Kyle Hendricks might be a lot closer to Greg Maddux than he thinks.
One of the challenges of bringing BP's new pitching data to light is figuring out whether it’s useful and how we can leverage it to better understand what is happening on the field. As mentioned previously, we look at this in much the same way we look at pitch movement or velocity; we need to figure out how these tunnels data points interact with other components of a player’s performance to unlock a deeper understanding of what is happening.
Cubs right-hander Kyle Hendricks is a perfect subject to start with. As we mentioned in "Two Ways to Tunnel," Hendricks has some of the smallest pitch tunnels in all of baseball. Hendricks is often compared to Greg Maddux (including by us!), and we can see how he is in fact like Maddux in certain respects. It gives us an idea of how he’s successful, but only an abstract one. That is, we rationalize Hendricks’ success because we’ve seen Maddux do it before, but we don’t really know how all of the moving pieces come together.
In order to better understand how Hendricks is successful, we’ll have to dig into some of our new data to see what that can tell us about how he pitches.
Hendricks has steadily learned how to strike out opposing batters, increasing his K% by 55 percent from 2014 to 2015 and 2016, and it’s clear the effect that has had on his game. In fact, Hendricks’ new-found ability to strike batters out has resulted in him becoming one of the best pitchers in baseball as he has posted a sub-3.50 DRA over each of the past two seasons despite getting dinged for pitching (and winning an ERA title) in front of an elite defense.
Tunneling from Greg Maddux and Barry Zito to Kyle Hendricks and Rich Hill, and everything in between.
The 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 was on to something, whether he knew it or not.
One day I sat a dozen feet behind Maddux’s catcher as three Braves pitchers, all in a row, did their throwing sessions side-by-side. Lefty Steve Avery made his catcher’s glove explode with noise from his 95-mph fastball. His curve looked like it broke a foot-and-a-half. He was terrifying. Yet I could barely tell the difference between Greg’s pitches. Was that a slider, a changeup, a two-seam or four-seam fastball? Maddux certainly looked better than most college pitchers, but not much. Nothing was scary.
Afterward, I asked him how it went, how he felt, everything except “Is your arm okay?” He picked up the tone. With a cocked grin, like a Mad Dog whose table scrap doesn’t taste quite right, he said, “That’s all I got.”
Then he explained that I couldn’t tell his pitches apart because his goal was late quick break, not big impressive break. The bigger the break, the sooner the ball must start to swerve and the more milliseconds the hitter has to react; the later the break, the less reaction time. Deny the batter as much information—speed or type of last-instant deviation—until it is almost too late.
Introducing new tools to evaluate command and control through the lens of strikes.
About a year and a half ago, Baseball Prospectus revealed a suite of catching stats that formed the basis for our industry-leading valuation of catchers. These new stats would shape how we perceived and discussed catcher value, but they also opened the door to better understanding the performance of pitchers.
Two key statistics—CSAA and CS Prob—serve as the basis for the pitch framing portion of our catching metrics. Today, we’ll show how those same statistics can tell us a great deal about pitching as well. CS Prob was initially introduced in 2014 with Harry Pavlidis and Dan Brooks’ first catcher framing model. Early the next year, Jonathan Judge joined the effort and the team introduced CSAA, officially moving our framing models beyond WOWY.
Of the two, CS Prob—short for Called Strike Probability—is the more straightforward: the likelihood of a given pitch being a strike. CS Prob goes beyond what the strike zone ought to be and instead reflects what it is: a set of probabilities that depends on batter and pitcher handedness, pitch location, pitch type, and count. Good pitchers understand that while the strike zone is a dynamic construct, it nonetheless has some consistencies depending on which combinations of these factors are present. We calculate CS Prob for every pitch regardless of the eventual outcome.
The other statistic, CSAA, stands for Called Strikes Above Average; a measure of how many called strikes the player in question creates for his team. In the case of catchers, we isolate the effects of the pitcher, umpire, and other situational factors which allows us to identify how many additional called strikes the catcher is generating, above or below average. For catchers, this skill is commonly described as “framing” or, in more polite company, “presentation.”
For pitchers, we can apply a similar methodology—controlling for the catcher, umpire, etc. to identify the additional called strikes created by the pitcher. CSAA is calculated only on taken pitches, an important nuance. A pitch must be taken in order to be eligible to be called a strike by the umpire, so while CS Prob looks at all pitches, CSAA only takes into account pitches where the outcome is left up to the umpire.
What can these two statistics tell us about pitcher performance and skill? First, we should define a few important things:
Perhaps no modern pitcher has had mechanics, or results, as consistent as Greg Maddux.
The legend of Greg Maddux already has a life of its own, and he has been retired for only four years. The widely held perception of the bespectacled right-hander centers on his reputation as “the smartest pitcher who ever lived,” and the prevailing wisdom tends to overlook the raw talents that he brought to the mound. Maybe it's the glasses, with the clichéd connection between poor vision and intelligence. It could be the K rate, which hovered around the major-league average through his career, or maybe it was the indelible impression of a 42-year old Maddux retiring massive sluggers with an 85-mph fastball, but this was not a pitcher who survived only on guile while mentally calculating triple-integrals for every pitch thrown.
Maddux's reputation for intelligence was well-earned, as he had a cerebral approach to pitching and advanced knowledge of his craft. Maddux understood the concept of Effective Velocity long before Perry Husband had conducted his extensive research on the subject, thanks to Maddux's recognition of the relationship between pitch location and batter timing. He knew that a hitter had to begin his swing earlier in order to hit the ball squarely on a pitch located up and in, but that the hitter had a longer time to react to a pitch that was low and away. He also followed the words of Warren Spahn, who said, “Hitting is timing. Pitching is upsetting timing.”
