals in football don’t come from fluid situations at all. They come from corners, free kicks, penalties and throw-ins – stop-start set-pieces that you can analyse much like a pitch in baseball. The new nerds could point to so many obvious irrationalities in football, especially in the transfer market, so many areas where smart clubs could clean up. For instance: goalkeepers have longer careers than forwards, yet earn less and command much lower transfer fees. Clubs often sign large players but actually tend to use the smaller ones, having belatedly realised that they have overvalued size. And few clubs have asked themselves even basic questions such as: do they earn more points when certain players are on the field? Given that you can hire perhaps 30 statisticians for the £1.5m that the average footballer in the Premier League earns each year, you’d think it might be worth paying some nerds to study these questions. Nonetheless, to some degree football’s suspicion of numbers persists. “Letting even a top-level statistician loose with a more traditional football manager is not really the right combination,†Forde once told me. He himself looks like a football man: trim, greying, regional accent, nice suit. That helps him sell numbers to old-style football men. But, in many clubs, the nerds are only slowly gaining power. Probably every club in the Premier League now employs analysts, but some of these people get locked in computer-filled back-rooms and never meet the manager. That’s why the data revolution was led by clubs where the manager himself trusted numbers. Arsenal and Allardyce’s Bolton began to value players in much the way that financial investors value cattle futures. Take Bolton’s purchase of the 34-year-old central midfielder Gary Speed in 2004. On paper, Speed looked too old. But Bolton, said Fleig, “was able to look at his physical data, to compare it against young players in his position at the time who were at the top of the game, the Steven Gerrards, the Frank Lampards. For a 34-year-old to be consistently having the same levels of physical output as those players, and showing no decline over the previous two seasons, was a contributing factor to say: ‘You know what, this isn’t going to be a huge concern.’†Speed played for Bolton until he was 38. Football’s shrewdest number-crunchers have always understood that data can only support a decision about a player. They cannot determine it. Biermann tells the story of how Wenger in 2004 was looking for an heir to Arsenal’s all-action midfielder Patrick Vieira. Wenger wanted a player who could cover lots of ground. He scanned the data from different European leagues and spotted an unknown teenager at Olympique Marseille named Mathieu Flamini, who was running 14km a game. Alone, that stat wasn’t enough. Did Flamini run in the right direction? Could he play football? Wenger went to look, established that he could, and signed him for peanuts. Flamini prospered at Arsenal before joining Milan to earn even more. Conversely, the clubs that stuck with “gut†rather than numbers began to suffer. In 2003, Real Madrid sold Claude Makélélé to Chelsea for £17m. It seemed a big fee for an unobtrusive 30-year-old defensive midfielder. “We will not miss Makélélé,†said Madrid’s president Florentino Pérez. “His technique is average, he lacks the speed and skill to take the ball past opponents, and 90 per cent of his distribution either goes backwards or sideways. He wasn’t a header of the ball and he rarely passed the ball more than three metres. Younger players will cause Makélélé to be forgotten.†Pérez’s critique wasn’t totally wrong, and yet Madrid had made a terrible error. Makélélé would have five excellent years at Chelsea. There’s now even a position in football named after him: the “Makélélé roleâ€. If only Real had studied the numbers, they might have spotted what made him unique. Forde explained: “Most players are very active when they’re aimed towards the opposition’s goal, in terms of high-intensity activity. Few players are strong going the other way. If you look at Claude, 84 per cent of the time he did high-intensity work, it was when the opposition had the ball, which was twice as much as anyone else on the team.†If you watched the game, you could miss Makélélé . If you looked at the data, there he was. Similarly, if you looked at Manchester City’s Yaya Touré, with his languid running style, you might think he was slow. If you looked at the numbers, you’d see that he wasn’t. Beane says, “What stats allow you to do is not take things at face value. The idea that I trust my eyes more than the stats, I don’t buy that because I’ve seen magicians pull rabbits out of hats and I just know that rabbit’s not in there.†Yet by the mid-2000s, the numbers men in football were becoming uneasily aware that many of the stats they had been trusting for years were useless. In any industry, people use the data they have. The data companies had initially calculated passes, tackles and kilometres per player, and so the clubs had used these numbers to judge players. However, it was becoming clear that these raw stats – which now get beamed up on TV during big games – mean little. Forde remembers the early hunt for meaning in the data on kilometres. “Can we find a correlation between total distance covered and winning? And the answer was invariably no.