Catcher Spotting is a project I've been working on casually for about 4 years, starting when I got curious about the last uncaptured bit of data from a baseball game: the set-up of the catcher, implying the intended target of each pitch before it's thrown by the pitcher. Every commentator knows that when a pitcher is "missing his spots", it's evidence of a loss of control, but attempts to measure the impact of this loss are utterly stymied by the lack of quality data out there.
That's where the Catcher Spotting project comes in: I am very interested in figuring out exactly how this data can be collected on a wide scale. While commentators can be in agreement about whether a pitcher has missed his spot, codifying this hasn't been established yet. And I'm far from convinced that technology can do it alone through video analysis, especially in cases of "intentional deception" like when a runner is on second. Crowdsourcing seems to be the obvious solution -- how well can you distribute the task to many different coders?
To that end, I've built an applet that tries to answer that question: users simply click their mouse to indicate where the catcher has set up, and where the ball actually goes. By collecting data from (hopefully) many users, we should know how many different human coders would be needed to get a reliable sense of a pitcher's intent, as signalled through a catcher. The idea is the same as sites like Hot Or Not, except that I'm explicitly concerned with how the same rater will judge different pitches, so that we can know how trustworthy a single rater could be.
Please give the applet a try!
That's where the Catcher Spotting project comes in: I am very interested in figuring out exactly how this data can be collected on a wide scale. While commentators can be in agreement about whether a pitcher has missed his spot, codifying this hasn't been established yet. And I'm far from convinced that technology can do it alone through video analysis, especially in cases of "intentional deception" like when a runner is on second. Crowdsourcing seems to be the obvious solution -- how well can you distribute the task to many different coders?
To that end, I've built an applet that tries to answer that question: users simply click their mouse to indicate where the catcher has set up, and where the ball actually goes. By collecting data from (hopefully) many users, we should know how many different human coders would be needed to get a reliable sense of a pitcher's intent, as signalled through a catcher. The idea is the same as sites like Hot Or Not, except that I'm explicitly concerned with how the same rater will judge different pitches, so that we can know how trustworthy a single rater could be.
Please give the applet a try!