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Credit Pitch Selection for Zito's Turnaround

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While Barry Zito isn't exactly earning every penny of that $126 million deal, this year the former ace has pitched his way back into the ranks of respectability. What is responsible for Mr. Zito's turnaround, and will he keep it up? A look at the numbers will help us answer that question.

According to his peripherals, Mr. Zito has been a bit lucky this year. Through 8 starts, hitters are only batting 0.242 against him when they put the ball in play. That's a full .030 better than his first 8 starts in 2009, and .032 better than his career line. The large difference between his 2010 FIP and his career FIP (1.08) also indicates that Zito's numbers are in store for a significant correction.

As you can see in the table below, the Giants benefit substantially from Zito's peripheral improvement: he's contributed nearly an extra win compared to this point last season, and his W-L% is reminiscent of his Cy Young campaign. (Seasonal totals from the first eight starts of each season. Source: FanGraphs).

Season BABIP FIP WPA W-L%
Career 0.274 4.27 0.565
2009 0.272 4.01 0.483 0.200
2010 0.242 3.19 1.407 0.857
Delta -0.029 -0.82 0.924 0.65

Of course, we shouldn't be satisfied in chalking up Zito's performance to luck. First, that doesn't really tell us anything. Second, we don't know if that's true just yet. So let's dig a litter deeper, shall we? With the help of PitchFX data from Brooks Baseball, we can see if Zito's pitches are behaving any differently this year than last. Typically, I start off by looking at overall velocity across all pitches. In this particular case, however, it's clear that pitch speed isn't explaining Zito's 2010 boost. See the chart below:

Velocity_all_medium

The chart represents the season-to-date average velocity of Zito's pitches through equal numbers of starts in 2009 and 2010. As is clear, Zito's pitch velocity started out strong but is currently trending in the wrong direction. For some time now, Zito's pitches have been slower than during his eight disastrous starts in 2009. Certainly, this can't positively explain Zito's 2010 performance. What about break?

Star-divide

Break_all_medium

Note: I conflated horizontal and vertical breaks into a "Pythagorean" break value to arrive at the average break measurement. Pythagorean break = sqrt( h-break^2 + v-break^2 ).

The chart above does the same thing with average break as the previous chart does with average speed. And while Zito is adding break to his pitches as the season progresses, his pitches' average break is still short of what it was last year. The funny thing is, even though Zito's velocity and break are down, hitters seem to be having just as much trouble with his pitches. Zito's strike rate is essentially what it was this time a year ago.

Season Mean Velo. (MPH) Mean Break (in.) Strike Rate BABIP FIP W-L% WPA WPA/LI
2009 80.92 10.49 63.9% 0.272 4.01 0.200 0.483 0.249
2010 79.94 10.08 63.8% 0.242 3.19 0.857 1.407 1.327
Delta -0.99 -0.41 -0.1% -0.029 -0.82 0.657 0.924 1.078

 

In summary, Zito's pitches are slower and don't break as much as they did in 2009. Despite this, Zito's strike rate is almost identical to last year's. And even though his pitches are slower, don't break as much, and are just as effective at the plate in 2010 as in 2009, his results are far better. Clearly, this data isn't getting at what we need, so let's unpack it even further.

Season Pitch Ratio Mean Velo. (MPH) Mean Break (in.) Strike Rate
2009 Four Seamer 48.2% 86.66 12.62 60.5%
2009 Two Seamer 0.4% 85.10 10.89 33.3%
2009 Curve 16.8% 73.67 10.38 66.9%
2009 All
80.92 10.49 63.9%
2010 Four Seamer 27.5% 85.57 11.57 62.2%
2010 Two Seamer 20.8% 85.32 11.54 62.4%
2010 Curve 22.5% 72.46 11.64 62.0%
2010 All
79.94 10.08 63.8%
Delta Four Seamer -20.7% -1.09 -1.05 1.8%
Delta Two Seamer 20.4% 0.22 0.65 29.0%
Delta Curve 5.7% -1.21 1.26 -5.0%
Delta All
-0.99 -0.41 -0.1%

 

Well now we're getting somewhere. When we disaggregate Zito's fastballs and curveballs from the rest of his pitches, we see a substantial difference between this season and last. Zito is relying a lot more on his two-seamer this year, seemingly at the expense of his four-seam fastball. Either that, or Zito changed the spin of his four-seamer so that PitchFX picks it up as a two-seamer; the important thing is that he modified the spin on his fastball. Moreover, he's utilizing his curveball more often. Overall, Zito's pitch selection is far more balanced this season; see below:

Ratios_medium

While we can't be sure that pitch selection is responsible for Zito's favorable results--again, the strike rate hasn't changed much and speed and break are still down--I surmise this might have something to do with Zito's low BABIP and other waxing indicators. The added break on his two-seamer and curve may be inducing more batters to softly ground out--indeed, his GB/FB and GB% are all sitting at multi-year highs, while his LD% and FB% are at multi-year lows. This is both remarkable and probably unsustainable. Finally, the more balanced pitch selection means that hitters can't as easily anticipate Barry's four-seamer.

And no, Barry Zito is not going to keep up this pace. New pitches are useful, but they probably can't buy you thirty BABIP points. Hopefully, for Giants fans, Zito leveling off will look a lot more like his last start than his second-to-last. That said, if the break on his pitches continues to improve, and if the former Cy Young winner can keep his velocity up, then Barry Zito might be able to keep up with Tim Lincecum, Matt Cain and Jonathan Sanchez in the Bay Area Batters Frustration Club.


W-L G GS CG SHO SV BS IP H R ER HR BB K ERA WHIP
2010 - Barry Zito 6-1 8 8 0 0 0 0 54.1 39 13 13 1 20 34 2.15 1.09

Comment 43 comments  |  0 recs  | 

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Yes, here here!

Great debut. I can get overwhelmed by PitchFX, but I do love when it is eloquently used like this to answer a question.

On Twitter: @baseballtwit

by adarowski on May 19, 2010 9:49 AM EDT up reply actions  

There are a few things about your approach I don't understand

1. Why do you want to compare game-by-game from 2009 to 2010? What is to be gained by that. I’m not aware of any evidence that game-by-game velocity measurement changes are meaningful. It is true that some pitchers generally improve their fastball velocity as the season goes on, and it’s true for the league as a whole that they gain fastball velocity as April passes and as the temperature increases. But it doesn’t seem like that’s what you’re getting at here. I’m not sure why it’s relevant what his fastball velocity was in game 3 vs. game 4 last year or this year.

2. I don’t see any meaning in any of the numbers prior to splitting by pitch types. Lower average pitch velocity is not necessarily a bad thing. Some pitchers might be more successful if they threw more off-speed stuff.

3. His fastball spin/break looks very close to the same from last year to this year. That MLBAM has started labeling more of them as two-seamers is very likely a function of the re-working of their classification algorithm over the offseason and nothing to do with any changes from Zito. His fastball is somewhat slower this year, though that’s before removing any effects from temperature, point in season, or PITCHf/x measurement issues.

Zito looks to me like very much the same pitcher pitch-wise as last year, except that this year he’s throwing his change-up for strikes a little more often and get more whiffs with it. His fastball velocity is down a tick, but again I’m not sure whether that’s a sample bias issue or not.

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 19, 2010 10:19 AM EDT reply actions   1 recs

1. awesome signature.

2. J-Doug pretty clearly makes the case that changes in velocity doesn’t explain this year’s results:

Typically, I start off by looking at overall velocity across all pitches. In this particular case, however, it’s clear that pitch speed isn’t explaining Zito’s 2010 boost

3. Thus, he looks for other explanations.

by Justin Bopp on May 19, 2010 10:33 AM EDT up reply actions  

That's true

But in any case that would not be where I would start. If he’d made the case that Martians didn’t explain this year’s results, that would probably be correct, too. I’m suggesting that is not a good way to approach pitch data, fwiw.

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 19, 2010 10:36 AM EDT up reply actions  

That's what confuses me here

What’s really the significance of average pitch velo for the entire arsenal?

As noted, that could be affected just as much by pitch usage as by legitimate changes in velocity. I think that it makes way more sense to look at each pitch individually when talking about velo, and really to focus on the pitches individually before focusing on other things.

Alas, I’m no Pitch F/X expert though..

I like baseball.
I write for Beyond the Box Score and The Hardball Times Fantasy

by Satchel Price on May 19, 2010 1:39 PM EDT up reply actions  

When he looked at it that way in his earlier analysis of Mo Rivera

it made more sense because Rivera only throws two pitch types, both fastballs. But for almost every single other pitcher who throws off-speed stuff I don’t think it works.