†Tackles seemed a poor indicator too. There was the awkward issue of the great Italian defender Paolo Maldini. “He made one tackle every two games,†Forde noted ruefully. Maldini positioned himself so well that he didn’t need to tackle. That rather argued against judging defenders on their number of tackles, the way Ferguson had when he sold Stam. Forde said, “I sat in many meetings at Bolton, and I look back now and think ‘Wow, we hammered the team over something that now we think is not relevant.’†Looking back at the early years of data, Fleig concludes: “We should be looking at something far more important.†That is starting to happen now. Football’s “quants†are isolating the numbers that matter. “A lot of that is proprietary,†Forde told me. “The club has been very supportive of this particular space, so we want to keep some of it back.†But the quants will discuss certain findings that are becoming common knowledge in soccer. For instance, rather than looking at kilometres covered, clubs now prefer to look at distances run at top speed. “There is a correlation between the number of sprints and winning,†Daniele Tognaccini, AC Milan’s chief athletics coach, told me in 2008. That’s why Fleig cares about “a player’s high-intensity outputâ€. Different data companies measured this quality differently, he said, “but ultimately it’s a player’s ability to reach a speed threshold of seven metres per second.†If you valued this quality, you would probably have never made the mistake Juventus did in 1999 of selling Thierry Henry to Arsenal. “For Henry to reach seven metres per second, it’s a relative coast,†said Fleig admiringly. The Frenchman got there almost whenever he ran. Equally crucial is the ability to make repeated sprints. Tévez, Manchester City’s little forward, is a bit like a wind-up doll: he’ll sprint, briefly collapse, then very soon afterwards be sprinting again. Fleig said, “If we want to press from the front, then we can look at Carlos’s physical output and know that he’s capable of doing that for 90 minutes-plus.†Just as clubs have learned to isolate sprints from other running, they have learned to isolate telling passes from meaningless square balls. On the screen in Carrington, Fleig flashed up a list of City’s players, ranked by how many chances each had created. One name stood out: David Silva had passed for a third more goal-scoring opportunities than any of his teammates. The new wash of data has made it easy to compare players to players, and clubs to clubs. Wigan, for instance, were recently conceding a greater proportion of their goals from crosses than any other team in the Premier League. If you’re playing Wigan, that’s handy to know. Increasingly, clubs are acting on the data. A quant has controlled Arsenal for 15 years now, but last autumn the numbers guys took over another English giant. The Boston Red Sox’s owner John Henry, who in 2002 had tried to hire Billy Beane, bought Liverpool and immediately hired Beane’s mate Comolli to do a “Moneyball of soccerâ€. From his perch at Anfield, Comolli often chats to the father of Moneyball 5,000 miles away. Beane says: “You can call him anytime. I’ll e-mail him and it will be two in the morning there and he’ll be up, and he’ll e-mail me and say, ‘Hey, I’m watching the A’s game’, because he watches on the computer. The guy never sleeps.†At Liverpool, Comolli has genuine power. He has said that data informed the club’s recent purchases of Andy Carroll and Luis Suarez for a combined £60m. And football’s data revolution has only just got going. Fleig thinks there is an exciting future in sociograms: who passes to whom, who tends to start a team’s dangerous attacks? If you play Barcelona, that man is obviously Xavi. But in another team, the data may show that the launcher of attacks is someone unexpected. If you know the zones where he puts his key passes, you can try blocking them. Someone who has thought harder than most about the future of soccer stats is the director of baseball operations at the Oakland A’s. Farhan Zaidi is a round MIT economics graduate with a sense of humour. He’s the sort of guy you’d expect to meet late one night in a bar in a college town, after a gig, not at a professional sports club. For work, Zaidi crunches baseball stats. But he and Beane spend much of their time at the Coliseum arguing about their other loves: the British band Oasis, and soccer. In 2006, in the middle of the baseball season, they travelled to the soccer world cup in Germany together. Zaidi chuckled: “We spend so much time together, that if all we ever talked about was the numbers on these spreadsheets, we would have killed each other a long time ago.†Because Zaidi knows whethe data revolution in baseball has gone, he can make predictions for soccer. The sport’s holy grail, he thinks, is a stat he calls “Goal Probability Addedâ€. That stat would capture how much each player’s actions over his career increased the chance of his team scoring (for instance, whenever he successfully passed the ball five yards forward from the halfway line), or decreased it (for example, whenever his pass was unsuccessful). I asked Zaidi whether one day pundits might say things like, “Luis Suarez has a Goal Probability Added of 0.60, but Carroll’s GPA is only 0.56.†Zaidi replied, “I tend to think that will happen, because that’s what happened in baseball. We talk now about players in ways that we wouldn’t have dreamed of 10 or 15 years ago.†In their ancient battle against the jocks, the nerds are finally taking revenge.
If Moneyball brought us Carroll for 35m and Downing for 20m then there must have been a bug in the system.