The war over analytics is being waged yet again, and this time, it’s baseball that ignited the fight.
During Game 6 of the World Series, Tampa Bay Rays manager Kevin Cash took out starting pitcher Blake Snell in the midst of an elimination game, despite Snell looking utterly dominant and still having a low pitch count. Immediately, the Rays bullpen blew its lead. The Dodgers went on to win the game and the championship, and the rest is history. The managerial move was met with apprehension when it happened, and given the result, heaps of criticism followed.
The sabermetrics nerds say a pitcher’s effectiveness dramatically decreases when facing a hitter for the third time. This is true because, of course, the numbers back up their argument. In removing Snell from the game, Cash followed this analytical line of thinking. But the supposed jocks and “sports purists” couldn’t disagree more. In baseball tradition, starters are supposed to tough out long, machismo-powered outings and managers are supposed to make decisions based on “feel,” not numbers.
Obviously, it’s not quite as clean a dichotomy. It’s unfair (and insulting) to label the pro-analytics crowd as nerds, and the same goes for minimizing the anti-analytics crowd as jocks. Algorithms and traditions aren’t water and oil –– successful franchises in all sports know how to infuse old ways with new thinking.
Yet when vaunted analytics causes this much of a stir, hot takes and overreactions start flying. Some commentators were mildly disappointed at Cash’s decision while others went all-out apocalyptic, signaling baseball’s death by analytics overload. Alex Rodriguez seemed to suggest that computers and machines were taking over the sport, Terminator style. He followed by hammering a metaphor about Ivy Leaguers getting Fs in baseball. Witty as Rodriguez may be in retirement, his manic and misguided takes are common among those who bash the usage of analytics.
By now, it’s clear that analytical approaches are here to stay in all sports. Not only do front offices have analytics departments, but many general managers and presidents have more background in academic fields than the sport itself. In the media sphere, analytics is still somewhat of a hot topic, and pundits still debate its effectiveness. But in team offices, it’s no longer even a question, but rather an arms race of acquiring the best people and resources in the analytics field.
Some in the anti-analytics crowd misunderstand what analytics truly are. Pablo Torre of ESPN put it best: “analytics” and “information” are one and the same. Statistics themselves aren’t an ideology and don’t provide an opinion; rather, they provide a basis for people to make decisions. Even points per game, as perfunctory as it is, is a statistic that gives us the most basic idea of a player’s effectiveness. Advanced stats and metrics themselves can’t cause a bad managerial decision or a faulty offensive system.
Ultimately, sports unfolds in a series of events, decided by execution. Any single play or decision can have various outcomes, but with a larger sample size, patterns tend to occur. Take the Houston Rockets for example –– they fully committed to the 3-point shot and layup because years of data have shown that those two shots are the most efficient. It’s no coincidence that the league’s average offensive rating jumped from 103 to 110.6 in the last 20 years, at the same time three-point attempts per game went from 13.7 to 34.1. But anything can happen in any given game, even missing 27 straight three-pointers in a row.
It’s completely fair to criticize Cash for his managerial decision, or the Rockets for not diversifying their offense, just like it’s fair to criticize any decision that ever led to a negative outcome. But while other errors are usually attributed to bad execution, when analytics are involved, some allege that numbers and algorithms must be banished from sports entirely.
Front offices and brain trusts have only scratched the surface of analytics' boundless potential. Each bad decision driven by stats and metrics is cause for critics to debunk its effectiveness, but at this point, that’s a losing fight. It’s time for the anti-analytics crowd to stop railing against ideas and concepts they might not understand, and embrace how analytics has been incorporated in sports.