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 19, 2010 1:42 PM EDT up reply actions  

Ah, it's just another case

Where the normal rules of pitching don’t apply to Mo. That guy is a freak of sorts, per se.

But it does seem to be an odd, and unideal, way of looking at things when you’re talking about essentially a five-pitch (FB, two-seamer, curve, slider, change).

Personally, I’d like to know two things:

1. What Zito has done to improve his ground ball rate
2. Why people think that Zito is a totally changed pitcher even though his xFIP over 2009-2010 (246 innings) is just 4.46

I like baseball.
I write for Beyond the Box Score and The Hardball Times Fantasy

by Satchel Price on May 19, 2010 1:51 PM EDT up reply actions  

Significance

To say that average pitch velocity by itself means “nothing” is rather extreme. First of all, I’m not looking at it “by itself,” but how it trends over the course of the season. Second of all, the significance of the variable is entirely dependent on the context in which it occurs. It’s the combination of factors—velocity trends, pitch selection, and outcomes—that matters. The fact that Zito’s velo is trending down a full MPH and yet things are working out better for him raises some rather compelling questions, which is what I attempted to answer here.

Blogger and Editor, Rational Pastime Blog (http://www.rationalpastime.com/)

by J-Doug on May 19, 2010 3:30 PM EDT up reply actions  

But are things really work much better, or is he just getting luckier?

Because for all of his supposed improvements, his xFIP hasn’t improved from 2009 to 2010, and overall his only legitimate improvement is an increase in ground balls induced.

I like baseball.
I write for Beyond the Box Score and The Hardball Times Fantasy

by Satchel Price on May 19, 2010 4:21 PM EDT via mobile up reply actions  

xFIP

Satchel:

I get different xFIP numbers than FanGraphs presents when I run my calculations, but comparing Zito’s first 8 starts of last season to the first 8 starts of this season, he’s down by about 0.012. Not huge, but I’m not sure it’s insignificant. That said, his HR/FB is incredibly low, and I would expect it to tick up.

But I’m also not about to give xFIP the last word on pitcher performance. His tRA is down, his WAR/Start is up, all his pitch values are improving (except his cutter which he has banished as far as I can tell). In other words, I’m not ready to say he’s not improving based on xFIP just yet.

Blogger and Editor, Rational Pastime Blog (http://www.rationalpastime.com/)

by J-Doug on May 19, 2010 6:53 PM EDT up reply actions  

.012 points of xFIP is insignificant

Given how good we are currently at estimating ERA from components, that .012 is well within the margin of error.

Secondly, tRA is not going to be as good as xFIP in a small sample size due to errors in batted ball classification. Most of the difference between tRA and FIP is just noise (unless a player has extreme batted ball numbers) and we know that xFIP is better than FIP in a ~50 inning sample.

Finally, WAR/start is based off of FIP and Pitch Values are based off of actual outcomes. Really it’s hard to make a case that Zito is pitching much better this year and the fact that his repetoire has remained mostly unchanged evidences that.

by vivaelpujols on May 19, 2010 8:00 PM EDT up reply actions  

That said,

I’d love to see what your step-by-step pitching analysis would entail. We might be able to come up with a nice, repeatable process.

by Justin Bopp on May 19, 2010 10:45 AM EDT up reply actions  

Well, I haven't published one in a long time

and the Stat Speak site (MVN) where I did is defunct, but I have republished some of my work from there on my old blog.

My Johan Santana article or Brian Bannister series is probably what I would consider the template for analysis, but I haven’t republished either of those, yet.

Two earlier ones that I republished were for Mariano Rivera and Erik Bedard:
http://fastballs.wordpress.com/2008/03/14/tales-of-the-cutter-mariano-rivera/
http://fastballs.wordpress.com/2010/04/18/tales-of-the-curve-an-analysis-of-erik-bedard/

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 19, 2010 11:11 AM EDT up reply actions  

Thanks, Justin!

I’ve now re-posted my Johan Santana analysis from two years ago:
http://fastballs.wordpress.com/2010/05/19/tales-of-the-changeup-an-analysis-of-johan-santana/

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 19, 2010 12:24 PM EDT up reply actions  

The few polar plots of yours that I've seen confuse me a bit.

You have 180° as “Breaks Away” and 0°/360° as “Breaks In,” but curveballs spin near 360° and fastballs spin near 180°.

