Those who follow British English Premier League (British football) know that the fabled club Liverpool has been rescued from bankruptcy by new American owners New England Sports Ventures. NESV also owns the Boston Red Sox. The British English exported an aging Beckham, and now a tittering football club; apparently, according to the Guardian, we are exporting Moneyball, which is described somewhat facetiously as "building title-winning teams on the cheap". (Thanks to reader Daniel L. for the link.)
More choice words (you've got to love British journalism):
these value-hunters are returning to a template authored by Billy Beane, Oakland's general manager, which said, in the starkest terms, the world is full of bargains and game‑changers whose brilliance is concealed by ignorance or circumstance.
The author is not a fan of Moneyball. And he has some good arguments.
Daniel proposes that fantasy football is essentially Moneyball for American football, and he takes the other side of the debate.
I'm not so sure. Fantasy football -- of which I only have passing knowledge, I must admit -- is fantasy sabermetrics, if it is sabermetrics. Yes, there are lots of statistics, and yes, statistics drive the results; but in one crucial aspect, it does not imitate Moneyball or Bill James at all: the statistics used in fantasy leagues are obtained by convenience, whatever are available; but in true sabermetrics, the key question is which statistic truly has value in predicting performance, and which doesn't. Often times, this requires inventing new statistics, or modifying existing statistics, e.g. a double is not twice the value of a single.
I think doing soccer statistics is extremely exciting but will be very challenging. The tradition of collecting detailed statistics is not there. The game is flowing rather than stop-and-start. Tactics matter a lot. Unlike baseball, and to a lesser extent, American football, the possibilities are infinite from any given point in a game. I think univariate statistics are pretty much worthless. My previous comments are here.
In terms of Oakland As equivalents, there are in fact teams like that already. For example, in Serie A, Udinese is a team that spots young talent, they are pretty competitive year in year out, and when the young players prove their worth, they get too expensive and move on to the more wealthy clubs. I don't know if they use much analytics to spot talent, though. The question with such teams--and with Moneyball--is whether they make champions, or just highly competitive outfits. Also, how sustainable is the advantage if all teams hire a stable of statisticians?
The most fascinating aspect of Michael Lewis's book, in my view, is the culture clash between the analytical people and the intuition people. This clash is replicated pretty much everywhere there is analytics work done. (Similar situation in the Minnesota highway meters story in Chapter 1 of Numbers Rule Your World.) One thing that is often missed is that it is not an either/or situation; statistical models should complement the human decision-making process, not supplant it.