Our new normalization option lets you compare hitters and pitchers to players of the same handedness.
First, thanks for your enormous level of support and feedback for our new Hitter and Pitcher Profiles. Because of your suggestions, we increased the number of sortable statistics to 19, added several new color schemes, changed some of the layout, and added several new multi-sort options. Your feedback makes building new and great tools easier, so thanks!
We want to announce a new option on our tools and briefly describe how it works. This option is “normalization,” which allows you to compare a pitcher or hitter to other similar pitchers or hitters. It works only for a few of the 19 sorts right now—it will work for all of them eventually—but we think that the most instructive sort is “frequency,” so we’ll describe it using that and let you play around with it. We’ve already done some limited “beta testing” of this new feature via Twitter, and people found it really fun and informative, so we’re excited to announce it on Baseball Prospectus. (As an aside, Harry and I often beta new features late at night on Twitter, so you can come follow us and be part of the creative process if you want.)
A few days after the rollout of the BP Hitter Profiles, we present their companion piece, the Pitcher Profiles.
Last weekend we posted “Hitter Profiles,” which let you look at PITCHf/x data for each hitter in MLB filtered by a bunch of different attributes. Today, we’re posting their companion piece, “Pitcher Profiles.” You can search for pitchers here. As we did for the Hitter Profiles, we’ll be adding a dropdown link to the search interface from the “Statistics” tab on the nav bar at the top of the page.
We think these profiles will revolutionize the way people look at PITCHf/x data. Location is perhaps the most important attribute of a pitch, and the Pitcher Profiles allow you to examine the results of pitches across multiple spatial locations. PITCHf/x data has been available for five years, but we haven’t been able to examine it this way, at least publicly. (There are scouting services that provide this kind of data.) It was the first thing that a scout I talked to asked for.
Is the traditional strike-ball dichotomy too simplistic?
Believe it or not, most of our writers didn't enter the world sporting an @baseballprospectus.com address; with a few exceptions, they started out somewhere else. In an effort to up your reading pleasure while tipping our caps to some of the most illuminating work being done elsewhere on the internet, we'll be yielding the stage once a week to the best and brightest baseball writers, researchers and thinkers from outside of the BP umbrella. If you'd like to nominate a guest contributor (including yourself), please drop us a line.
Matt Lentzner has carved out a (very) small niche in the baseball analysis world by examining the intersection of physics and biomechanics. He has presented at the PITCHf/x conference in each of the last two years and has written articles for The Hardball Times, as well as a previous article for Baseball Prospectus. When he’s not writing, Matt works on his physics-based baseball simulator, which is so awesome and all-encompassing that it will likely never actually be finished, though it does provide the inspiration for most of his articles and presentations. In real life, he’s an IT Director at a small financial consulting company in the Silicon Valley and also runs a physical training gym in his backyard on the weekends.
The Indians' sophomore surprise and stalwart starter has a striking similarity to the Yankees' Chien-Ming Wang.
After a 2006 season in which Chien-Ming Wang was declared to be a unique hurler with outcomes only reproducible by Wang himself, we seem to have possibly found another edition, a pitcher just as capable of succeeding in the face of sabermetrically-orthodox expectations. That's because the Indians have stuck Fausto Carmona into their rotation with similar results. Other than Carmona's extra few punch-outs, the two do almost the same things to succeed. Is this enough for Fausto to survive round two in the majors as a big-league starter in 2008?
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Popping the hood on King Felix as a demonstration of what's possible with PITCHf/x data
"Hell, yeah, I want to throw that pitch. They don't let me, though. They tell me I'm too young, that it's bad for my elbow. I told them I want to throw it."
--Felix Hernandeztalking about his slider before the 2006 season
Before claiming any success for any measure in predicting injury, we must fundamentally recognize that any PAP-style metric will be positively correlated with raw pitch counts. Pitchers with high pitch count totals will tend to have high PAP totals. If a PAP function provides no additional insight into which pitchers will be injured that pitch count totals alone, there is no reason to add the added complexity of a PAP system to our sabermetric arsenal.