There are several moments in Moneyball, the film which documents the rise of the Oakland A’s, when Billy Beane (played by Brad Pitt) ignores the joint advice of his scouts and looks at the fictional Peter Brand (played by Jonah Hill) and asks him to recite the statistical data that supports the buying of player A or B. This goes against the advice of the scouts, who say the player has a weird way to pitch, is too slow, too old, has a complicated personality or whatever else. Beane does not care. For him, the stats are everything. The scouts are dinosaurs – a point helped by their age (they all looking like having reserved their spots in the local cemetery) – and their empirical knowledge is essentially useless.
The message is that it does not matter what the years of experience of these scouts bring, only what the raw data mentions. When Sabermetrics, a method for objective analysis of baseball using statistics popularized by Bill James, appeared, it was very much ignored. The scouts distrusted the view that people sitting in cubicles could look at numbers and spot what all their hours in ball parks could not. On the other hand, when the Oakland A’s succeeded, scouts started being seen in the manner described above. Unfortunately, both approaches miss the point completely.
It is very much true that scouts, such as any human being, will fall prey to their own prejudices and preconceptions. If a player is built so-and-so, he cannot play in position A. If he is fast, he has to be a runner. If he has a strong arm, he must be a pitcher. This concept is immediately defeated by the most famous baseball player ever: Babe Ruth. Or by the tall and lean Usain Bolt, who runs mainly against shorter and bulkier sprinters. On the other hand, it is also true that papers filled with numbers do not tell the whole story. One player may excel in his position, but his success may be as much due to his own prowess as to that of the teammate who interacts the most with them. Conceivably it can be seen as the Lennon-McCartney effect: separate they may be good, but together they were geniuses.
Cause and effect
One other point is about the origin of the statistics. It may be true that scouts are looking at style when they should be looking at results, but it was the scouts (and possibly reporters) who came up with the relevant statistics to look at. It may sound silly, but if the statistics are now “base runs” or batting averages”, they could very well be “hand size”, “batting arc” or “average running speed”. Someone came up with the right statistics to look at, because someone figured out the relation cause-effect. That is, someone realized that the higher the batting average, the higher the total points made. Not the other way around.
Some time ago, Simon Kuper and Stefan Szymanksi published Soccernomics, a book which looked at football from the point of view of an economist, using his tools. There, they realized, for example, that the amount paid in fees for players had little correlation with the success of the team that brought in the players. A much better measure of success were the salaries paid to the players in the team. This indicator provided a very strong correlation, but may not be the whole story. Obviously nobody would expect that if Stoke increase the salaries of the whole squad to Manchester City levels, they would challenge for the title. Still, it may not be clear if the salaries are high because the victories forced the management to increase them, or if the victories came because successful players who earn high salaries were brought in. Once again, cause and effect.
The Liverpool case
The most ironic part of all this is the recent sacking of Damien Comolli. He had been brought in by Liverpool to oversee the implementation of Moneyball-rules to the club. He identified the necessary areas of intervention, identified the players necessary to bring in and did it, apparently with the blessing of Dalglish. With hindsight, the decisions were, mainly, disastrous. Only Jose Enrique and Craig Belamy were successes and Charlie Adam does not feel overpriced (he arrived on the cheap). Naturally, the casual observer will feel aggrieved with the fees paid, but should he? Moneyball was never about bringing brilliant players for peanuts. It was always about bringing players with added value for less than what they could contribute. With this in mind, and considering Liverpool elected to bring in English players, Carroll and Henderson (very young), Suarez and Downing (not old and with important sets of skills) were not bad choices. Maybe overpriced, but if you are willing to pay the price, you should not complaint.
Still, even with a Soccernomics/Moneyball devotee as Director of Football and another as owner, Liverpool haven’t had the highest success. This goes to show how difficult transposing success formulas between different sports can be. It also goes to show that, with it’s simple rules, football can still defy analysis. Statistical tools must know what to look for, otherwise they are simply a nice party trick. On the other hand, when the key issues are identified, a relation of cause and effect must be established, lest one focuses on the wrong side of the issue. In baseball, this is easy but in football the issue is much more complicated due to the multiple interactions between all the players.
This is not to say that such statistical analysis will not be possible, only that it will have to identify the key issues before it can be applied. And, as in everything in human history, the first one advancing the knowledge a bit stands to profit immensely. The question is: who will that be?