The movie "Moneyball" is about baseball statistics. Putting a human touch on this subject seems nearly impossible, but the movie is primarily about how people deal with the emotional side of taking a calculated risk. If I were younger I might think that it held great life lessons about determination, courage, and the triumph of glorious mathematics over stodgy old men. I recommend it today because it has some great moments of humor, and because it illustrates one step in what turns out to be a long and continuing saga of mathematics applied to sports. Baseball teams have finite budgets for player salaries, and the ratio can be as much as 5 to 1. In order to get into post-season play, a team needs to win more than 90 games. What is the least money needed to buy players who can assure that? That's the game of "moneyball". Surprisingly, until recently, the concept of maximizing return on player investment had little traction. Managers got the best (i.e., most highly paid) players that they could afford. More surprisingly, there has been plenty of mathematical and modeling information available to guide moneyball players (i.e., general managers) for decades. The movie "Moneyball" is about how "conventional" baseball wisdom finally started being displaced by statistical wisdom. What was the impediment to this displacement? It seems to me that there were two factors which are probably common to all group endeavors. The first is that the reward system was skewed. Teams that spent a lot but did not perform to expectation were still admired because they had good players, and teams that did well on low budgets aspired to buy expensive players. Secondly, the decision process for selecting players is consensus-based, and that is inherently conservative. Again, the reward for selecting a good team is too little --- the analysts themselves are like players that are not subjected to individual metrics. Are they doing well or not? Without the metric, they evaluate themselves and reward consensus over excellence. I was surprised to discover that there a model of human aversion to risk. See Prospect Theory, http://en.wikipedia.org/wiki/Prospect_theory This caused me to wonder about conventional wisdom about decision making. I've read that in general, "crowds" do well at Bayesian decisions. Apparently committees don't. As for Moneyball, it's effects are longlasting. This is a good article about it: http://www.grantland.com/story/_/id/6466015/cashing-new-moneyball Baseball isn't my game, though. I like NFL football. So, naturally I've wondered if there a version of moneyball for football, soccer, basketball, lacrosse, or Ultimate? Maybe not. Field-based team sports are harder to analyze. Baseball has some very simple metrics that are clearly tied to winning, e.g. "he gets on base." Having 10 to 22 people in motion at once is complicated. Which individual performance metrics most strongly predict success? As far as I know, this is an open question. For the most part, team sports on a playing field are about control of space. Strategies that can create open space adjacent to players are the most successful It is like chess. But, because everyone is in motion, the space is also in motion. There's also a premium for maintaining space around the player with the "ball" (like avoiding checkmate). If you can turn that into player metrics, then you could invent "Money Football" and be as famous as Bill James (read "Moneyball" the book). Hilarie