When David Price was chosen by the Tampa Bay Rays with the first overall pick of the 2007 amateur draft, it probably would not have surprised fans to find him as one of the best pitchers in the American League in the 2010 season.  In between, however, has been an interesting journey with a number of adjustments for Price along the way.

Price made a rapid ascent through the minor leagues in 2008, dominating High-A Vero Beach and Double-A Montgomery with sub-2.00 ERAs, 92 strikeouts in 91.2 innings, and a sparkling 11-0 win-loss record.  He was promoted to Triple-A Durham in August 2008 and held his own with a 4.50 ERA and 17 strikeouts in 18 innings.  He was called up to the big leagues and debuted with the Rays in a pennant race, pitching mostly out of the bullpen in September.  He pitched in three games in the American League Championship Series and two games in the World Series, striking out eight in 5.2 innings and acquitting himself well against October competition.

2009, however, was a year of struggles for Price.  He was sent back to the minors to begin the season, and after he was called up in late May, he posted a 5.60 ERA through his first 11 starts, failing to finish the fifth inning in five of those games.  Though he had posted 54 strikeouts in 53 innings, he had also given up 33 walks and 11 home runs.  He finished the remainder of the season on a stronger note, recording a 3.58 ERA over his final 12 starts, allowing only 6 home runs and 21 walks in 75.1 innings, but also cutting his strikeouts to 48 over that time frame.

In 2010, David Price emerged as the dominant starter people expected when he was drafted.  He finished third in the American League with a 2.72 ERA and boasted a splendid 19-6 win-loss record.  His peripherals were solid, with 188 strikeouts in 208.2 innings against 170 hits, 79 walks, and 15 home runs allowed.

Let’s take a look at the pitches that Price throws and how his repertoire has evolved during his tenure with the Rays.

Evolution of his repertoire

As you will see, classifying Price’s pitches can be a bit of a challenge when he’s frequently changing what pitches are in his repertoire.  However, I’ll go out on a limb and say that Price has used six pitch types in the major leagues: a four-seam fastball, slider, curveball, and three variations on a sinking pitch which I have identified as a two-seam fastball, split-finger fastball, and changeup.

I’ll explain the varieties of sinkers and changeups in a moment, as well as his journey from one pitch type to another.  Let’s start by talking about what Price threw when he broke into the majors in 2008, mostly pitching out of the bullpen.

For those of you not familiar with my previous writing, I enjoy analyzing the detailed pitch data that has been collected on pitchers for the past few years using the PITCHf/x camera systems that are installed in all 30 major league stadiums.  PITCHf/x tracks the speed and trajectory of nearly every pitch thrown in major league games, and the information is available for download from Major League Baseball’s Gameday website.  I have created a database of this pitch information and use it to analyze pitchers.  A number of other analysts have done similar work, including Josh Kalk, who published at the Hardball Times before being hired by the Rays in 2009.

Let’s look at what the PITCHf/x data show us about the pitch speed and spin movement of the pitches he has thrown.  We’ll go through each of the stages of the evolution of Price’s pitch repertoire, beginning with 2008.

David Price was basically a two-pitch pitcher as a reliever in 2008.  He threw a 94-mph four-seam fastball two thirds of the time, and the other third of the time he threw an 87-mph slider.  He also showed a changeup, but it was not a regular part of his repertoire out of the bullpen.

When he returned to the majors in May 2009 as a starting pitcher, he threw his four-seam fastball slightly slower, averaging 93.4 mph, but it was still his main pitch.  He expanded his off-speed offerings to right-handed hitters, adding an occasional changeup and a rare curveball or two-seam fastball.  You’ll recall that he was not especially effective during this period, and he struggled with his control.

In the second half of 2009, Price added a 90-91 mph two-seam fastball and cut back on his slider usage.  He threw the two-seam fastball almost exclusively to right-handed hitters, and used it almost as often to them as he did the four-seam fastball.

In his last three starts of 2009 and continuing into 2010, Price began to feature his curveball much more prominently and nearly abandoned his slider.  He also increased the speed differential between his four-seam fastball and two-seam fastball, as he threw the sinking fastball only 89-90 mph.

From May through August of 2010, the evolution of Price’s two-seam fastball continued.  He decreased the speed of the pitch even further to an average of 87 mph, such that it could probably best be described as a split-finger fastball.  At the same time, he upped his average four-seam fastball speed to 95 mph.

Finally, in August and September, Price largely abandoned the splitter (or whatever you want to call the high-80s sinking pitch) and replaced it with a harder two-seam fastball, thrown nearly as hard as his now 96-mph four-seam fastball.

We’ve examined each of the major phases of David Price’s pitch repertoire development. Let’s view the same thing a different way by looking at his pitch selection by game throughout his career.