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What are the real mechanical precursors of pitcher injury? And what is the real lesson of Mark Prior's injury history?
Pitching mechanics are a bit like long-snappers in football, in the sense that we hear about them only when something goes horribly wrong. Mechanics rarely enter the discussion until a pitcher gets hurt, but when an ace succumbs to injury, the village folk grab their torches and pitchforks to go on the hunt for blame.
Experience has taught me that there is rarely an isolated cause for a pitcher's injury, with confounding variables that include mechanics, conditioning, workloads, genetics, and plain old luck. The pitching delivery is a high-performance machine, with a multitude of moving parts that must work efficiently in concert for the system to perform at peak levels, and any weak link in the system can lead to a breakdown.
Writing that Kyle Drabek is no stranger to great expectations oversimplifies things. Drabek is the son of one Cy Young award winner, and he was traded for another before he had thrown a pitch in the majors. Those bloodlines are invaluable in baseball. Good genes can ensure athleticism, yes, but they can also prevent a player from wilting under the hot stadium lights. The physical stuff is easy for Drabek—his hammer curve, and a fastball that can touch the mid-90s, can get big-league hitters out, thanks for asking. The mental stuff is supposed to be, too—scouts labeled him a bulldog multipletimes during last spring; this tells you about his mindset (and excuses his occasional barking at hitters). Yet last season, both the physical and mental parts of Drabek fell apart.
For a time, Drabek made pitching in the bigs look easy. His first start in 2011 was a one-hitter spread over seven innings against an incumbent division winner. He would allow four runs over his next two starts. From that point on, Drabek met the wrath of major-league hitting. He would complete 60 more innings as batters hit .314/.416/.508 against him; Joey Votto, your sixth-place finisher in National League MVP voting, hit .309/.416/.531 last season. Back to the mental part of baseball: the idea is that failing in baseball is unavoidable and difficult. You need to be cut from a special psychological cloth to persevere and, more importantly, to adjust. In summation: failure is nature’s best educational tool. Drabek took this lecture seriously and spent the offseason working on his mechanics. Shi Davidi chronicled Drabek’s transformation:
An amazing music video featuring a World Series game between the Cubs and the A's was unearthed recently.
It was 1992. The Oakland A's, behind Tony La Russa, Rickey Henderson, Dennis Eckersley, and the Bash Brothers, were only a year removed from a three-year run in the World Series. The Cubs, meanwhile, had been to the playoffs once in eight years, and Greg Maddux was only just beginning his stretch as the greatest pitcher alive. Away from sports, Garth Brooks had friends in low places, Pearl Jam was destroying the charts, and Uncle Jesse was breaking little girls' hearts all over the world. Not to be forgotten, Chicago Cubs fan Richard Marx was dreaming of a World Series win for the North Siders.
From this early-'90s potpurri, a music video was born. No, it wasn't "Jeremy" or even that silly Beach Boys video that had Uncle Jesse up on stage drumming. Not even close.
Owner Jerry Reinsdorf writes another check to keep the White Sox competitive, along with other news and notes from around the major leagues.
LAKE BUENA VISTA, Florida—Santa Claus was roaming the lobby of the Swan and Dolphin Resort for a good chunk of Wednesday afternoon. However, few people seemed to notice. Perhaps it was because this Santa was not wearing a red suit and a white beard. Instead, White Sox chairman Jerry Reinsdorf wore business casual.
Attempting to plot the career path of those who may reach the 300-win plateau.
I’m excited to join Baseball Prospectus. If you’ve read any of my previous work, you may know me as something of a PITCHf/x guy. I’ve been learning about and writing about PITCHf/x since the pitch-tracking system was installed in major-league ballparks in 2007, so that description is apt. My interests extend beyond PITCHf/x to the physics of baseball and the details of the pitcher-hitter confrontation.
Cliff Lee's number of strikeouts opposed to walks is at record-setting proportions this season.
Most of the time when I begin writing or researching an article, the spark comes from seeing something noteworthy on MLB Tonight or in the box scores while checking to see how my fantasy team is performing. At the beginning of the week, Jered Weaver’s strikeout rate piqued my interest, which led to a rather long-winded but informative article on the reason for his vast spike in the rate as well as whether or not it held precedent. Today, the story is a bit different, but along similar lines, as after watching the last couple of innings of Cliff Lee’s most recent start—one in which he issued a walk and whiffed 11 hitters—I could not help but think about his extremely impressive strikeout-to-walk ratio. The guy has walked just six batters in 103 2/3, innings, while striking out 89, leading to a K/BB ratio of 14.83 that, yes, leads the entire sport.
It wasn’t exactly Lee’s ratio that got the motors in my mind churning, however, but rather the actual rate itself. I mean, the rate is used so frequently these days and has essentially been imprinted—no, not imprinted like in the Twilight movies… wait, did I just implicitly reveal I’ve seen all three?—into our statistical vernacular, but can anybody tell me who is credited as its inventor or when its rise to prominence began? I rummaged through my library, re-read most of Alan Schwarz’ The Numbers Game, and even Googled like a madman and still turned up nothing discussing the origin of the rate. It is a perfect example of a number that makes so much sense to use for several different purposes, yet whose origin has somehow managed to elude us. That isn’t to say that knowing the creator or how it was derived is important, but as an analyst it is always interested to learn where stats come from.
A look at the stylish left-hander's Hall of Fame chances through the prism of JAWS.
The other day I set out to write a piece covering the Hall of Fame cases of both Frank Thomas and Tom Glavine. Two thousand or so words in, I was neck deep into the Big Hurt's career, so I decided to spin the Glavine piece into a separate one. In parallel, Marc Normandin did a thorough job covering the ups and downs of Glavine's career, so rather than repeat what he's done, I'll skip to evaluating his Hall of Fame case and the context surrounding it.