Let’s talk about “analytics”

At this point, we know that baseball is run by “analytics.” That’s kind of a broad term meant to encompass everything that goes into evaluating players intelligently and efficiently: For proponents, it’s meant to convey a wide-ranging set of data points that signify which players are worth an organization’s time; for detractors, it’s a catch-all meant to disparage the “Ivy League nerds,” as I’ve seen front office members called. As we drudge through a largely uneventful offseason and press towards the 2021 season, which we hope won’t face significant delays or cancellations, I can’t believe how many fans continue to lob grenades at “analytics.”

Baseball’s history is unique and contrasts to other sports; while many sports have a record book and fans have some indication about what players did what and when, baseball – and its fans – are religious about the stats. It’s just now we have new stats. As it turns out, things like batting average and runs batted in aren’t quite the sterling metrics we thought they were for years. With the advent of different evaluation tools, like wRC+, FIP, and WAR, we’re much better at gauging a player’s performance; in some instances, we’re also much better at determining whether or not a player is actually a valuable asset who deserves a contract extension or big free agent money.

I think the gripe with a heavy data reliance is due to concerns about the on-field product. This is where I want to make a differentiation: Just because baseball is now being played with the actual best players for the job and because the game is more efficient than ever, doesn’t mean that it’s not occasionally boring. We’ve entered the age of the three true outcomes, as it’s called: Strikeout, walk, home run. While it’s sometimes enjoyable to watch a starting pitcher carve up his opponents late into games, a lot of the time, copious amounts of strikeouts can be a tedious proposition. Walks are boring. As for home runs, while a lot of people like them, it sounds like more and more people are preferring the “old” way of baseball business: Hit, bunt, run, and mix in some triples. Even I would prefer that method a lot of the time. But that’s not where we are.

Those who wish death upon analytics, I’ve got news for you: Our reliance on data isn’t waning; it’s only growing stronger. The next wave – and in many ways, the current wave – is biomechanics. Will those staunchly opposed to deeper statistical analysis eventually part ways with their curmudgeon attitudes? It’s hard to say. But by the time they’ve acquiesced and joined the “dark side” – or, at least, come to tolerate the dark side – I wouldn’t be surprised if Greg Amsinger on MLB Tonight is showing elaborate breakdowns of pitchers’ throwing mechanics on computer simulations. That’s where the game is headed.

We’ve come to refer to baseball as a “thinking man’s (person’s) game,” and it’s becoming even more so; why is there such a resistance? Instead or railing against what’s inevitable, let’s envision solutions about what could make the game more enjoyable to audiences again. At The Athletic, Joe Posnanski had written an article about what former front office executive Theo Epstein should do next. He concluded that a new position be established for the intelligent, analytically savvy Epstein, and give him the responsibility of revamping the on-field product in a way that is both enjoyable and compatible with the current state of the game, as well as the future of it.

In the Washington Nationals’ case, one current, relevant example of a guy who analytics liked is newly retired playoff hero Howie Kendrick. The 15-year-veteran didn’t have the typical makeup of a guy which analytics prefers in some ways, but he hit the ball hard, which the Nationals analytics department noted. In making a smart, data informed decision, Washington brought in the player who, unbeknownst to them at the time, was going to be a major driving force in finally bringing a World Series title to the nation’s capital. There’s a fairly long list of players who credit a shift in approach thanks to analytics to their on-field production, particularly for pitchers.

Despite all this, we’ve got disgruntled fans taking to Twitter to air their grievances. Granted, these angry types might be a vocal minority, but the vitriol is spilled, nonetheless. It’s one thing when the average fan decides to ridicule the shift the game has taken – it’s another when players (and usually former players) decide to do it. The impetus behind this article was something I saw former Detroit Tiger Brandon Inge tweeting about.

In a video in which a hitting coach is talking to his player about hitting line drives and being able to hit the ball out front, as well as deep, Inge interprets it as a diatribe against informed hitting. Inge says, “This is how 99 % of the best MLB hitters do it!! Study this and forget about the ridiculous launch angle thoughts! Compete!!!” What Inge is failing to understand here is that, to teach a player to hit line drives is not counterintuitive to an analytical or “launch angle” approach – never mind that Inge treats launch angle not as a data point, but as an approach. Coaches don’t teach launch angle because it isn’t a teachable commodity. Altering other parts of the swing results in a change in launch angle, not vice versa. It’s not like the coach was imploring his player to hit the ball on the ground; that would be antithetical to the new approach to hitting.

Finally, our data points must be correct in some sense because when sorting by these metrics which some deride, the undisputed best hitters still crop up at the top of the list. Ted Williams is still there, Babe Ruth is still there, Barry Bonds is still there. What front offices are doing with this approach is not denigrating former greats; what they’re doing is forming a more comprehensive understanding of what those players did and trying to determine which characteristics modern players share with them. Like Carl Sagan said, “You have to know the past to understand the present.” Just as science shifts, our understanding in baseball must also shift to paint a better picture of the past.

When colleges like the University of Pennsylvania are writing articles about baseball, that’s a good thing, not a bad thing.

So, instead of focusing on how bad the game is because of “analytics,” let’s attempt to reach conclusions on what they game should do next in order to make the sport better.