We see that Price began his career as a four-seam fastball and slider pitcher, then added a two-seam fastball, then a curveball. Next, he replaced the two-seam fastball with a splitter, then went back to the two-seam fastball.  Toward the end of 2010, he increasingly favored the two-seam fastball over the four-seam fastball.

Pitch repertoire description

Let’s talk a little more about each of his pitch types.

First, the four-seam fastball.  Price has gained speed on his four-seamer in 2010.  In 2008, mostly in relief, his heat was measured at an average of 94.3 mph by PITCHf/x.  In 2009, it was measured at 93.5 mph; however, the Tampa Bay PITCHf/x system was recording speeds about 0.8 mph too slow that year.  That would imply Price’s real 2009 average fastball was more like 93.9 mph, assuming a roughly equal number of pitches at home and on the road.  In 2010, his average four-seamer was recorded at 95.2 mph.  The Tampa Bay PITCHf/x system was still recording speeds about 0.8 mph too slow until mid June; after that it was fairly well calibrated for speed.  The calibration adjustments to the PITCHf/x data give us an average four-seam fastball speed of about 95.4 mph for the 2010 season, or 1.5 mph faster than it was in 2009.

There has been some talk about Price progressively increasing his fastball speed during the 2010 season.  I believe this perception was mostly, but not totally, an artifact of the PITCHf/x calibration adjustment in mid June.  In August and September of 2010, his four-seam fastball averaged about 95.9 mph.

Price gets about eight inches of hop and seven inches of tail on his four-seam fastball.  That’s pretty typical for a major-league four-seamer.  He heavily relies on the pitch to left-handed batters, throwing it 75 percent of the time to them during 2010, whereas to righties he throws it only 49 percent of the time and mixes in the two-seam fastball.  The four-seamer is his primary strikeout pitch, generating 85 percent of his strikeouts of lefty batters in 2010 and 67 percent of his strikeouts of righties.  Price uses a classic four-seam grip, which you can see here.

We discussed earlier that David Price debuted a two-seam fastball in the second half of the 2009 season.  To recap, it was a pitch he threw 90-91 mph, about three mph slower than his four-seamer.  In 2010, he switched to a slower version that I’ve called a split-finger fastball before returning to a much harder two-seam fastball in August and September.  This new two-seam fastball averaged 95.1 mph, or within one mph of his four-seam fastball.  He gets about six inches of hop and 11 inches of tail on his two-seam fastball, which is about four or five inches of movement relative to his four-seamer.  In August and September, Price used the two-seamer only six percent of the time to left-handed batters but 37 percent of the time to right-handed batters.  You can see his two-seam fastball grip here and here.

Price’s split-finger fastball, as I’m calling it here, is a slower version of his two-seam fastball that existed primarily from May 12 to August 4, 2010.  His average speed on this pitch was about 87.4 mph, or almost eight mph slower than his four-seam fastball.  That’s almost a changeup speed differential, and I might have called it a changeup were it not for an even slower offspeed pitch type thrown by Price, which we will discuss in a moment.  His splitter gets about five inches of hop and nine inches of tail, fairly similar to his two-seamer.  During the time period where this was his main sinking offspeed pitch, May to July, he threw it 15 percent of the time to right-handed batters and rarely, if ever, to lefties. (I counted two such instances.) I’ve looked for game photos of his splitter grip from games in the May 12 to August 4 time frame, but so far I’ve had no luck finding any.  I’d guess his splitter grip is pretty similar to his two-seamer grip, with the variation coming in how tightly he grips the ball into his palm rather than from major changes in seam orientation.

As mentioned previously, Price has another slower sinking off-speed pitch.  I’ve called this pitch type a changeup.  His changeup averages about 83 mph, or 12 mph slower than his four-seam fastball.  He gets about seven inches of hop and 10 inches of tail on his changeup, very similar spin movement to his two-seam fastball.  He has thrown the pitch exclusively to right-handed opponents, about four percent of the time during the 2010 season.  I’ve not been able to find a game photo that I can conclusively identify as a changeup grip, but this one looks suspiciously like a circle change to me, though it wasn’t taken from the best angle for grip identification.

Coming up through the minors, Price’s slider drew high praise, and it was his main secondary pitch at the end of the 2008 season.  However, we’ve seen a lot less of the slider since he developed the curveball toward the end of 2009.  He throws the slider about 86-87 mph, with very little spin movement.  When it was his main breaking ball in 2008-2009, he threw it equally to righthanders and lefthanders.  In 2010, he used it mostly to lefties (12 percent of the time) and rarely to righties (three percent of the time), preferring instead to use the curveball against right-handed batters.  You can see a photo of his slider grip here.