What am I missing?

by NoNameOnCard on May 19, 2010 1:43 PM EDT up reply actions  

They are from the pitcher's perspective

That’s why backspin = 0/360° and topspin = 180°. That’s opposite of the catcher’s perspective.

I forget why I chose that perspective. It’s been over two years since I made those charts.

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 19, 2010 3:00 PM EDT up reply actions  

The catcher's perspective wouldn't change "breaks up" from 180 to 90...

180° should be “breaks up,” and 0°/360° should be “breaks down.” This is the root of my question.

Are you converting the spin angles to match a “90° is vertical” orientation?

by NoNameOnCard on May 19, 2010 4:45 PM EDT up reply actions  

Correction...

From pitcher’s perspective, 180° should be “breaks down” and 0°/360° should be “breaks up.” I’m puzzled as to how they got shifted by 90° when being flipped from the catcher’s perspective.

by NoNameOnCard on May 19, 2010 4:49 PM EDT up reply actions  

Ah, I understand now

I was graphing spin deflection angle, not spin axis angle.

I’m not sure if I’d do that the same way if I made that graph today. At the time, nobody knew what I was talking about when I talked about spin axis angle, etc. I was taking a lot of the terminology from Alan Nathan’s papers and trying it out for the audience.

Nowadays even MLBAM has added spin axis angle to their data, so it has a pretty commonly accepted understanding and convention. Back then it was not so.

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 19, 2010 4:53 PM EDT up reply actions  

Hey Mike

What do you think about putting together a little tutorial for how to produce those and putting it up as a fanpost? We could then have a little contest to see who can make them look the best, similar to how Sky ran the HoF-zone thread.

Sounds like fun.

by Justin Bopp on May 19, 2010 1:49 PM EDT up reply actions  

A contest like that sounds interesting

I doubt I will get around to making a fanpost, though.

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 19, 2010 3:02 PM EDT up reply actions  

I appreciate the snark...

…but I think where you stop looking is more important than where you start. Moreover, when a pitcher’s velocity is trending down a full MPH, I think that’s worth investigation.

Blogger and Editor, Rational Pastime Blog (http://www.rationalpastime.com/)

by J-Doug on May 19, 2010 3:20 PM EDT up reply actions  

The snark was for Justin

I agree that Zito’s fastball velocity drop could be worth investigating, if someone wants to do that.

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 19, 2010 3:28 PM EDT up reply actions  

The point is that overall pitch velocity means nothing

A guy could be throwing harder with his fastball, but slower with his curveball (both are good things) and his overall velocity would be unchanged.

I’ve done a lot of “what is this pitcher doing differently?” analysis’ and I would suggest boiling it down into a few simple steps:

1) Reclassify the pitchers pitches. Given the errors in the Pitch f/x classification algorithm and the fact that you need to be able to pick up small subtle changes, I think this is very important.

2) Look at velocity, vertical movement, horizontal movement by pitch type.

3) Look at location by pitch type/count

By far the three most important parts of pitching are pitch selection, stuff and location, so those are the things you should look at first.

by vivaelpujols on May 19, 2010 8:05 PM EDT up reply actions  

Re: There are a few things

1. Mike, you answered this yourself when you wrote "it’s true for the league as a whole that they gain fastball velocity as April passes and as the temperature increases." I don’t think it’s a safe assumption that Zito will come out of the gate pitching top-speed and with perfect mechanics, so I make sure my 2009 and 2010 samples are homogeneous on this variable. Moreover, I don’t think you quite read the graph. I’m not comparing game x 2009 to game x 2010. I’m comparing their seasonal averages through that game. I find this gives us a better idea of trends than just looking at individual game data, which includes a good deal of static. Later in the season I’ll be using moving averages, but it’s a bit too early for that.

2. Yes, that’s true. But we don’t know until we look, which was why I brought it up and then looked deeper.

3. Does it look the same? I admit that time constraints kept me from disaggregating data per pitch. I will note that FanGraphs agrees with me, and they don’t get their data from MLBAM, rather from Baseball Info Solutions. Moreover, I would be very surprised if they tweaked the algorithm so substantially that half of Zito’s 4-seamers turned into 2-seamers, or that Zito’s cutter disappeared and was replaced by curveballs.

