Looking Beyond the Box Score


The arrival of spring, even in its usually inconsistent form, always is a welcome sign. Spring means warmth, and growth, and baseball. To me, the geometric perfection of baseball is one of the mysteries of the universe, along with the pyramids and the platypus.

Imagine baseball with 100-ft. baselines instead of the current 90 ft. The pitcher’s mound would be proportionally further away, which would change the time the batter has to pick up the pitch and the velocity the ball could maintain before it gets to the batter. It also would take 11% longer to get between bases, which would negate the speed factor in a game and make it a fundamentally different sport.

When baseball arrives, it brings with it another mathematical wonder: the box score. I have been reading box scores since I was old enough to read, sometimes by night light as I was supposed to be sleeping.

The simple complexity of this document each day is not found in any other sport. At first glance, you know everything about the game: who won, who lost, which innings the runs were scored in, how many hits each team had. Dig a little deeper and you learn more information.

You learn about strikeouts and errors, and how many innings each pitcher threw. By comparing the pitcher’s stat line with the scoring summary, you can understand if the pitcher started poorly and then settled down, or whether he might have thrown one inning too many that day. You can get more details about how each hitter did that day. A hitter going 0-for-3 with three strikeouts might have been the hero if his RBI sacrifice fly in the 9th inning drove home the winning run. And a hitter who does 4-for-4 but commits two errors in the field may have undone with his glove whatever good his bat may have accomplished.

Over a long season, you begin to understand how player performance can ebb and flow, how the loss of one player has a ripple effect across the team and how decisions made during the game impact not just the short-term outcome of a given game but also prepare the team for success later in the year.

No other sport is so specifically strategic and yet so wildly unpredictable. To mitigate both of these factors, baseball has become not just a digital game, but a scientific one. Today we measure spin rates for pitchers and exit velocity for hitters. The proliferation of cameras and sensors throughout the ballparks and the ability to use artificial intelligence to analyze this data and provide it to teams has led to a far more cerebral approach to America’s Pastime. (In this context, we separate “artificial intelligence” used by most teams as compared to the deliberate stupidity of the Houston Astros. But that’s for another column.)

There is nothing new here, of course. Balls always have spun and the velocity by which they have exited the playing field always has been rapid. What has changed is our ability to better measure and analyze those events and gain knowledge from it.

It is the way our manufacturing plants have changed as well. We have always “sensed” productivity; now we can measure it down to the shift and down to the worker. We can better determine when our mechanical and our human machines begin to falter, and we can take steps to mitigate that event. We know more about what happens in our plants today. Our challenge is to take the data and make it useful. The data leads us toward the path of improvement, but the data alone cannot change the outcome.

The data revolution in manufacturing provides one of the clearest opportunities yet to augment our human genius with artificial intelligence and gain victories that might have been impossible before.

Temperature and vibration are just runs and hits. They’re just numbers—unless you understand what those numbers tell you about current performance, and what they might tell you about future performance.

How well do you keep score in your plant? And how well are scoring your success not just day to day, but over the long haul? The answers are in the numbers—if you know how to read the box score.



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