The PitchFX Data for the Rays/Phillies Endless Game 5 is still posted under 10/27/08.

The strikezone maps include all of the calls from Monday.

Just a heads up for anyone planning on using any of it.

The scariest part about Daisuke is that he consistently pitches this way. We're talking about a guy who pitched 7 shutout innings, striking out 9, while walking 4. Walking the bases loaded in the first inning and managing to escape. Stranding a runner on third with 0 outs. It shouldn't be possible to walk the bases loaded in the first and pitch a no-hitter through 6. But for whatever it's worth: it is.

For those of you still wondering what the dots mean, here is a plot of all the pitches Daisuke threw with annotations:



Green: Changeup
Blue: Slurve (Slider/Curveball)
Orange: 2-Seam Fastball
Red: 4-Seam Fastball
Purple: Cutter

While that plot is nice for looking at all of the pitches, this one might be a bit nicer for breaking down what actually worked for DiceK over the course of the game:



Here we can see his 9(!) strikeouts in black: 2 changeup, 5 fastball, 2 cutter (although, one of those is a very slow cutter, more like a true slider). You can also see that a bunch of his trouble came from the Slurve - 3 walks and 2 singles off of it.

That's the initial breakdown, but I'll have more on this start tomorrow.

A link to Daisuke's performance in Game 1 of the ALCS can be found here.

Today's post concerns an interesting trend in pitch distribution: "establishing the fastball". You often hear about this strategy from broadcasters, but essentially the idea is to establish that you will throw your fastball early in the game (perhaps to set hitters up in terms of timing or trajectory), and then work off of that set up to effectively mix in your other pitches.

My disclaimer here is first that I'm just looking at a few pitchers on one pitching staff that's been caught by one catcher the majority of the season. Can we capture this trend and gain some insight into pitch distribution?

Data for this project has been gathered for from every game in the 2008 season. Pitch identification has been done by the MLB Gameday Algorithm, which isn't great, but we're also looking for something that's supposed to be a very large effect, so it's possible that this won't prevent us from finding it.

To begin, I'll look at Daisuke Matsuzaka, who's fun to write about and sometimes aggrevating to watch pitch.

We'll start by dividing up "Pitch Counts" into a series of 20-pitch groupings and then looking at the relative distribution of pitch types within those groups.



You can pretty clearly see that the proportion of fastballs (plotted here in green) decreases steadily through the first 40 or so pitches, and the proportion of sliders generally increases; both of these values then level off into a relatively stable proportion for the rest of the start. Meanwhile, the relative distribution of other pitches stays essentially unchanged.

I've labeled these things here:


So, it's fairly easy to see that the pitch distribution for Daisuke, averaged across all of the games in the season, is at first biased heavily (over 60%) in favor of throwing a fastball, which steadily levels off to around 50%, and the proportion of sliders increases from less than 20% to greater than 30%.

These effects are even more dramatic when looking at what Daisuke throws on an 0-0 count:


Early in the game you have an over 80% likelihood of seeing a first pitch fastball, which decreases to (and levels off at) just above 50%. Likewise, seeing a slider on the first pitch starts at around 5% and increases to (and stablizes at) 25-30% likelihood.

Some pitch distributions, however, remain relatively unchanged. For example, if you get into a full count, in most game situations the pitch distribution is relatively equivalent (although, caveat emptor, there's a lot of variability due to small sample size):


On the other hand - and I was quite surprised by this - if you're in any 2-strike count, the pitch distribution still follows the game plan. So, early in the game he's not trying to put you away with the slider.


What does all this mean? Well, I think one thing it shows is that although a pitcher (like Daisuke) might have a relatively stable pitch distribution after some reasonable point in the game, using the aggregate pitch distribution numbers that are shown on some websites might not be such a good idea. In order to get a good idea of the real proportion of pitches, it's best to first adjust for establishing the fastball.