There is some indication in his last couple starts, September 23 and September 28, 2010, that Price might be evolving his now seldom-used slider into a cutter.  The slider was thrown a little harder with a little more hop in those two games.  It’s a very small sample size, a total of five pitches, but it was enough to pique my curiosity, and it’s something I’ll be paying attention to in the playoffs.

Price’s favorite breaking pitch is now a curveball. He throws the curveball at about 78 mph on average, and he gets five inches of cut and eight inches of drop due to spin.  If you include the effect of gravity, his curveball drops about 2.5-3 feet. In 2010, he used the curve 11 percent of the time to left-handed batters and 17 percent of the time to right-handed batters.  He uses a spike curveball grip that you can see here.

Pitch mix

We’ve looked at some changes in Price’s pitch repertoire and examined some of how he uses each of his pitches.  Let’s also look at how he mixes his pitch types in different ball-strike counts.  Below, I show his pitch mix for 2010, split out by batter handedness.


To left-handed batters, Price uses mostly his four-seam fastball.  This is especially true when he falls behind in the count; lefties will see the four-seamer 87% of the time in this case.  When he is even or ahead in the count, he’s a little more likely to throw a breaking pitch (26% of the time).

Price uses his off-speed and sinking pitches more freely with right-handed opponents, though he still favors his four-seam fastball as a strikeout pitch on 0-2 (70% of the time).   He throws his curveball most often (19% of the time) to righties when even or ahead in the count, and his splitter and two-seam fastball when he gets behind in the count.

Pitch results

What kind of results did Price get with each of his pitch types in 2010?

Pitch Number Ball CS Foul SS InPlay BACON BABIP SLG HR Strk% Con%
FB4 1841 0.34 0.17 0.23 0.11 0.15 0.319 0.299 0.500 0.028 66% 77%
FB2 507 0.33 0.15 0.20 0.09 0.22 0.219 0.205 0.325 0.018 67% 82%
Spl 208 0.34 0.17 0.15 0.09 0.25 0.327 0.300 0.481 0.038 66% 81%
Chg 105 0.33 0.18 0.19 0.07 0.23 0.208 0.208 0.292 0.000 67% 86%
Sld 172 0.35 0.17 0.16 0.10 0.22 0.135 0.086 0.361 0.054 65% 79%
Crv 521 0.39 0.22 0.17 0.07 0.15 0.342 0.333 0.468 0.013 61% 81%

Price has thrown all six of his pitch types for strikes this year.  The four-seam fastball and two-seam fastball generated impressive whiff rates, 11% and 9% respectively, as compared to 7% and 6% major-league average.  His off-speed and breaking stuff, however, was not terribly impressive in that regard.  He had some pretty low batting averages allowed on balls in play (BABIP) for the two-seam fastball, the changeup, and the slider.  I looked a little deeper into this but did not find any patterns that suggested this was likely to be a persistent trend.  It’s possible I missed something that data from additional seasons may reveal more clearly.

Let’s look now at where he locates his pitches to right-handed and left-handed batters. Strike-zone location charts are shown from the perspective of the catcher. The location of a pitch is indicated where it crossed the front plane of home plate.

The first thing that is obvious from this graph is that David Price faces many more right-handed batters than left-handed batters.  Price has faced 77 percent right-handed batters; this is fairly typical for a left-handed starting pitcher.  Against righthanders, Price throws his four-seamer both inside and outside.  He’s very successful at getting swinging strikes when he gets the ball up and away within the strike zone.  Against lefthanders, he keeps the four-seamer away, and he gets quite a few called strikes where the umpires typically expand the outside edge of the zone to lefty batters.

Price pitched with a similar pattern with all of his sinking pitches: the two-seam fastball, the split-finger fastball, and the changeup (as I have labeled them), so I’ll discuss them together.  He rarely throws any of the them to left-handed opponents.  To right-handed batters, he kept them on the outside edge.  He does well at throwing them for strikes, and the two-seamer seems to be the best of the three at fooling opponents into swinging and missing.

As already discussed, Price cut back on his slider usage in 2010.  When he did use it, he kept it away from lefties and brought it inside to righties, which is a typical approach for a left-handed pitcher.  Price was able to throw the slider for strikes, but otherwise it was fairly unremarkable, generating below-average numbers of whiffs.

On the other hand, Price used the curveball much more like a typical breaking pitch, inducing swings and misses on pitches down and out of the zone, though again, his whiff rate on the curve was below average when compared to the league.  To right-handed batters, he mostly kept the curveball across the middle of the plate, and he was able to keep it in zone at a slightly above average rate (62 percent vs. league average of 57 percent).  Against left-handed batters, he moved the curveball more toward the outside edge, and consequently, his curveball strike rate was lower to lefties (57 percent).

