Sabermetric Aesthetics

by by by Taylor Kelley

Moneyball, Barry Bonds, and the Beauty of the Game

In the canon of baseball-nerd scripture, Bill James’ Abstracts is the Old Testament, Tom Tango’s The Book is Paul’s epistles, and the gospels is Moneyball. Last Friday, after years of pre-production delays, a revolving door of producers and writers, and a Jonah Hill-for-Demetri Martin deadline trade, the film adaptation was finally released to theaters.

The movie, based on the eponymous book by Michael Lewis (who also wrote The Blind Side and The Big Short), follows the Oakland Athletics’ 2002 season. It focuses on general manager Billy Beane, played by Brad Pitt, and his effort to compete in the league in which his team’s budget is three times less than the wealthiest franchise, the New York Yankees. Frustrated after an offseason of getting outbid for three of the team’s most important players, Beane decides that his team can only sustain success in such unfair circumstances if his process fundamentally differs from his privileged competition.

A revelation came to Beane, captured in a climactic scene, during a chance meeting with über-nerd, Assistant GM Peter Brand (Jonah Hill, obviously). His solution is to prioritize advanced statistical analysis over scouting and traditional stats. Baseball, to a degree, has always used numbers to evaluate players. These pre-computer statistics were valuable mostly because they were easy to count: runs scored, for example, or strikeouts. Advanced stats (called sabermetrics, derived from the acronym for the Society of American Baseball Research) use more up-to-date techniques, like regression analysis, to better model the correlation of individual plays with wins. For example, the ubiquitous stat of batting average counts singles and home runs as equally valuable, whereas its sabermetric analogue would account for the extra value created by the home run. In the movie, Beane and Brand use these techniques to identify players with skills undervalued by teams using more traditional methods, allowing them to construct a winning team within their limited budget.


If this were a review of the film, I’d have to explain how two guys looking at spreadsheets and making phone calls to trade marginal major leaguers for obscure minor leaguers makes for compelling drama.” (It does, but you’ll just have to trust me.) I’d like to talk instead about one of the movie’s main themes: the tricky balance between the beauty of the game and its numbers.

Throughout the film, Beane asks several times, “How can you not be romantic about baseball?”, despite coming across as a hardened and unemotional professional. His daughter writes him a song that, in the movie’s final moments, reminds him to “just enjoy the show” (“the show” being a nickname for the Major Leagues). Most memorably, Beane is touched when Peter Brand shows him a video from a recent minor league game of an overweight catcher, drafted because of his statistics against the strong objections of Beane’s scouts. In the video, the enormous player stumbles and crashes to the ground while rounding first, realizing that he may have a shot at a rare triple. He awkwardly crawls back to first base for an embarrassing single. His teammates, though, are in hysterics, and when he looks up he sees the ball has sailed well over the fence. He hit a home run without even realizing. It is easy to imagine Beane, a few days earlier, looking over the stats from the game, noting the home run and moving on. Despite the movie’s glorification of the numbers in baseball, it also suggests that sometimes a home run is more than just a home run.

This scene points to a common argument against sabermetrics: that statistical analysis misses the real point of being a sports fan. In a recent column about how he wouldn’t be seeing Moneyball, Fox Sports’ Jason Whitlock complained, “The sabermetricians will punch in the numbers and give you, in their mind, a definitive answer. It’s boring. It’s ruining sports.” Proponents of Whitlock’s traditionalist line of thinking typically identify beauty in baseball with the human. Baseball for them is all about the brotherhood of a cohesive team, the leadership of the star player, the personal sacrifice for the good of one’s teammates and fans. Beloved by these traditional are the players that hustle to first after every grounder, attempt lots of diving catches, and, because perceptions typically conform to expectations, tend to be white and good-looking. Fat players, black players, and Spanish-speaking players don’t fit the mold.

