Moneyball

I watched the movie a few weeks ago and just finished reading the Michael Lewis book it was based on, and as it happens, what works in the movie and what doesn’t are the same as with the book. Both stood out as interesting examples of a certain type of storytelling — dense, jargon-heavy dialogue about a specific subject, nevertheless rendered compelling by the fact that they are about big, easy-to-understand ideas and people who believe in them. Once you focus on that, you realize that what drives these stories is the same thing that drives so many others — a man with a theory nobody else believes.

In this case, that man is Billy Beane, the general manager of the Oakland Athletics. Beane was a gifted athlete whose pro-baseball career fizzled out, but who found a lot more success after his move to the management side of things. He was given the task of building and managing a team that had far fewer dollars to play with than its competitors (less than a third of what the New York Yankees had to work with), and responded by trying to find undervalued players who could help the team win.

How did they do this? The simple, yet superficial answer would be statistics. A lot of rigorous statistical analysis replaced the conventional wisdom used by the scouts working for baseball teams. Instead of letting the scouts influence the decisions on who a team picked and for how much, Beane based his decisions on the work of his analysis team, led by a Harvard economics graduate named Paul DePodesta.

But as anyone who has a lot of data on his hands knows, you can coax a large enough database into giving you any conclusion you want. What really matters when you delve into the world of baseball statistics is an ability to figure out what you should be looking for. Lewis uses a number of examples about both batters and pitchers to convey this point, and this is where the jargon gets in the way of the narrative.  If you don’t know baseball, you might find it difficult reading.

The film has the same problem — there were scenes where my response was driven primarily by the expressions on the characters’ faces and not by what they were saying. It was like watching a foreign movie without subtitles. These scenes are rescued by the acting, and by the fact that we understand the emotional context of the scene, if not the specific topic being discussed. As a result, we stay involved enough in the narrative to cheer when Beane’s unorthodox methods produce spectacular results.

In 2002, the Oakland As put together the longest winning streak in the history major league baseball. As Paul himself might say, that’s a bit of a statistical freak with not a large enough sample size to back it up. But the truth is, the 2002 season was not the first time that the As did so well with so little money, or the first time Beane went looking for undervalued draft picks. It was just the season where his methods were most evident and came under the most stress (three of his best players had just been bought by other, richer teams).

While the movie is principally about Beane, and how he championed the use of new techniques to be “the card counter at the blackjack table”, the book uses it as a jump-off point to profile a bunch of people whose work influenced him and his team. This idea of focusing on a little band of idiosyncratic outsiders is something Lewis uses again in The Big Short, his chronicle of the subprime mortgage crisis.

Chief among the outsiders here is Bill James (who was later hired by the Boston Red Sox), who is among the best known pioneers in this area. When one says, “James wrote the book on meaningful baseball stats”, it’s not a figure of speech — he literally wrote a series of books with all kinds of baseball stats. But more than the numbers he crunched, it was the kind of analysis he provided that really had an impact on the game.

As someone employed in the field of data mining, I can understand why this character strikes a chord with me. I can imagine being engrossed by a biography/biopic of James himself. But I can also see why the focus of the book and the movie is not James but Beane — he was the man who staked his career on these ideas. Given how much it went against the conventional wisdom prevalent in major league baseball, he’d have been flipping burgers if it hadn’t panned out. The fact that Beane had, in the past, shown himself incapable of dealing with failure, meant that flipping burgers was not the worst of the consequences one would worry about when it came to him.

As interesting as Beane is on the printed page, what makes him tough to base a movie around is that a team manager’s involvement with the game does not seem as immediate as that of a player or even that of a coach. So the filmmaker is stuck with the challenge of making a sports movie where the sport is as much of an abstraction as a stock ticker in a movie set in Wall Street. Even a movie like Jerry Maguire, which was about a sports agent and only peripherally about the sport, had one of those big last-minute-play moments. This one has no major scenes on the field, no inspirational speeches… none of the traditional dramatic flourishes that we’ve come to expect, really. But it works, and we are involved, because in its own understated way. Brad Pitt’s performance helps immeasurably — here is an actor who is more often admired for looking good, and therefore underrated as an actor. By the time he gets an offer to manage the Red Sox at what was then an unheard-of salary, the film has quietly built up such a dramatic head of steam that we cheer, even though the scene is quiet as they come.

You don’t always need great dramatic flourishes to draw people in. Quiet observation of interesting people will do just as well. What is significant doesn’t always have to be the thing that draws our attention at first glance. Which, I suppose, is what the story is about.

ps: It occurs to me that I have not said anything about the extent to which the movie is faithful to the events and characters depicted in the book. It also occurs to me that this is not a significant variable in the equation.

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