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January 25, 2017 Prospectus FeatureTwo Ways to TunnelThe new pitch tunnels data released by Baseball Prospectus gives us a new glimpse into the repertoires of pitchers across the major leagues. Of course, this data is only as useful as the analysis it helps produce. To showcase how pitch tunnels data can help us better understand the success, or lack thereof, of certain pitchers, we’ll need to better understand how pitch tunnels manifest themselves in the real world. The title of this article— “Two Ways to Tunnel”—already signals that there isn’t a one-size-fits-all approach to this new data. While game theory might suggest that each individual pitcher has an optimal approach (or approaches), there can be dramatic differences in how different pitchers attack major-league hitters. As such, we should look at this tunnels data much like we would PITCHf/x data. It’s descriptive, and there are many ways to interpret and utilize the data. We’ll use modern pitchers to explain these concepts with requisite data, but first it’s worth revisiting a historical example. Jeff Long's very first post for BP over two years ago included the following quote about Greg Maddux, the patron saint of tunneling (yes, we know the majority of this quote is included in the introductory post about pitch tunnels, but it’s so good that it merits inclusion once again):
Greg Maddux is inarguably one of the best pitchers baseball has ever seen. Yet when you watched Maddux’s individual pitches, with no results to put his performance into context, he was pedestrian. Paradoxically, that was the key to Maddux’s success. In the latter half of his career, Maddux had a contemporary who was also among the best pitchers in the game at that time. The other pitcher’s name was Barry Zito, and his bullpen sessions surely inspired more confidence than Maddux’s. In fact, Zito’s downfall through parts of his career was that his raw stuff was so impressive that he had a hard time harnessing it—Zito averaged more than 3.5 walks per nine innings over the first seven years of his career with Oakland. Nonetheless, Zito still managed to be successful, producing nearly 20 WARP and winning a Cy Young award in those seven seasons. Maddux and Zito exemplify the concept of “two ways to tunnel." Success can come from tremendous raw stuff that hitters simply can’t adjust to—as was the case with Zito’s curveball. It can also come from deception—pitches that all look the same until they aren’t and suddenly you’re hitting a weak dribbler to second base. There’s more than one way to get major-league hitters out. *** Madduxing
Greg Maddux is one of the founding fathers of the pitch tunnels concept, explained through his “column of milk” analogy in the above excerpt. Maddux’s approach is typically what we think of when we think of “pitch tunnels”: the ability to fine-tune pitches so that they all fly through a small window a certain distance from home plate. When these pitches eventually diverge, it’s too late and the hitter is unable to adjust to variations in speed or movement. The result, the theory goes, is weak contact and the (more than) occasional whiff. At his peak, Maddux would use his full repertoire to change the eye level of the batter, change speeds, and work both sides of the plate. His willingness to throw all of his pitches in any count and to any part of the plate was amplified by the fact that all of his pitches looked the same to the batter. Maddux’s pitches didn’t have to move a lot, because he had already won the battle before the ball even reached home plate. The modern Maddux might just be Chicago right-hander Kyle Hendricks, who won the ERA title and finished third in the Cy Young voting this past season. Hendricks has a repertoire that might remind you of Maddux. It turns out that his approach is Maddux-like as well. Hendricks ranks 15th in baseball (among pitchers throwing 1,000 pitch pairs) in terms of having the smallest pitch differential at the batter’s decision making point—this is based on Hendricks’ Tunnel Differential, which measures the distance between back-to-back pitches 23.8 feet from the front of home plate. During those final 24 feet or so, Hendricks’ pitches move an additional three inches—that’s three inches of movement after the batter has decided if they’re swinging, and where they’re swinging.[i] The reality is that Hendricks is among the best in baseball at consistency from release to tunnel point. He has the sixth-smallest variation in release point in the majors, meaning that it’s exceptionally difficult to tell his pitches apart after release. Typically, pitchers with a lot of pitches in their repertoire feature larger differentials—this makes some intuitive sense, the more pitches you have, the less likely any two pitches will be close to one another in flight—but Hendricks manages to maintain a very tight tunnel despite an arsenal that includes three fastballs, a changeup, and a curve. The key to Hendricks’ success is that all his pitches look similar; it’s a feature, not a bug. Maddux would be proud. You’re probably wondering if Maddux and Hendricks are really alike. They are, and we have the data to prove it. Our tunnels data only goes back to 2008, but fortunately that’s the last season Maddux pitched in the major leagues. That season—his final one mind you—Maddux had the third-smallest release point differential in baseball. He had the eighth-smallest differential between pitches