This narrative is beautiful in its simplicity, but statistics have also been a point of emphasis for even the most traditional baseball fans. Baseball romanticizes certain numbers: 755 home runs, a .300 batting average, the 56-game hitting streak, 300 wins; these carry historical significance and conjure real emotion. (You might notice, for example, that I’ve listed 755 instead of whatever number the current career record holder Barry Bonds, accused of steroid-use, ended up with. As a Braves fan, 755 was the number of one of my players, Hank Aaron, and so it’s the one that will stick with me).

When a no-hitter is thrown, the catcher runs out to the mound, dramatically embraces the pitcher, and the game makes the front page the next day. The sabermetrician, however, would be more interested in the actual quality of the game pitched. Minnesota’s Francisco Liriano, for example, threw a no-hitter earlier this year in which he walked six batters, definitely a worse performance than giving up a couple hits and one or two walks (something that happens all the time). But what matters to the traditionalist is the number—0 hits. Baseball even romanticizes the players that accumulate the traditional stats, but lack the personal qualities typically valued by traditionalists: think Mickey Mantle, twenty time All-Star but a reckless drunk during his playing days. Presumably this is because fans like winners, and stats like batting average and RBIs correlate with winning. Why, though, are these stats prioritized over newer, sabermetric measures with an even stronger correlation with winning, say— wOBA or FIP? (head to Wikipedia to hunt for acronyms).

Many traditionalists argue that the newfangled metrics lionized in Moneyball are too abstract and complicated. Not that the old stats aren’t complicated too. Allow me to paraphrase one of baseball’s most traditional statistics, the pitcher win: a pitcher receives a win if they leave the game with their team winning, and that lead is not relinquished by the end of the game. If the pitcher started the game, they must pitch at least five complete innings to be eligible (unless, of course, the game is shortened enough by rain). If the pitcher came in as a reliever with his team tied or trailing and leaves the game with the lead, they are eligible for the win. In a scenario in which the starting pitcher gained the lead, but pitched less than five innings, the official scorer just decides who he felt pitched the best amongst the relievers and awards them the win. The pitcher win, more or less fully understood by all baseball fans, is both complicated and arbitrary. And this isn’t really a cherry-picked stat; just try to define precisely what events constitute an “at bat”.


Basically, the old statistics work for Jason Whitlock because they’re old. And that’s fine: I was really hoping Detroit’s Justin Verlander would get his 25th win this year, despite its ineffectiveness as a metric for pitcher performance, because the last time it happened was the year I was born. It’s fun and part of being a fan to participate in baseball mythology.

But advanced statistics can cater to this mythology just as easily: Barry Bonds’ spreadsheet of sabermetric numbers is a beautiful sight to behold (I couldn’t care less that he cheated; the numbers are real). While all fans may know that Bonds was a great player, his complete domination of the game can only fully be seen through the advanced metrics. From 2001 to 2004, he was 40% better than the second best player in baseball and about twice as valuable as someone who put up four All-Star quality seasons each of those years. The “advanced defense” numbers show us that, even in his late 30s and weighed down by artificial bulk from steroids and human growth hormone, he was still an above-average fielder. And perhaps most amazingly—and Billy Beane would certainly agree—in that four-year period, he walked over three times as often as he struck out. To me, and many others, that is as beautiful as the Babe calling his shot, or DiMaggio’s 56-game hit streak.

Amongst the sabermetrically inclined, there has been much discussion of whether Moneyball will bring the statistical good news to the people, or whether things will remain the same, with advanced statistics still largely at the nerd fringe of baseball coverage. Either way, there is no doubt that the movie does a good job romanticizing the spreadsheet without losing sight of the more traditional beauties of baseball. There is definitely a delicate balance between the two. After all, despite all the amazing things Bonds did, he was still an asshole. I booed him along with the rest of my city while he chased the career home run record set by Atlanta’s Hank Aaron. I know, though, that Bonds’s numbers will be legendary before too long. Hopefully, though, the Billy Beane revolution comes to pass and his 38% walk percentage will be given as much weight as his 73 home runs.

TAYLOR KELLEY B’12 is sabermetrically inclined.