Blogger and Editor, Rational Pastime Blog (http://www.rationalpastime.com/)

by J-Doug on May 19, 2010 3:17 PM EDT up reply actions  

I didn't understand the graph

Thanks for the clarification. I’m still not sure about that approach because it’s still including a great deal of noise and other variables, but it’s not quite what I thought it was.

Fangraphs gets their PITCHf/x data from MLBAM. Their BIS pitch data doesn’t split fastballs into two-seam or four-seam because that’s too difficult for most people to do by video.

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 19, 2010 3:30 PM EDT up reply actions  

Well, forgive me if I'm wrong, but...

FanGraphs does have a separate category for Two-Seamer (http://www.fangraphs.com/pitchfx.aspx?playerid=944&position=P) which they label FT, and I believe what they label as Fastball (FA) is what Brooks Baseball labels as a Four Seamer.

Moreover, this is the quote at the bottom of their page: “All major league baseball data including pitch type, velocity, batted ball location, and play-by-play data provided by Baseball Info Solutions.”

But I don’t work at FanGraphs, so I could be wrong.

Blogger and Editor, Rational Pastime Blog (http://www.rationalpastime.com/)

by J-Doug on May 19, 2010 3:33 PM EDT up reply actions  

Fangraphs gets data from both places

From BIS they get data that is classified by a “video scout”. They report the classifications as FB, SL, CT, CB, CH, SF, KN, XX, and PO. The FB group includes both four-seam and two-seam fastballs.

From MLBAM they get the PITCHf/x data. That’s the data you’re linking to that has the FT (two-seam/sinker) and FA (four-seam) distinction.

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 19, 2010 4:07 PM EDT up reply actions  

Zito throws a slider and a changeup. There’s also talk about Zito’s “cutter”, but I’m really not sure it’s any different from either his 4 seam or 2 seam fastball, it always seemed to me it was just a fastball with a bit of movement on it, or maybe it’s similar to his slider….either way, I’m not sure it’s really a “unique” pitch in his arsenal.

I think overall it’s an interesting topic, and you made efforts to delve deeper into it, but I’m unsatisfied you went deep enough. You made a claim that his FIP was lower so he’s probably not going to sustain that – well, you might be right, but why? And how much “correction” should we expect going forward? His strikeouts are down by a lot – definitely a bad sign, walks are down some, a good sign – how sustainable are those two things? The big difference looks like HR/FB, so that’s a sign you might be right, but then again, he IS getting more GB’s and IFFB’s – how sustainable are those? I don’t have answers, but I think if you do, it could give us more clues into what to expect out of him going forward.

The next thing where I don’t think you went deep enough was just the pitches. His arsenal is bigger than you looked at. I liked what you were doing, but include all his repetoire – I like the individual pitch breakouts, but in addition to velocity and break, maybe look at both horizontal and vertical break? Maybe look at the handedness of batters somehow? I’m under the impression (not sure I’ve ever seen it confirmed, though) that horizontal break tends to have more of a platoon split while vertical break tends to work more against both hands…..so who’s he throwing those pitches to?

The last thing I think you need to look at is beyond just strike rate – how often is he throwing it in zone and out of zone, and how often is he inducing swings, and swings and misses in each of those zones?

So…..yeah, there’s a lot to look at!

by Missing Barry on May 20, 2010 1:35 PM EDT reply actions  

You can always go deeper

But sample size is going to be a daunting issue only 8 games into the season. Even with a full season, sample size can be a big problem when you start splitting by batter handedness and pitch type (which you need to do to make sense of many things).

I’d be curious what his batted ball distribution is looking like. Using Sean Kelly’s tool (http://katron.org/projects/baseball/hit-location/), I don’t notice anything that stands out except that the batters just aren’t hitting the ball as far in the air off Zito as they were in 2009. Could be interesting if that data was split out by pitch type, but again, it starts making the sample size very small.

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 20, 2010 4:20 PM EDT up reply actions  

Of course sample size is an issue for some of my suggestions and really limit what we can get out of the data, but I really think some of my suggestions are necessary to get anything out of what we’re discussing. Just including his full repetoire, for instance. The stuff about in zone and out of zone swing%‘s and swing and miss %’s, too.

by Missing Barry on May 21, 2010 11:15 AM EDT up reply actions  

Yep, no argument from me about those things

Winner, Beyond the Box Score 32 Predictions Contest, 2009

by Mike Fast on May 21, 2010 5:25 PM EDT up reply actions  

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