Analytics, Moneyball and Heart


Ah, another baseball season, another silly mischaracterization of what sabermetrics/analytics mean and don’t mean. In the batter’s box today – Mike Lupica, one of the deans of the “old school.” I didn’t catch all of his musings on the subject this morning, but here’s what I did hear:

1) Lupica became the one millionth customer to say that Billy Beane’s Moneyball approach benefited greatly from the presence the Big Three starting pitchers at the beginning of the new century, as if Beane himself had absolutely nothing to do with the construction of that rotation. I am pretty confident no one has ever denied that having really good pitchers helps you win baseball games, or that it takes luck as well as skill to cultivate both a talented and healthy pitching staff. But since anti-sabermetric space aliens didn’t one day deposit Mulder, Hudson and Zito in the A’s clubhouse as fully formed major league aces, maybe Beane deserves a tiny bit of credit for their being on his baseball team. In fact, when the A’s won their first of four division titles between 2000 and 2006, only Hudson was a great starter for the entire season. Zito was a mid-season call up (and pitched extremely well in 14 starts) and Mulder was still feeling his way – he went 9-10 and pitched to a 5.44 ERA, which was bad even in 2000. There is no doubt that the terrific troika carried the A’s to division titles in ’02 and ’03. By the time of their fourth and final division pennant in 2006, only one was left – Zito.

Of course it helped Beane to have great starters during his earlier run of success. This is not an insight, or a rejoinder to “Moneyball.” It’s a banality. As it happens, the A’s have won division titles the past two seasons, in a neighborhood with two very big spending teams and without the benefit of a Big Three. So, there’s that.

2) Lupica also generously conceded – while surveying the landscape of baseball this past decade and asserting that you can’t win “just with analytics” – “I’m not saying the Red Sox are completely dismissive of analytics.” Nice try, Mike. The GM who guided them to their first two World Series titles in nearly a century was indisputably heavily influenced by sabermetrics. Hell, he hired the damn godfather, lord and master of the Moneyball revolution – Bill James – to work in his organization. Theo Epstein’s successors remain deeply committed to analytics and the principal owner John Henry has made clear his own views on the subject, which is why he was willing to break the bank to hire Beane a decade ago.

No one in baseball circles argues that you “just need analytics.” It’s a poor representation of the state of the debate in 2003, let alone in 2014, when virtually every major league team incorporates analytics in a serious way into their player evaluation process (even the once averse San Francisco Giants). Over the past ten years, the Boston Red Sox have won three World Series titles and there is simply no disputing that they were among the earliest and most committed practitioners of a talent evaluation system heavily dependent on sabermetrics. There is also little dispute that since 2008, the most consistently successful low payroll team has been the Tampa Bay Rays. They’ve become the envy of the sport for their consistent ability to churn out top flight pitchers and to replace them with more top flights pitchers when the older ones become too expensive. Under the direction of President Andrew Friedman, the Rays have fully and relentlessly embraced sabermetrics to guide their decision-making. Likewise, the consistently successful Cardinals have also developed a serious analytics approach.

3) Lupica also said – he claimed to be quoting Joe Torre – that you can’t use analytics to “see what’s in a player’s heart.” That’s deep, Mike. It also happens not to mean anything. You’re very unlikely to find a baseball (or any sports) executive who considers “character,” or personality or whatever irrelevant.  Major league teams are trying to process extraordinary amounts of data. Like any business, they need models, shortcuts, heuristics to help make sense of that data, to separate out the signal from the noise. One thing they can’t really do, it seems, is predict ahead of time who is going to perform well in especially high pressure situations. And to the extent that “heart” has any concrete meaning in sports, it’s that – how players perform when the game or the season is on the line. In this regard, “heart” turns out to be an almost entirely retrospective judgment. Just a few weeks ago, the Kentucky Wildcats were being widely criticized as a bunch talented, but raw and unrefined basketball players, overrated early because they lacked the “experience” and other intangibles allegedly necessary for success, despite all the hype about the supposed greatest recruiting class of all time. Three extraordinary Aaron Harrison three pointers later, and suddenly, it seems, all that talent has been fortified by lots of heart.

This is no knock on Aaron Harrison at all. He seems like a good kid, he’s really talented and what he’s done over the past two weeks is damned impressive. But no one can say they “knew” that he, or anybody else, could hit such big shots before he actually did. What does that mean in the context of analytics and so forth? It means that “heart” is not, somehow, an alternative approach to analytics, one that the geeky numbers people somehow fail to recognize. It is, of course, incredibly helpful to make really clutch plays in close games. But John Calipari isn’t recruiting for “heart.” (I am sure he says otherwise. But his recruiting approach seems fairly easily explained by consulting the rankings of the most highly rated high school players in the country each year). Since there’s no way to know, ahead of time, who’s going to come up big when it matters most, the fact is that no one actually plans for that. You do your due diligence to field the most talented teams you can. Then you hope for the best. That, in a nutshell, was what Beane meant when he uttered his often misunderstood comment that when it comes to the postseason, “my shit doesn’t work.” Some year, it might, at which time there will be all kinds of commentary about how Beane finally “figured out” how to translate regular season success into the playoffs and about how, after all, heart and character were what pushed his team over the top.

It’ll make for a comforting story. It will also tell us nothing about what actually happened.


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