Analytics or heart: Can old-school baseball reclaim sport’s soul?

For once, New York Yankees fans wish their team were more like the Texas Rangers.

It’s not just that the Rangers are one win away from clinching the World Series. It’s also that, in an era when baseball in particular is increasingly defined by statistical analysis, the Rangers seem to be a testament to steady, old-school thinking. They still have, as many see it, a baseball soul.

The portrait is admittedly simplistic. Everyone uses statistical analysis to guide their decision-making – even the Rangers. But as the season draws to a close, it’s the time for an annual reset. And some fans are starting to worry that the relationship between America’s pastime and on-field statistics has gone too far.

The Yankees are only the most convenient target. Their commitment to distilling baseball into advanced metrics didn’t work; they missed the playoffs. But the sense that the sport has essentially been overtaken by mutual fund managers is widespread.

“The idea is that the Yankees’ use of analytics has failed them because analytics cannot take ‘heart’ and ‘clutch’ into account,” says Michael Quinn, a professor of sports media at Manhattan College. “The Rangers have heart and that propelled them, whereas the Yankees just have calculators and by-the-numbers accountants.”

Should fans be content with game-time decisions made in the name of risk aversion, and free agent signings made in the name of sustainability?

“[Some feel] it’s trying to take the mystery out of the sport,” says Professor Quinn. “It’s trying to take the heroes and the heart out of the sport.”

Baseball is no stranger to statistics. But since the 2002 Oakland Athletics pioneered the modern “sabermetrics” movement, teams have relied on formulas and data points that are increasingly complex – and, to some, incomprehensible.

Dan Secatore runs “Over the Monster,” a fan blog for the Boston Red Sox. He says that when fans voice their dissatisfaction with analytics, they are not voicing the same complaints that are shown in the “Moneyball” book or movie, which both chronicle the 2002 Athletics team.

“We all came to view players the same way,” he said, referring to sabermetrics such as on-base percentage and wins above replacement. “But then [teams] moved on and started applying the same metrics to, ‘How should the game be played?’”

The result has been years of heavy investment in analytics, as teams use the numbers at their disposal to decide everything from pitching matchups to roster construction.

“Teams began to be taken over by guys with backgrounds at McKinsey and Wall Street, who began to prioritize risk management ... above anything else,” he said.

Case in point: After the Seattle Mariners narrowly missed the playoffs this year, team executive Jerry Dipoto argued that his team’s season was actually a success. He noted that, historically speaking, teams winning 54% of their games (as the Mariners did) are likely to eventually appear in a World Series (which the Mariners, to date, never have). “We’re actually doing the fan base a favor in asking for their patience to win the World Series while we continue to build a sustainably good roster,” he said.

“That’s really where the backlash is now,” says Mr. Secatore. “Fans want to win – but they don’t want their teams to be turned into mutual funds where the goal is slow-and-steady, sustainable growth. They want to know that their owners are trying to win the World Series.”

Analytics are commonly used by teams to identify a player’s “value” – both individually and as part of a team. Front offices looking for a competitive advantage tend to look for “undervalued” players – which critics see as a reluctance to spend big or commit to winning.

“It just binds you where you are. You have to make these penny-pinching moves [for trades and signings] that aren’t going to move the needle,” says Joe Castellano, a Yankees fan from Long Island.

For lower-budget teams like the Athletics, which need to identify undervalued players, analytics can be indispensable, says Mr. Castellano. But for teams like the Yankees, he says, the pursuit of “value” has distorted their worldview and made penny-pinching seem a virtue – all while the Rangers doled out $800 million over the past two years to sign the top players on the free agent market. 

“There’s no excuse for us not to be spending in that way,” he says.

That’s not to say the Rangers are still operating in a pre-“Moneyball” mindset. According to Andrew Baggarly, a baseball writer for The Athletic, “Every team has analytics baked into their decision-making.”

Even Bruce Bochy, the Rangers manager widely perceived as “old-school,” has acknowledged how data informs his game-time decisions: “You’re crazy not to listen and get all the information you can.”

It’s just a matter of how obvious those decisions are for casual viewers, says Mr. Baggarly. “Do fans feel like their teams may be tilting a little too far on the spectrum towards data? And have they lost a little bit of their soul along the way?”

Frustration also boiled over this year in Boston, where many Red Sox fans celebrated the firing of general manager Chaim Bloom, an analytics guru who, according to Mr. Secatore, had tried to build a “cost-controlled pipeline of players” after years of uncontrolled spending. Mr. Bloom’s four-year tenure saw the departure of several popular stars and ended with a last-place finish in the division.

“In a lot of cases where teams are doing less and figuring they have a chance to get in [the playoffs], it means frankly they’re not creating a product that is as compelling and as entertaining,” says Mr. Baggarly.

Baseball’s unique reverence for tradition has only deepened the controversy, says Professor Quinn. For once, statisticians are the in-group, and longtime fans are the outsiders. “There’s a feeling that some of the people who used to watch don’t really belong in the game anymore.”

The conversation over analytics mirrors what’s happening in society, says Mr. Secatore. “We’re sort of all at a point now where we all acknowledge that Amazon, for example, is a much more efficient way to shop ... but maybe we’re missing something that we had before. Maybe there are certain things in our society that should be a little bit more inefficient.”