Conclusions

It has been interesting to watch David Price develop into the ace of the Rays’ pitching staff.  It has been fascinating for me to dive into how he accomplished that and to learn about the evolution of his repertoire across seasons.  It’s rare that a pitcher is that willing to continuously experiment, adapt, and evolve.

He has a dominant 95-96 mph four-seam fastball that serves him well against left-handed batters and a four-seamer/two-seamer pairing that has helped him improve against right-handers in 2010.  His breaking pitches are average offerings that fill out a solid repertoire.  Though his performance on batted balls going forward may not be expected to be as good as it was in 2010, his stuff certainly seems to support his ability to carry the mantle of staff ace in the future.

Note: This article was originally published at the Statistically Speaking blog at MVN.com on February 28, 2008.  Since the MVN.com site is defunct and its articles are no longer available on the web, I am re-publishing the article here.

 In Part 1 of this series, we examined Brian Bannister’s suggestions for why he has been able to beat the league BABIP. He indicated that it was probably due to pitching more often in favorable pitcher’s counts and inducing balls in play with two strikes, when the hitter is against the ropes. However, the evidence didn’t show much advantage for Bannister. We noted that he did pitch a little more often in favorable counts, but this led to him avoiding walks more than anything; it had little salutary effect on his BABIP.

In Part 2 of this series, we learned about the pitches that Bannister threw during 2007 and how he used them. We saw that the fastball and curveball were good pitches against right-handed hitters, and the slider was a good pitch against left-handed hitters.

Part 1
Part 2
Part 3

In this final part of the series, we’re going to marry those two approaches to see if we can uncover any patterns that might explain Bannister’s BABIP performance. In this portion, I’m not concentrating so much on evaluating Bannister’s own statements, as I did on Part 1. Rather, I’m thinking more about what we can expect from Bannister in the future. I’m also interested in investigating techniques that could prove useful for evaluating DIPS theory on a component basis as we accumulate more PITCHf/x data in the coming seasons.

Should we expect Bannister to maintain any of his BABIP edge and thus his 3.87 ERA from 2007? Or are the projection systems like PECOTA (subscribers only) and CHONE more reasonable when they project an ERA of 5.19 or 4.74?

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Note: This article was originally published at the Statistically Speaking blog at MVN.com on February 26, 2008.  Since the MVN.com site is defunct and its articles are no longer available on the web, I am re-publishing the article here.

In Part 1 of this analysis, we examined the league numbers for batting average on balls in play (BABIP) and whether Bannister was able to beat the league BABIP by pitching in favorable counts. We found that he did not gain any particular advantage by inducing more balls in play on two-strike counts, so we turn elsewhere to seek an explanation for his 2007 performance.

Part 1
Part 2
Part 3

What pitches does Brian Bannister throw? The scouting reports tell an interesting tale, especially if you follow them back a couple years. In the minor leagues, the cut fastball was reputed to be his best pitch. His four-seam fastball was thrown in the high 80’s, touching 90, although he was able to locate it well, his curveball was a big breaker that was considered a plus pitch, his changeup was a work in progress, and his slider was regarded as a pitch likely to be scrapped. But in the fall of 2006 in the Mexican League, Bannister worked on a two-seam fastball, and after joining the Royals in trade for Ambiorix Burgos, he scrapped his cutter, experimented with different speeds on his curveball, and started throwing a slider again.

What can we see in the PITCHf/x data regarding his pitch repertoire in 2007?

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Note: This article was originally published at the Statistically Speaking blog at MVN.com on February 24, 2008.  Since the MVN.com site is defunct and its articles are no longer available on the web, I am re-publishing the article here.

I’ll warn you from the start that the title is a tad ambitious. I don’t know exactly how Brian Bannister wins in the major leagues with a below-average fastball speed, but I hope to share some of what I have learned on the topic. This article will take the form of a three-part series.

Part 1
Part 2
Part 3

In case you’ve been hiding under the proverbial sabermetric rock the last few weeks–maybe you’re one of those weirdos who believe players are human or you’ve been out of your garage recently to look at the sky–Brian Bannister gave a fascinating three-part interview to Tim Dierkes at MLB Trade Rumors last month.

In Part 3 of the interview, Bannister talked about his opponents’ batting average on balls in play (BABIP).

I think a lot of fans underestimate how much time I spend working with statistics to improve my performance on the field. For those that don’t know, the typical BABIP for starting pitchers in Major League Baseball is around .300 give or take a few points. The common (and valid) argument is that over the course of a pitcher’s career, he can not control his BABIP from year-to-year (because it is random), but over a period of time it will settle into the median range of roughly .300 (the peak of the bell curve). Therefore, pitchers that have a BABIP of under .300 are due to regress in subsequent years and pitchers with a BABIP above .300 should see some improvement (assuming they are a Major League Average pitcher).

