How Data Is Ruining Baseball (And How It Can Fix It, Too)
Smart businesses allow data to guide their marketing.
The ability to do this is relatively new and likely not to last too much longer. A firehose stream of information is available on a company’s marketing campaign performance, its customers and its potential customers. That stream is so strong that there’s a movement afoot to create a new federal agency, the Bureau of Privacy, to govern its flow.
Access to and the correct interpretation of data changes business. Those who have it and do it well more frequently see their success accelerate, while those who lag behind more often fail.
This truth applies to Major League Baseball, too. The flow of information there is so strong that it is more appropriate to compare it to a tsunami than a firehose. Everything in baseball is now knowable, and in a game where the margin between success and failure is infinitesimal, the collective data output has become more valuable than the contract Juan Soto will be receiving in a few years.
The problem is that, just like a tsunami, that flood of data is killing the game and has the potential to send it into a death spiral from which it cannot recover.
Back Then …
Baseball started as a simple game played by simple folks. Even the owners and administrators of the teams were most often simple people.
Dugouts were filled with blue-collar players and blue-collar managers who guided their teams based on gut feel and personal experience. General managers — the guys who put the team together by finding young players, orchestrating trades and signing free agents — were almost exclusively former ballplayers and managers.
Things began to change as the piles of money available for playing the game better than the rest grew bigger and bigger. Without a salary cap that limited what teams with the best attendance in the biggest media markets could offer the most talented players, teams in small markets had to find a way to compete as a matter of survival.
Enter Billy Beane, a former outfielder of average accomplishment who ascended to the general manager position with the small-market Oakland Athletics. Recognizing he couldn’t compete with clubs that spent cash by the barge if he did did everything else the same way they did, Beane used his thimbleful of resources to hire a different type of person to guide the club’s decisions than baseball had ever seen before:
Beane and his crew of Ivy League-educated data analysts began scouring the trove of statistics churned out by each Major League game for data points undervalued by other teams. What they found was the beginning of the movement that has changed how baseball is played. Beane’s story is chronicled in the book and movie Moneyball, a worthwhile read and watch.
Historically, teams valued hitters for their batting average, home runs, stolen bases, runs scored and/or runs batted in. They valued pitchers for wins, strike outs and earned run average. Beane’s nerds found inefficiencies in that system and began to exploit them by trading away players who didn’t excel at the statistical categories they found more linked to the thing that ultimately matters most in baseball: Winning. In return, they received players who didn’t exactly fit the mold of what a baseball superstar should look like.
And here’s the thing: The A’s won. No, it didn’t end in a string of World Series championships, but Beane and his Nerds routinely got the woefully underfunded A’s to the playoffs with a collection of players no one would have given a chance to succeed.
But the significance of Beane’s success isn’t with how it affected the A’s. Its significance rests with how it changed the game of baseball — and how it threatens to destroy it today.
Today’s data flow in baseball makes Beane’s early work seem Flintstonian. The rise of advanced analytics has made the game of baseball far easier to play for those with the talent to play it at the highest levels. Long gone are scouting report with overarching trends. Here are detailed reports on each player’s performance in any given situation coupled with predictive analysis on what that player is going to do against you at that very moment.
This has led to significant changes in the game of baseball that has made it something purists hardly recognize and certainly aren’t comfortable with. When three infielders shift to one side of the field instead of the standard two on each side of second base, those purists scream at the field or their television sets, “Just bunt the ball where the fielder isn’t!”
Which seems like an obvious solution.
Except today’s player won’t do that. Why? Because the data says there is more value in him doing what he does without changing his approach thanks to the higher probability that he’s going to hit a home run or other significant form of contact to make a greater difference in the game’s ultimate aim of winning.
So what happens is glaring failures in which the hitter smacks the ball right into the teeth of the shift, where that third defender on that side of the field scoops up what previously might have been a single and instead throws him out at first.
But it gets worse.
Smart hitters who recognized this shift in strategy realized they had a way to beat the shift that didn’t force them to drop a measly bunt down the third-base line. Thus, launch angle was born. If you can’t hit it past where a bounty of fielders suddenly resides, hit it over them.
This has, yes, led to prodigious home runs. It also has led to an explosion of strikeouts. To create an optimal launch angle, hitters have to swing with an uppercut, which leaves the bat in the hitting zone far less than a smooth, level swing. Less time in the area where the ball is going to appear means less of a chance of hitting it.
This is just one way in which data has changed baseball … and just one way in which it is destroying it.
Pitching Changes, Ad Infinitum
The way the 2015 Kansas City Royals used their data dealt another death blow to baseball. As the small-market Royals pursued their first World Series title since the Reagan years, they found and developed a crop of hard-throwing pitchers who could bring it to hitters at blurring speeds.
Yet they could only throw so hard for so long.
