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SmartData Collective > Big Data > Data Visualization > How the Numerati are killing baseball
Data Visualization

How the Numerati are killing baseball

StephenBaker1
StephenBaker1
5 Min Read
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An Utley homer: The computer probably called for the pitch 3 inches to the right.

Optimization may be terrific for factories, and data-driven targeting will no doubt revolutionize marketing. But these arts of the Numerati, I’ve come to believe, are killing baseball as a spectator sport.

Sunday night I was watching the Yankees play the Red Sox in the opening game. This was a scenario I could have only dreamed of a couple decades ago. I was watching two great teams in hi-def on a 40-inch screen. They were playing in Fenway Park, one of the most beautiful fields on earth, and the game, a 9-7 win for the Sox, featured a roaring comeback and clutch home-runs. But I wasn’t done til after midnight, and that’s part of the problem.

The trouble is data. In the data-sparse era I grew up in, teams did not have ‘the book’ on every single hitter and pitcher. They didn’t know, for example, that a certain shortstop hit .086 against left-handers’ curve-balls over the outside corner. Today they know such things. In the old days, teams had a certain idea about how to pitch to two or three sluggers on the other team, and then treated everyone else like commodities …

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An Utley homer: The computer probably called for the pitch 3 inches to the right.

Optimization may be terrific for factories, and data-driven
targeting will no doubt revolutionize marketing. But these arts of the
Numerati, I’ve come to believe, are killing baseball as a spectator
sport.

Sunday night I was watching the Yankees play the Red Sox
in the opening game. This was a scenario I could have only dreamed of a
couple decades ago. I was watching two great teams in hi-def on a
40-inch screen. They were playing in Fenway Park, one of the most
beautiful fields on earth, and the game, a 9-7 win for the Sox,
featured a roaring comeback and clutch home-runs. But I wasn’t done til
after midnight, and that’s part of the problem.

The trouble is
data. In the data-sparse era I grew up in, teams did not have ‘the
book’ on every single hitter and pitcher. They didn’t know, for
example, that a certain shortstop hit .086 against left-handers’
curve-balls over the outside corner. Today they know such things. In
the old days, teams had a certain idea about how to pitch to two or
three sluggers on the other team, and then treated everyone else like
commodities. All these batters got the same assortments of fastballs,
curves and sliders. It was quicker.

Now, every at bat is modeled
and optimized. This might mean bringing in three or four pitchers in
the eighth inning alone. This takes time. What’s more, batters have
learned that if they force pitchers to throw more, they’re more likely
to wear them out (and get on base with walks.) So each at-bat is a
marathon. (A few decades ago, pitchers wouldn’t put up with such
tactics. They’d throw the ball over the plate and challenge weaker
hitters. But today, thanks to weight training and perhaps other
chemical additives, there are far fewer scrawny easy-outs in a
line-up. Each player is capable of hitting homers.)

In the tech world, this type of personal and situational customization is rampant, especially in
e-commerce. But thanks to ever faster computers, it doesn’t take more
time. In baseball, though, all the data-driven commands must be transferred
to the analog world. This slows the on-the-field drama to a crawl. This doesn’t work for a 162-game season, at least for me.

So what to do? Increasingly, I find myself consuming baseball as a
stream of data while doing something else. I’d rather hear the game
on radio, or even watch the pitch-by-pitch feed on my iPod. The game as
remodeled by the Numerati is more interesting than ever–but not to
watch.

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