Because I don’t have enough of a sample size yet (service time), I don’t claim to be able to beat the .300 average year in and year out at the Major League level. However, I also don’t feel that every pitcher is hopelessly bound to that .300 number for his career if he takes some steps to improve his odds – which is what pitching is all about.

In the interview, Bannister postulated a reason for his success on BABIP.

So, to finally answer the question about BABIP, if we look at the numbers above, how can a Major League pitcher try and beat the .300 BABIP average? By pitching in 0-2, 1-2, & 2-2 counts more often than the historical averages of pitchers in the Major Leagues. Until a pitcher reaches two strikes, he has no historical statistical advantage over the hitter. In fact, my batting averages against in 0-1, 1-0, & 1-1 counts are .297/.295/.311 respectively, very close to the roughly .300 average.

My explanation for why I have beat the average so far is that in my career I have been able to get a Major League hitter to put the ball in play in a 1-2 or 0-2 count 155 times, and in a 2-0 or 2-1 count 78 times. That’s twice as often in my favor, & I’ll take those odds.

This interview has gotten a lot of buzz in sabermetric cyberspace. Several people have taken a look at BABIP at different ball-strike counts, including my colleague at StatSpeak, Pizza Cutter. There seems to be some ability for the pitcher to control the count on which hitters put balls into play, but it looks like a fairly small effect on average. (Pizza, correct me if I’m summarizing your conclusions incorrectly.)

Bannister also mentioned to Dierkes that getting two strikes on the hitter gives him the strategic advantage in terms of pitch selection.

It is obvious that hitters, even at the Major League level, do not perform as well when the count is in the pitcher’s favor, and vice-versa. This is because with two strikes, a hitter HAS to swing at a pitch in the strike zone or he is out, and he must also make a split-second decision on whether a borderline pitch is a strike or not, reducing his ability to put a good swing on the ball. What this does is take away a hitter’s choice. If I throw a curveball with two strikes, the hitter has to swing if the pitch is in the strike zone, whether he is good at hitting a curveball or not. He also does not have a choice on location. We are all familiar with Ted Williams‘ famous strike zone averages at the Baseball Hall of Fame. It is well-known that a pitch knee-high on the outside corner will not have the same batting average or OBP/SLG/OPS as one waist-high right down the middle. Here is a comparison of the batting averages and slugging percentage on my fastball vs. my curveball:

Fastball: .246/.404
Curveball: .184/.265

We do know from John Walsh’s work something about batting average and slugging percentage against the typical major-league fastball (.330/.521) and curveball (.310/.471). If Bannister is correct in his numbers, he’s doing quite a bit better than the league with both the fastball and curveball. But is Bannister correct in the numbers he quotes and assertions he makes?

So far, most people are accepting what Bannister said at face value. Let’s take a closer look and see if we should believe his numbers and conclusions. We’ll draw on two data sets from the 2007 season. One is the standard pitch-by-pitch result data for all of Bannister’s 2603 pitches in 2007. With this data set we can examine results on balls in play and how Bannister performed in various ball-strike counts. The second data set is the detailed PITCHf/x trajectory data recorded for 1304 of Bannister’s pitches, or about half of his starts. With this data set we can identify pitch types and reliable strike zone location information in order to gain a greater understanding of Bannister’s pitching strategies.

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Note: This article was originally published at the Statistically Speaking blog at MVN.com on December 22, 2007.  Since the MVN.com site is defunct and its articles are no longer available on the web, I am re-publishing the article here.

What if we knew what type of pitches every major league pitcher threw? What if we had detailed pitch-by-pitch data about how he used those pitches in every game situation? What if this information was accurate and freely accessible to baseball researchers?

Let’s begin with some history. Since Sportvision’s PITCHf/x system was unveiled during the 2006 playoffs, people have been thinking about using the detailed pitch data to classify pitches by type. Reference this comment by MLBAM’s Director of Stats, Cory Schwartz:

“When the system is installed in all 30 ballparks, it will provide unprecedented accuracy, consistency and depth of data to the measurement of speed and trajectory of each pitch,” Schwartz said. “Ultimately we’ll be able to use this data to determine the pitch type in real time and with greater accuracy than ever before. By recording all of this data in real time, we can provide it to broadcasters such as FOX, in-stadium scoreboards, fans via Enhanced Gameday, clubs and other business partners.

It wasn’t long before Baseball Analysts’ Joe Sheehan was leading the public research down that path, too, publishing articles in the spring of 2007 about pitch classification for pitchers like Jeff Weaver, Mike Mussina, and Kenny Rogers, using the data from the 2006 playoffs.