What the Royals and other teams had begun to learn through data, however, was that they didn’t need to throw it that hard for too long, and that if you used those pitchers in ways different from the way the game had seen pitchers be used in the past, there was a competitive advantage.
Traditionally, baseball had starting pitchers who routinely completed the game. Bob Gibson stands out as the prototype for this. In his illustrious career with the St. Louis Cardinals, Gibson started 482 games. He was on the mound to record the last out in 255 of them. That’s nearly 53%. In his most dominant year, 1968, Gibson started 34 games and completed 28 of them.
By way of comparison, in 2021, there were a total of 33 complete games pitched in all of Major League Baseball. The American League leader threw two and the National League leading trio threw three each.
Arguably the best pitcher of this century has been Max Scherzer, currently with the New York Mets. Over his entire Major League career, which began in 2008, he has started 421 games and completed 12 — just 2.8% — and never thrown more than four in a season.
What does that data mean? Well, first it’s important to understand why this is so. The biggest reason is because data showed how much easier things became for hitters the third time they faced the same pitcher in the same game. The percentage at which hitters reach base safely jumps dramatically if the starting pitcher is still around for a third shot.
So now, most often, he’s not.
The Royals exploited this in their World Series run by expecting very little of their starting pitchers and then turning the ball over to a train of relievers who threw 100 mph and plowed through opposing hitters. It worked. The won the championship, and their model has become the model for other teams in the playoffs.
This is where we get to what the data means: Longer games. A lot longer games.
Pitching changes take time. Pitchers who throw the ball that hard generate more swings and misses, which means more pitches, which takes more time. And hitters who don’t adjust their approach to hitting because the data tells them trying to jack the ball 500 feet is still the best option generate still more swings and misses.
The result is bleary-eyed fans at work the morning after the latest in a long line of four-plus-hour playoff games … and kids who have no interest in baseball because they aren’t awake or are bored by the slow pace of the sports crowning jewel each year.
Enter: The Death Spiral
Now we’ve reached the crux of the problem.
On the one hand, you’ve got players who are able to perform better because of the information provided by the tsunami of data. For a team to ignore these advanced analytics is sheer stupidity. Teams with the smallest investment in data analytics perform worse on the field, in general, than the teams who have invested in it heavily.
On the other hand is the reality that the data being provided to these players is making the game unfamiliar to the fans who helped make it, at one point, America’s pastime. Some would say the playoffs have become largely unwatchable, and not just because the games are routinely ending after midnight Eastern.
The ingredients are mixed and ready to put in the oven to bake baseball’s death cake.
An increasingly long game featuring far less action compared to its own past and exponentially less action than the sports that draw higher interest from today’s generation of fans with gnat-like attention spans will stop being financially possible.
Attendance and viewership will fall.
When it’s time for TV networks to renegotiate their deals to broadcast Major League games, the contract will be worth far less than the current one. Players salaries are based on either an owner’s benevolence or its fanbase’s willingness to support it through attendance and viewership and purchases of its paraphernalia.
As all things economic tend to do, this will disproportionally hurt the less wealthy teams first. Fewer games on television and fewer fans attending them live will worsen the downward spiral, and teams like the A’s and the Royals will feel that first because their base is smaller.
These teams will fold or move, but there are only a limited number of cities in which what those teams will experience won’t be an issue.
The death spiral accelerates when the game, no longer as much in the public eye, becomes even less the game of choice for the nation’s youth. With fewer kids playing the game, eventually the product at the top is no longer played as well as it once was. This provides even more reasons to save the money and stay home or to watch something different.
To say this couldn’t happen to baseball is to ignore how once-prominent sports like boxing and horse racing have become fringe, niche offerings.
Can This Be Stopped?
What is baseball to do? It can hardly tell teams to ignore the data that gives them an advantage. You can’t put limits on the number of data analysts a team can hire or the types of data it can track. This would only create a black market for information.
What baseball can do is tweak its rules to legislate the impact of data out of the game. Take the data that is making the game worse and couple it with the data that shows the drop in viewer appeal to make the game better.
Three suggestions for baseball to implement next season would be:
- Limit the size of pitching staffs on the active roster to promote starters going deeper into the game, thus reducing game time and promoting offense.
- Eliminate the shift by mandating that two infielders have their feet on the left side of second base and two infielders have their feet on the right side of second base when the pitch is thrown.
- Enforce a pitch clock and stop allowing hitters to fiddle with every piece of their uniform in between pitches.
And that’s just the beginning.
Baseball has a data problem. It is allowing the access to information and the brains adept at interpreting it to make its product less palatable to those who would consume it. The game has already gone from being one that shaped our national identity to one with only regional appeal.
But there are ways to stop it from getting worse. The same data that’s leading to advantages on the field can be used to create the rules that restore the game’s watchability. Baseball would be wise to act quickly.
John Agliata is a marketing professional with more than 30 years of communications experience. Reach him at firstname.lastname@example.org or (352) 226-5852.
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