Home Runs heating up?

November 12, 2011
By

(This article was first published on datum » R, and kindly contributed to R-bloggers)

My intuition tells me that objects traveling through the air would meet more resistance when there is more moisture in the air. It turns out that my intuition is wrong. It still doesn’t make sense to me but apparently humid air is less dense. And this applies to baseball specifically because the belief is that there are more home runs in the latter half of the season because many parks are in humid areas (east coast bias) and as the summer progresses it gets hotter and hotter and more and more humid. A lot of this is purely anecdotal: “The ball’s really going to start flying out of the park as the weather heats up” and other such nonsense from the mouths of the talking heads we’re forced to listen to while watching a game.

Anyway, after seeing this post at Revolution Analytics I wanted to use the calendar heat map function created by Paul Bleicher.  (source code is available here) And it seemed like a really fitting opportunity to look at how cumulative daily home runs fluctuated over the course of the MLB season. Based on the science behind the humidity factor you would imagine that there would be a, somewhat, obvious increasing trend at least until it starts to cool off at the end of September. Here is how that data looks in one of these calendar heat maps.

From this perspective I’m seeing home run heavy days sprinkled all over the course of the season. The only conclusion that I can come to is that 1) obviously the science is right but the sample size is too small on a daily basis not to be skewed by one big game and 2) the announcers that perpetuate these myths are just parroting each other with no actual check on what comes out of their pie-holes.


To leave a comment for the author, please follow the link and comment on his blog: datum » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Tags: , , ,

Comments are closed.