I have surrendered to the numbers. I will make no assessment, athletic or otherwise, without rigorous statistical analysis. Miguel Cabrera versus Mike Trout? Andrew Luck versus Robert Griffin III? Without examining all the hard data, I won't even cast a vote on Ginger versus Mary Ann. I reject your anecdotal evidence, your hunches, your wishes disguised as predictions. I will keep my gut instincts away from my brain and suggest you do as well. Resist all you want, but soon—and a statistician with enough time and a laptop can pinpoint when—you, too, will give in to the power of the numbers and those who crunch them.
I welcome our new computational overlords. I once was blind (to the limitations of batting average and pitchers' win-loss records), but now I see (the wonder of wOBA and FIP). The data point that finally convinced me fully had nothing to do with the AL MVP vote between Trout, the Angels' rookie centerfielder whose absurdly high WAR (wins against replacement) makes him the poster boy for the sabermetric crowd, and Cabrera, the Tigers' third baseman who won the traditionalists' admiration by becoming the first Triple Crown winner in 45 years. It was statistician Nate Silver's correctly predicting the outcome of that other ballot you may have heard about last week.
Silver not only forecast President Obama's reelection, he did it with uncanny precision, calling which candidate would win each of the 50 states despite weeks of heckling from more than a few pundits who scoffed at his mathematically based projections. That's a little like hitting every jumper in a three-point-shooting contest while opponents rain trash talk on your head. It's little wonder that Silver couldn't resist a dig at his doubters. "I'm not very pro-pundit, I have to say," he told The Colbert Report host Stephen Colbert last week, after the election. "If pundits were on the ballot against, like, I don't know ... Ebola? I might vote Ebola, or third party."
Regardless of your political persuasion, there was no disputing Silver's accuracy. If analyzing the numbers properly can successfully predict voters' actions, then why has it been so hard for some of us to accept that similar analysis could accurately assess athletes' performances?
That's always been the issue, hasn't it? It's hard to believe that algorithms could accurately measure or predict something as seemingly unpredictable as human behavior. How do you quantify desire or motivation or other intangible qualities? In sports, as in other areas, we tend to cling to the notion that people are too complex to be summed up by formulas and functions, too multidimensional to be solved by a set of equations. And so we resist, even as we see evidence that the numbers don't lie, that they can help us gain a more precise understanding of ourselves.
The skepticism about Silver's political number crunching was a familiar development to sports fans. Before he began tackling presidential races in 2008, Silver had used advanced statistical measurements in baseball, with his PECOTA system that predicted player and team performances. His methods and projections were met with just as much resistance in baseball as they were in politics. (Though to be fair, his baseball results weren't as spot-on as his election projections.) Silver's success with the election results is just one example of the ways in which statistical analysis has been useful in areas that are far more important than in deciding the AL MVP. Sophisticated quantitative analysis is now part of everything from crime prevention to medical treatment, and those real-world uses make it seem silly that we ever wondered whether numbers can be trusted to help determine whether one second baseman is better than another.
So that is why, in the war on expertise, I am on the side of the spreadsheets. I am with Team Calculator. Stat nerds, let your geek flag fly. I will defend you against the stereotype that you all live in your parents' basement and every one of you looks like Sheldon from The Big Bang Theory. From now on, I will try to advance your cause and think in terms of advanced metrics. In basketball I won't listen to talk of PPG (points per game) unless it also includes PER (player efficiency rating). In football I will judge each play not only on the yardage gained or lost but on its EPA (expected points added) and WPA (win probability added). In baseball I will not be silent until everyone is buzzing about BABIP (batting average on balls in play).
I look forward to life under the geeks. Perhaps in time, the braying broadcasters arguing about the "clutch gene" and "killer instinct" will be replaced by analysts engaging in reasoned discussions, their positions bolstered by numbers. Maybe there will be fewer ex-jocks cackling and backslapping on studio shows and more explanation of players' value in ways that go beyond the rudimentary averages.
In that case, there will be more reason to embrace the encroachment of Big Data than to fear it. The bottom line, though, is that in the future, it will be impossible to avoid more number crunching, in sports and elsewhere. You don't have to be a statistician to nail that prediction.
I once was blind (to the limitations of batting average), but now I see (the wonders of wOBA).