Strunk: The cost of saving money in baseball
From Trevor Strunk at Baseball Prospectus on May 5, 2016:
One of the major misunderstandings the [Fire Joe Morgan] blog tried to correct was sports media’s systemic inability to understand what the book Moneyball was about, and, consequently, what the general philosophy of Moneyball actually was. More often than not, commentators and journalists, particularly the titular Joe Morgan, would argue that Moneyball meant teams being cheap, privileging walks over batting average, and losing in the playoffs like the Oakland A’s. As Ken Tremendous and company would insist over at Fire Joe Morgan, though, the idea behind Billy Beane’s strategy as documented by Michael Lewis in Moneyball was the exploitation of market inefficiencies. Especially for teams that did not have the capital to spend like the New York Yankees or Los Angeles Dodgers, Beane’s philosophy—which Lewis gave the shorthand of “Moneyball”—was essentially a leveling technique, a way of attacking a hopeless mismatch by finding a completely different resource to pursue. No money? No problem!
This philosophy is very appealing in the abstract. You can imagine yourself as a kind of treasure hunter, finding players who would have never gotten a chance in previous years, and showing how they can be productive major leaguers. The bad body types, the too-patient hitters, the light hitting defensive center fielders: analytics have rehabilitated all of these kinds of players at one point or another. I would argue that the Jack Custs or the Jarrod Dysons of the world would not have had nearly the shot they have had if not for Beane’s emphasis on market inefficiency, and that’s all for the good.
But the dark side of sabermetrics also has to do with labor. On the players’ side, this is something of a necessary evil in modern baseball. With the number of analytical tools at the disposal of major-league teams currently, teams will know how risky any player is, his upside and, more importantly, his downside. So when GMs offer “team-friendly” long-term contracts to very young players, these are necessarily “player-antagonistic” as well. (With the possible exception of that overlap in each party’s interest created by each party’s different incentives.) The player can gamble on his own upside against his downside, but he can only ever do so knowing that the team has run the actuarial and statistical math to determine exactly where the monetary limit of their risk is. The team has run the simulations, and the player gets to bet on himself against the numerical odds or accept a contract that, while sizable, is a fraction of future potential earnings.
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Originally published: May 5, 2016. Last Updated: May 5, 2016.