In April 2007, the PITCHf/x system was installed in nine ballparks, and this produced a wealth of data that encouraged more people to join the analysis fun. Dan Fox, Bill Ferris, and Steve West were among the leading PITCHf/x researchers in the first half of 2007, and although the work in the field covered a number of topics, pitch classification was often at the forefront.

Soon the quest turned toward developing a set of rules to classify pitches for many pitchers, perhaps for every major league pitcher. John Walsh published the early definitive article on this topic. In August, the analysis really began to heat up; for example, see these articles from John Beamer and Joe Sheehan. The quest for a pitch classification algorithm was on.

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Note: This article was originally published at the Statistically Speaking blog at MVN.com on February 18, 2008.  Since the MVN.com site is defunct and its articles are no longer available on the web, I am re-publishing the article here.

Recent evidence may suggest otherwise, but I am still a contributor to Statistically Speaking. I’ve been working on an analysis that has been more difficult to bring to fruition than I expected; that, along with “real life” getting in the way more of late, is what has severely cut into my posting frequency.

However, in the process of number crunching for the analysis I’m doing, I came across some statistics that I haven’t seen posted publicly anywhere, not even in the Baseball-Reference splits. (Some of it is in the B-R splits, but not most of it.) Maybe I’ve just missed them, in which case drop me a line and let me know where else you found them. I thought these might be interesting to a few other people, so I’ll share them. Mostly, I’m just putting the numbers up here for the rest of you to enjoy, but I’ll also make a few comments on some trends that stuck out to me.

I’m looking at pitch data broken down by ball-strike count. I’m using the MLB Gameday 2007 data as my source. Today I present the breakdown of types of balls put into play by the hitter.

Ball Strike Total Pitches Total Safe Total Out Single Double Triple Home Run Field Error Other Safe
0 0 22029 0.341 0.659 0.214 0.069 0.007 0.039 0.012 0.001
0 1 17222 0.329 0.671 0.222 0.062 0.005 0.027 0.012 0.001
0 2 7878 0.319 0.681 0.228 0.049 0.005 0.022 0.013 0.001
1 0 14030 0.344 0.656 0.212 0.070 0.007 0.044 0.010 0.001
1 1 16576 0.334 0.666 0.214 0.066 0.006 0.034 0.012 0.001
1 2 14626 0.326 0.674 0.220 0.059 0.006 0.025 0.014 0.001
2 0 5015 0.355 0.645 0.202 0.077 0.007 0.056 0.012 0.000
2 1 10308 0.349 0.651 0.212 0.074 0.007 0.041 0.014 0.001
2 2 14861 0.330 0.670 0.215 0.062 0.009 0.030 0.012 0.001
3 0 251 0.402 0.598 0.167 0.120 0.008 0.092 0.012 0.004
3 1 4393 0.376 0.624 0.214 0.083 0.009 0.056 0.013 0.001
3 2 11019 0.351 0.649 0.216 0.070 0.007 0.045 0.012 0.001
- total 138208 0.338 0.662 0.216 0.066 0.007 0.036 0.012 0.001
Ball Strike Ground Out Fly Out Pop Out Line Out Force Out Ground into DP
0 0 0.208 0.195 0.073 0.043 0.036 0.034
0 1 0.270 0.183 0.067 0.047 0.034 0.034
0 2 0.291 0.181 0.070 0.047 0.039 0.033
1 0 0.225 0.206 0.078 0.048 0.031 0.032
1 1 0.267 0.194 0.070 0.046 0.031 0.030
1 2 0.293 0.181 0.076 0.047 0.033 0.028
2 0 0.218 0.217 0.077 0.051 0.028 0.027
2 1 0.254 0.198 0.075 0.049 0.026 0.025
2 2 0.278 0.194 0.076 0.051 0.031 0.025
3 0 0.171 0.219 0.096 0.040 0.024 0.020
3 1 0.213 0.213 0.081 0.049 0.023 0.021
3 2 0.264 0.212 0.080 0.055 0.009 0.012
- total 0.254 0.195 0.074 0.048 0.030 0.029
Ball Strike Sac Bunt Sac Fly Double Play Bunt Ground Out Field. Ch. Out Bunt Pop Out Other Out
0 0 0.033 0.014 0.004 0.010 0.002 0.005 0.001
0 1 0.015 0.010 0.004 0.004 0.002 0.002 0.000
0 2 0.004 0.010 0.003 0.000 0.002 0.001 0.001
1 0 0.014 0.011 0.004 0.002 0.002 0.001 0.000
1 1 0.010 0.008 0.003 0.003 0.002 0.001 0.000
1 2 0.002 0.007 0.003 0.000 0.002 0.000 0.000
2 0 0.008 0.013 0.005 0.000 0.002 0.000 0.000
2 1 0.005 0.010 0.003 0.002 0.002 0.000 0.000
2 2 0.001 0.009 0.003 0.000 0.002 0.000 0.000
3 0 0.000 0.024 0.000 0.000 0.004 0.000 0.000
3 1 0.004 0.012 0.004 0.001 0.003 0.000 0.000
3 2 0.001 0.009 0.005 0.000 0.001 0.000 0.000
- total 0.011 0.010 0.004 0.003 0.002 0.001 0.000

Ball in Play Safe Percentage vs Count

A hitter reaches base safely more often on balls in play when the count is in his favor. Don’t change the channel, the revelations like that just keep on coming at StatSpeak, and you don’t want to miss one!

