Somewhat Pretty Pictures

Ok so the last couple of posts probably have been pretty boring to most people. So I am going to interject with some plots from pitchFX system so we can maybe get a better feel for things. First up I want to break down all the pitches tracked by pitchFX by what park the pitch was thrown at.

Click on all of these plots to enlarge them. As you can see, the system rolled out first mostly on the west coast and then moved east skipping some parks along the way. If you are fan of a team in the AL west your teams will have huge amounts of pitchFX data to work with. If your favorite team is in the AL east or NL central then not so much. PitchFX has just been added to the New York parks and to Tropicana with less than 2,000 pitches thrown in them. As I pointed out in my last post, RFK has only seen one game with the system turned on. Looking at this discrepancy in the amount of data and then looking at the errors on each of the parks in the post below it is pretty clear that getting to at least a few thousand pitches is important if we want to be able to do anything with the statistics in those parks. With less than a month left in the season, this seems unlikely in at least three parks.

Moving on to the actual data, the only quantities that pitchFX actually measures are an initial position, velocity, and acceleration in the x, y, and z directions. So lets take a look at some of these quantities starting with our favorite, z0.

Starting with the uncorrected data you can see that most pitches are thrown at a height of about 6 feet but if you look closely you can see another bump around 3 feet. That must be where the sidearmers throw. Often when comparing data that spans several magnitudes people will plot that data on a logarithmic plot (here is a wiki article on log plots if you are interested) and here is one of the same data below.

It might not look very similar but if you look at the statistics in the upper right hand corner they are identical. The only difference is in the Y axis which now is on a logarithmic scale. This scale is really handy at looking at the tails of the distribution and looking at this plot we can see several bumps as we go down in release point. The data continues until the release point is actually negative! On the other side we see some pitches that were thrown at a release point of 10 feet. Obviously something is wrong here and if you look at these plots pitcher by pitcher you won't find just one guy who is causing the problems. This appears to be our first sign (though others have shown plenty more) of pitchFX just whiffing on a pitch. What about when we apply our correction factor from the post below?

Here the data appears to be behaved a little better with a smoother drop as we go down in z0. There still are some values that are just way out there but things are looking a bit better and the RMS (which is a fancy way of calculating something like variance) has gone down which is something we would expect from corrected data. What about the x0 data?
The x0 data shows what you would expect with two peaks, one on the left side of zero (this is the right handed pitchers remember these coordinates are as the catcher sees them) and another on the right side. Both peak around two feet from zero and both have a tail that goes out. The real question is why are there so many points near zero? The answer is pitchers stand on different parts of the rubber. If a left handed pitcher stands at the extreme left side of the mound he is going to release the ball very close to zero, or right in the middle of home plate. Lets zoom in at take a look at the plot in log form.

Again we can see a shoulder in the data that is where the sidearmers are. This is easier to see from teh lefties but it is there for the right handers as well. Also, we see some more pathological points extending out 10 feet from 0. Just like with the z0 data we are going to have to clean that up before we can start to really analyze it. Do things get any better with the corrected data?
We still see just as many pathological points but the peak where the sidearmers are throwing is more clear. Again, this is exactly what we would hope for in correcting the data. Hopefully, as the large error on the x0 correction goes down the data will get even more clear. What about the initial velocities.

Because the y direction is towards home plate the initial velocity in y is the largest component in the initial speed of the ball. All the values are negative because the ball is traveling to home plate from 55 feet. I have converted this into miler per hour to make things easier to see. The peak here is at about 90 MPH with a shoulder around 82 MPH. Presumably, the points near the peak are mostly fastballs and the points near the shoulder are breaking balls. How about the tails of these distributions? Do they show as many ugly points at the positions?
It looks to me that this plot is much more reasonable. There are a few points near 105 MPH but some pitchers (Zumaya) might be able to get it close to that and if they were pitching in a park with a fast pitchFX system that night that doesn't seem to unreasonable. What about the pitches on the other side? Why are there so many pitches below 60 MPH? A possible explanation would be intentional balls. It is possible that a pitcher is just lofting those in at a very low speed. To check that we can plot all of the velocities of those intentional balls because that data has been added to the system.

So the really, really, slow ones are not from intentional balls. Those seem to be a good portion of the balls thrown near 60 MPH but few of them are below 50 MPH and none of them are below 40 MPH. So again it appears that there is some issues with the data. Hopefully these outliers can be properly removed and then real study can begin.