at the tunnel point. He had the second-least movement after the tunnel point. He was still roughly a league-average pitcher at 42 years old. *** Zitoing When he was on, Barry Zito was incredible. His curveball seemed to break four or five feet en route to home plate: Zito’s dominance came despite his being fairly predictable. Like clockwork he would use his fastball to get ahead and his breaking balls (curve or slider) to put batters away. Of course, when your pitches move as much as Zito’s did, you could afford to be a little predictable. As we mentioned previously, Zito was often plagued by his inability to throw strikes as his career walk rate hovered at around four batters per nine innings. Still, his stuff was good enough that he was able to pitch fairly effectively over a long 15-year career. While Zito wasn’t the same force that Maddux was, he is a perfect example of how great stuff can go a long way. In terms of tunnels data, Zito had the 19th-largest break:tunnel ratio in 2008 among pitchers throwing 1,000 pitch pairs. He also had the ninth-largest tunnel differential, meaning that his pitches did not look the same coming out of his hand, so hitters effectively knew what was coming when he threw it. This seems less than ideal, but the reality is that if your stuff is good enough it’s less critical that you fool hitters in terms of pitch identification. If Hendricks/Maddux are the blueprint for succeeding by shrinking your tunnels, Zito shows us how success can come without small pitch tunnels. This approach isn’t exclusive to Zito. Mike Mussina, Adam Wainwright, Roy Oswalt, and Ben Sheets were also big tunnel pitchers. Each of those guys had very successful careers even though they were, in this way at least, anti-Madduxes. If Hendricks is the modern Maddux, then Rich Hill is the modern Zito (easiest comp ever). Looking at our 2016 tunnels data, Hill ranks highly for the key factors we would identify with being an anti-Maddux. He has the greatest differential between sequential pitches at the tunnel point (11.4 inches). He has the second-highest ratio of break differential to tunnel differential, behind only Collin McHugh. Hill’s pitches move a lot. They move as soon as they come out of his hand, after the batter makes his decision to swing or not, once they cross the plate. They move all the time. Because of that, Hill can essentially throw just two pitches and post a 2.56 DRA. *** Just the Beginning This is arguably the most basic form of analysis that can be done with this pitch tunnels data. That said, what it lacks in insight or data it makes up for in philosophical importance. It shows that this data isn’t just made for leaderboards or simple analysis as to whether small tunnels are automatically “good” or large tunnels “bad.” There are many ways to be successful as a major-league pitcher, and tunnels simply provide a lens through which we can look at that success. This light analysis is just the overview. In the articles to come, we will discuss how the pitch tunneling data documents the contrasting approaches of Hendricks versus Hill. We will take Maddux’s column of milk and quantify it with actual numbers. We will pair pitch tunnels with other PITCHf/x data, giving us a more complete profile of what happens between the ball leaving the pitcher’s hand and arriving in the catcher’s mitt. Our new tunnels data opens up all sorts of new analytical opportunities. There’s the opportunity to look at specific teams to see if certain teams are trading for and/or signing specific types of players. (Answer: yes.) There are opportunities to see how players have changed over time, perhaps improving their tunnel ratios with the addition of new pitches. We can assess how effectively pitchers are sequencing their pitches, changing speeds, and much more. In the coming days, we will do a much deeper dive into what we see as the secrets to Hendricks’ success, and the success of others. We’ll also look at how one team in particular favors pitchers with a specific pitch-tunnel profile. But overall, we consider this to be just the tip of the iceberg, and we’re eager to see where other talented analysts take this data in the coming weeks and months. We’ll certainly be digging deeper into it, and we hope you will too.
Jeff Long is an author of Baseball Prospectus. Follow @JeffLongBP
3 comments have been left for this article.
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Interesting developments here, showing there's more than one way to skin a tunnel. Might be that certain analyses going forward might want to take tunnel range into account, that is, needing to separate data by small and large tunnel approaches.
I'm sure we'll learn more going forward, but my initial thoughts:
-- Small tunnel will almost always be successful as long as
1) Can consistently maintain it
2) Don't do so by selling out the movement, resulting in a lot of flat, straight souvenirs.
-- Big tunnel will work best with great Stuff -- enough speed/movement where it just doesn't matter if the batter can identify it.
This sounds suspiciously like fitting the data to the model. Small tunnels are great, except when you don't have one, but succeed anyway.
I recall that Maddux piece from years ago and it has always stuck with me. I agree with it 100%. But to write off the exceptions as pitchers who compensate with "great stuff", I think that reasoning is a bit simplistic. There's something missing from the equation, we just don't know what it is yet.