Three days of the pitchf/x condor …

There appears to be something funky about at least three games worth of pitchf/x data from 2013.

I was playing around with learning to use ggplot2 and using Justin Verlanders data from 2013.  This revealed a strange pattern of pitch movement during the three starts on 4/25, 7/9, and 9/7 where the pfx_x and pfx_z data appear to be scaled differently.

pfx_x vs pfx_z for JV 2013-2016

I’ve taken two other three-game samples from 2013 and also the entire season (without the three odd games) and the average pfx_x and pfx_z data look like this:

 

Dataset
All games except 4/25 7/9 9/7
Games of 5/5 7/4 9/13
Games of 5/6 7/6 9/16
Games of 4/25 7/9 9/7
PITCH pfx_x pfx_z
FF -1.577 8.204
FF -1.961 9.155
FF -1.599 8.059
FF -0.849 3.501
PITCH pfx_x pfx_z
CH -1.08 3.923
CH -1.227 4.475
CH -0.725 4.079
CH -1.246 0.694
PITCH pfx_x pfx_z
CU 3.129 -5.93
CU 3.114 -5.58
CU 3.079 -5.952
CU 2.202 -9.302
PITCH pfx_x pfx_z
SL 1.809 0.333
SL 1.851 1.257
SL 1.013 0.114
SL 1.426 -3.141

I’d love to hear from anyone who has seen anything similar, or who might have an idea as to what might be going on.  I’m sure the problem lies with the data, but I’ve :cough: been wrong before.

And … bear with me while I figure out how to make tables and plots.  Tons of fun, but I’m at the simple stage for now :-þ

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cap56cruncher

Long-time resident of London, Ontario - with an all-too-short diversion to Quebec City. Married to my best friend for 35 years and counting, and proud father of the five nicest kids on the face of the planet.

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