Data Cleaning and Data Dreaming

I think there's some really great thought and work going on around cleaning up the noise in PITCHf/x. Via Mike Fast, here's a good post and discussion on the topic at ike2100.

While I understand the need to correct measurement error, as a recovering psychophysiologist, I'm more interested in correcting the measurement, not the error.

Obviously, Sportvision will work that end, while we throw away the junk, try and understand (not eliminate) weather and park effects, and manage them to help discriminate pitches.

I do like that the physicists want to go after the data in very interesting ways, down to the algorithm that is used to create the data. It furthers understanding in multiple dimensions, and I do enjoy thinking about and following the challenging problems.

The problems I want to tackle are more around developing a bag-of-tricks - metrics and visuals - that are intuitive, informative, and fun. Right now, I'm an open-to-the-world brain dump of ideas (some even my own), meandering about a fresh domain.

OK, anyway, GO BRAVES

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Cubs 81-73 *8*
Brewers 78-74 -2.0