Let's take a look at other Red Sox pitchers to see if we can get a better handle on this. Here's Jon Lester, showing a similar trend, but with a quicker "fastball establishment":


But, the trend becomes more like Daisuke's trend if you look at only 0-0 counts:


So, again, over the first 40 pitches, the fastball is "established" and continues to lose likelihood of being thrown, while the curve and slider/cutter increase. Of course, Jon Lester throws a much larger proportion of fastballs, but the trend is still relatively apparent.

For Josh Beckett, on the other hand, we see a much more gradual decline in the relative proportion of fastballs thrown over the course of the game:


But again, this trend (40 pitches of fastball establishment) is recaptured quite nicely if we look at only 0-0 counts:


So, what have we learned? Well, it's fairly easy to see "Establishing the Fastball" as a gameplan strategy by the Red Sox staff as a whole (and not just Daisuke), and it appears to take about 40 pitches before Sox pitchers stablize into their gameplan. After that, the relative proportion of pitches remains relatively unchanged.

There is a thread at Sons of Sam Horn entirely devoted to talking about Jon Lester.

This is odd, because it is against their policy of megathreads, but if you're looking for some retrospective analysis of Jon's stuff over the course of the season, you could just compile that and post it on the web. A friend and I are planning to do that, just after I manage to crawl out from the mound of papers currently stacked up on my desk (note: if my advisor is reading this, it's my first blog post in a month, really).

Anyway, a recent discussion was about whether or not Jon was getting stronger as the season went on. Fair question. Here's my post on the issue:




The first figure is simply a graph showing his average fastball velocity and average curveball velocity over the course of the season, for all the games except Philly (their system is pretty clearly broken).

There's a steady rise in both Fastball and Curveball velocity, suggesting that the rise in fastball velocity isn't due to a change in fastball type distribution.


The other graph is a bit more psychadelic, so here is the explanation. I realize that averaging across pitch types can be bad because of the known issues in trying to identify pitches, so I took one of his first starts from each month of the season and plotted each pitch on the same Horizontal Movement X Speed axis. To account for the fact that different systems may have slightly different speed readings I used his first start at Fenway for each month.

Warmer colors (yellows and oranges) are early in the season, cooler colors (blues and purples) are later in the season.




I think it's pretty clear that the velocity increase is not due to pitch misidentification or something else, as the velocity increase is really across the board. Cooler colors are clearly above warmer colors in each cluster in this figure.


For those struggling to identify these pitches I have labeled them.

1. Bottom Left (Ugly Dark Purple) - Curveball
2. Middle Left (Light Blue) - Cutter (a few sliders towards the curveball side)
3. Top Middle (Green) - 4Seam Fastball [a few changeups are thrown with this kind of movement and erroneously grouped in the circle, they are the very slow 4seam fastballs, sorry]
4. Top Right (Light Purple) - 2Seam Fastball
5. Bottom Right (Orange) - Changeup

Some updates from around the internet:

Oliver Perez seems like quite the popular figure, as he is the focus of an update on New York Mets Daily devoted to a PitchFX analysis of what's worked since his mechanics change (http://newyorkmetsdaily.com/?p=209) by Brian Joura. Perez is also one of the players examined in a Newspaper article (http://www.nysun.com/sports/is-the-metamorphosis-of-perez-pelfrey-for-real/82691/) by Tim Marchman.

Jeff Samardzija has recently been the subject of an article (http://bleacherreport.com/articles/41242-jeff-samardzija-pitchfx) by Kanka, who looks at some of the pitches he threw while making his major league debut.

Jon Lester is pretty damn good this year, and has been inspiring all sorts of media. Peter Bendix takes a look at Lester's progression in an article (http://www.beyondtheboxscore.com/2008/8/4/585966/jon-lester-the-best-pitche) on his blog.

As always, if you're planning on writing an article about pitching or a pitcher and either have questions about using PitchFX data or need specific graphs or plots made, send me an email at dan@brooksbaseball.net.