As reader (and fellow blogger) sky pointed out in my earlier post, you can attempt to classify pitches using break and velocity. So I tried to do that with Peavy in his last start at Shea …

The x axis is deviation in inches from a theoretical pitch with no spin. The pink data points are the vertical breaks of the pitch and the blue ones are the horizontal breaks. So there are two data points for each pitch and they are plotted by velocity on the y axis. I’ll let Doctor Nathan describe exactly what these breaks are:

pfx_x,pfx_z: The deviation (in inches) of the pitch trajectory from a straight-line in the x (horizontal) and z (vertical) directions between y=40 ft and the front edge of home plate, y=1.417 ft. It is important to note two things. First, the initial value is y=40 ft, regardless of the value of the initial value y0 (defined below). If the pitcher’s release point had been used (approximately y=55 ft), then the deviation would have been nearly twice as large. Second, the effect of gravity has been removed from pfx_z, so that both parameters are the “break” of the pitch due to the Magnus force on a spinning baseball. Note that the online Gameday reports the quantity pfx, which is presumably the square root of pfx_x²+pfx_z². Given our sign conventions, a positive value of pfx_x cooresponds a deviation to the catcher’s right and a negative value to the catcher’s left. Similarly, a postive value of of pfx_z is a pitch the drops less than it would from gravity alone (most pitches fall in this category), whereas a negative value is a pitch that drops more than from gravity alone (e.g., a “12-6″ curveball).

Yea, what he said. : )

You can see at least 3 pitches that Peavy worked with in this game. He threw a fastball (probably 2 and 4 seamers), an 85-88 mile per hour slider, a slower 79-83 mile per hour slider (I think), and a few change ups (again, I think …).

I believe there’s a better way to display this with a graph, but I’m still working on my “graphing skills”. Anyhow, I think it’s interesting to actually visualize this stuff. It’s a nice compliment to hearing somebody say what pitches someone throws or trying to remember what you saw on tv.

While, perhaps, I haven’t quite precisely classified what Peavy throws, at least we have a glimpse of what he tossed against the Mets on August 22nd.

Of course, that’s a relatively small sample. The next step is doing this with more than one game and diverging into different kinds of analysis. Again, some people are really doing great work with this data. Check out the links I provided in the first Peavy post and/or some of the ones on my sidebar. Me … I’m just getting started. But hopefully I can share a few interesting things as I explore the data.