Okay. My first slightly less than completely and utterly obvious observation is that the home run rate is strongly tied to the count.

Ball in Play Home Run Percentage vs Count

The doubles rate shows the same effect, but smaller, as does the triples rate to some extent. The singles rate stays pretty flat with respect to count, although there is a bit of an inverse effect–in better hitter’s counts, the hitter gets more extra base hits and slightly fewer singles.I haven’t looked at the type of batted ball (fly ball, line drive, ground ball, bunt, etc.) that results in hits. That’s a bit more difficult to parse out of the Gameday data. Since it doesn’t have its own field, getting that information requires some regular expression matching on the text description of the play. That’s fairly straightforward but nonetheless a nontrivial bit of coding that makes it a project for some point in the future rather than part of this data set for me.

Ball in Play Groundout-Flyout Ratio vs Count

Another thing I noticed was that there were more groundouts and less flyouts the more strikes and less balls there were in the count. As pitchers gain the upper hand, they tend to get more groundball outs. I didn’t include popups and line drives in the accompanying chart since they didn’t show a strong tendency relative to count.

I saw a couple other things that are obvious once you think about them, but it was interesting to me to see them reflected in the data. The first was that force outs, GIDPs, and fielder’s choice outs all go down dramatically with a 3-2 count, dropping from 6.4% to 2.3% of balls in play. Presumably this is because the runners are often going with the pitch on 3-2.

The second thing that interested me was the favorite counts for hitters to bunt for an out. (Bunting for a hit is not included for the reason mentioned previously.)

Count Bunt Outs
0-0 0.043
0-1 0.019
0-2 0.004
1-0 0.016
1-1 0.013
1-2 0.002
2-0 0.008
2-1 0.006
2-2 0.001
3-0 0.000
3-1 0.005
3-2 0.001

If I don’t get around to presenting my full analysis in a timely fashion, I’ll see if I can present a few more statistical tidbits like this along the way.

Note: This article was originally published at the Statistically Speaking blog at MVN.com on December 13, 2007.  Since the MVN.com site is defunct and its articles are no longer available on the web, I am re-publishing the article here.

I don’t know any other major league pitcher who relies on his cut fastball to nearly the same extent as Mariano Rivera, but there are many pitchers who use a cutter to some degree. Most of them, like Josh Beckett, merely put a little “cut” on a fastball now and then, and it’s debatable whether to classify it as a separate pitch in their repertoire. Some of them, like Greg Maddux, throw both a cut fastball and another fastball as fairly distinct pitches. A few others, like our subject today, throw a single type of fastball that moves more like a cutter than it does like a traditional four-seamer. Do we also label this kind of a pitch a cut fastball?

The cutter is second only, perhaps, to the slider in the flexibility of its definition. Almost every starting pitcher is said to throw a cutter by an obscure report somewhere. I’ve learned to discount these notional references, but I pay a lot more attention when the pitcher himself or his catcher says he threw a cutter.

Which brings us to Joakim Soria, closer for the Kansas City Royals. The Royals picked him up from the San Diego Padres in the Rule 5 draft last winter, and what a find that was! He had been pitching well in the Mexican League, and showed his stuff for the Royals last year when the closer of plan, Octavio Dotel, was first injured and later traded. Soria appeared in 62 games, pitched 69 innings, allowing 46 hits, 19 walks, and only three home runs, while racking up 75 strikeouts to go with 17 saves and 2.48 ERA.

What pitches does Joakim Soria throw? His catcher John Buck reports:

“It’s hard to pick him up. His ball has a natural cut to it. Not as much as [Rafael] Soriano but it does have a cut to it. That’s just his natural fastball,” Buck said.

“He has a great slider and curveball and can throw his change-up on any count. You have to kind of speed up your bat to get the head up to hit the cutter and, all of a sudden, he throws a changeup and it makes it difficult — sitting in-between those two is a tough place to be as a hitter.”

So his catcher calls his fastball a cutter. Let’s take a look at the data we have from PITCHf/x for the 2007 season, covering 477 pitches for Joakim Soria. I’ll begin with a graph of pitch speed versus the angle at which the spin on the ball is deflecting the pitch.

