With the ever-present thirst for the next competitive advantage, new strides – or at least attempted strides – are made in baseball analytics every single day.
Sometimes, they even come from ideas of which we’ve long been aware.
Take, for example, the concept of pitch tunnels. It may not be something you’re explicitly familiar with, but I strongly suspect it’s something you’ve conceptually understood for a while now.
The idea is that a pitcher can be at his most effective when more of the pitches in his arsenal are indistinguishable from each other at the (tunnel) point where batters decide whether or not they need to swing. The later the movement, in other words, the more difficult it is to decide if, where, and when to swing the bat.
Greg Maddux was talking about it before it was cool:
“[My] main goal was to make all of my pitches look like a column of milk coming toward home plate. Every pitch should look as close to every other as possible, all part of that ‘column of milk’.”
And these GIFs do a great job visualizing how it looks in real life:
— Driveline Baseball (@DrivelineBB) January 20, 2017
Kyle Hendricks, 3 Pitch Strikeout/Tunnels [FB 88mph, FB 88mph, Change 80mph–Using 1st pitch just off the plate called strike to win the AB] pic.twitter.com/OtzF5NUsNH
— Rob Friedman (@PitchingNinja) February 13, 2017
But, until recently, this was really just a theoretical strategy. It was well-utilized by pitchers like Maddux, but it wasn’t easily quantifiable. And when you can’t quantify something, it’s difficult to hold an objective measure of who is already succeeding – or might soon succeed – because of the approach.
Now, we live in a data-intensive age, and Baseball Prospectus took the lead on this one, and got the conversation rolling.
At Baseball Prospectus, Jeff Long, Jonathan Judge and Harry Pavlidis performed a deep study on pitch tunnels and how they might be used to project future performance. It’s a really excellent study and useful bit of new information, so I strongly encourage you to check it out.
In the end, the trio explains that the value in these new pitch tunnel statistics are “largely rooted in their ability to inform us on opportunities for improvement and other such practical applications.” Specifically, they mention that this data may lead pitchers to add an additional pitch to their repertoire (even if it isn’t top notch), changing the sequencing of their pitches, and/or tweaking existing pitches.
Some pitchers may have done some of these things on their own, but in so doing were unknowingly reacting to the positivities of optimizing their pitch tunneling, specifically.
Whatever the impetus for him, Cubs lefty Jon Lester may be one of the current best.
In response to the pitch tunneling study (which did feature Jon Lester as the experiment’s variable), Darius Austin took a separate look at Jon Lester and pitch tunnels at BP Wrigleyville.
As we established, the “tunnel point” is the point at which a hitter needs to decide whether to swing. According to BP, that ‘s about 175 milliseconds before contact (based on a league-average fastball). As it turns out, in addition to some tangential characteristics (an “incredibly consistent release point), Lester’s pitches come with just a tiny bit differentiation between his pitches at the tunnel point.
For far more explanation on how Lester (and to an extent, Kyle Hendricks) has made this work for him, be sure to check out Darius Austin’s piece. I’m not sure if this will be the next big thing, but it’s certainly a compelling study – and a strategy that seems to be employed by two of the Cubs’ most effective pitchers.
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