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Pitching is about keeping hitters guessing — and about walking the line between overusing certain pitches to the point of predictability and underusing others that have quietly confounded opponents in limited doses. Now more than ever, each MLB pitcher’s repertoire is scientifically calibrated, from the shape of the ball’s arc as it approaches the plate to the spin it carries and how it looks coming out of the hand. Modern pitchers take their pitch selection as seriously as a Michelin chef planning a gourmet menu.
But even with all of that sophistication, there are inefficiencies in how pitchers deploy their stuff. Many years ago, I dove into the game theory behind pitch selection, and specifically which pitchers were throwing their different pitch types in an optimal way versus those who could stand to tweak their pitch mix a bit to achieve better results.
The thought process went like this: We know from Statcast data how frequently each pitcher throws each type of pitch, and thanks to websites such as FanGraphs, we also know how effective each pitcher’s pitches have been at preventing runs. (We now even know how good each pitch should be based on its characteristics, such as velocity, movement, spin and other factors.)
From this data, we can then find cases where there are mismatches between a pitcher’s most effective pitches and the ones he uses the most.
Of course, not every pitch can be scaled up without diminishing returns. But in general, pitchers who lean more heavily on their best pitches are likely getting more out of their repertoire than those who don’t.
I then developed what I call the Nash Score for pitchers…
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