Soria has a fastball with a lot of cut that runs 89-94 mph. The cut fastball is his bread-and-butter pitch; he uses it for 69% of his pitches to lefties and 78% of his pitches to righties.

He has a changeup with a lot of lateral action that he throws 80-84 mph. He uses the changeup almost exclusively to lefties, making up 19% of his pitches to them.

As his off-speed pitch to righties, Soria uses a slider with a big break that runs 76-81 mph. The slider makes up 11% of his pitches to right-handed hitters.

Rounding out his repertoire is a slow curveball that Soria throws 66-71 mph. The curveball makes up 10% of his pitches, and he uses it equally to lefties and righties.

Let’s look at how these pitches move from the hitter’s perspective.

All of Soria’s pitches have good movement. His fastball has”cut” to it, and his changeup has good lateral and vertical movement when compared to his fastball. His slider looks like most pitchers’ curveballs, and his curveball is a slow ball with a lot of drop.

Next, let’s look at what pitches Soria throws in each ball-strike count.

Count Cutter Changeup Slider Curveball Total
0-0 114 6 6 0 126
0-1 40 14 12 2 68
0-2 19 3 2 16 40
1-0 39 3 1 0 43
1-1 35 3 5 1 44
1-2 19 2 1 20 42
2-0 14 0 0 0 14
2-1 24 1 0 0 25
2-2 22 7 5 10 44
3-0 0 0 0 0 0
3-1 3 1 0 0 4
3-2 25 2 0 0 27
Ahead 78 19 15 38 150
Even 171 16 16 11 214
Behind 105 7 1 0 113
0 strikes 167 9 7 0 183
1 strike 102 19 17 3 141
2 strikes 85 14 8 46 153
Ball 0-1 266 31 27 39 363
Ball 2-3 88 11 5 10 114
Total 354 42 32 49 477

And here’s the same information presented graphically:

We can see that until he gets a strike, Soria uses almost only the cut fastball, and when he gets two strikes, he brings out the curveball pretty often, except in a 3-2 count, where he sticks with the cutter. This would imply that the curveball is his strikeout pitch and that he has trouble getting strikes with his off-speed pitches.

As a second opinion, you can look at what Josh Kalk’s algorithm spit out for Joakim Soria. Josh also has release point data there if you are interested in that.

Finally, let’s examine where Soria throws his pitches and what results he gets.

LHH Ball CS Foul SS IPO IPNO TB BABIP SLGBIP Strk% Con%
Cutter 34 44 30 10 20 8 12 0.286 0.429 77% 85%
Changeup 15 3 11 5 5 2 3 0.286 0.429 63% 78%
Slider 2 0 0 0 0 0 0 0%
Curveball 10 1 1 10 1 0 0 0.000 0.000 57% 17%
RHH Ball CS Foul SS IPO IPNO TB BABIP SLGBIP Strk% Con%
Cutter 60 43 54 18 24 9 15 0.273 0.455 71% 83%
Changeup 0 1 0 0 0 0 0 100%
Slider 14 3 0 5 6 2 5 0.250 0.625 53% 62%
Curveball 10 5 2 7 2 0 0 0.000 0.000 62% 36%

–-
CS=called strike, SS=swinging strike, IPO=in play (out), IPNO=in play (no out), TB=total bases, BABIP=batting average on balls in play (including home runs), SLGBIP=slugging average on balls in play (including home runs). For Strk% all pitches other than balls are counted as strikes. Con% = (Foul+IPO+IPNO)/(Foul+IPO+IPNO+SS).

Our earlier conclusions seem to hold up.

Here are Soria’s results for the cut fastball.

To lefties, Soria seems willing to pound the zone with the cutter, and his results indicate that strategy works. Against righties, he works more up and away. He misses the zone a little more often, and he generates more foul balls, but his results are still good.

Moving on, let’s see the results for the changeup and slider:

As I mentioned earlier, Soria uses the changeup to lefties and the slider to righties. In both cases, he likes to throw down and away. It looks like he has trouble throwing the slider consistently for strikes.

Last, but not least, the curveball.

Soria gets a lot of swinging strikes in the zone to both lefties and righties. The only difference appears to be when he misses–down and away to righties, and up and away or down and in to lefties.

Since I mentioned earlier that the curveball looked like Soria’s strikeout pitch, let’s check on that. We have PITCHf/x data for 40 of his 75 strikeouts. For those 40 K’s, 23 of them were on the curveball, 9 on the cutter, 4 on the changeup, and 3 on the slider.

I hope you enjoyed the analysis of one of my favorite players from my favorite team. My work’s had a bit of an “East Coast bias” lately, which feels a bit odd to me. I don’t expect to continue solely in that vein. If nothing else, you should see a Royal popping up in this space now and then.

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