The more I use it, the more I understand the benefits and value of Github as a code-sharing resource. The gist found here is the R code for my posts on run scoring trends by league (found here, here, and here). I will continue to use Github for t...

The more I use it, the more I understand the benefits and value of Github as a code-sharing resource. The gist found here is the R code for my posts on run scoring trends by league (found here, here, and here). I will continue to use Github for t...

Or, The 2010 Mariners: How Bad Were They?In earlier posts, I used the statistical software R to plot the trends in league average run scoring since 1901. This was the first step to answering other questions I had on my mind:How poor was the offensive performance of the 2010 Seattle Mariners?Are they showing any signs...

My previous two posts have looked a using R to create trend lines for the run scoring environments in the American and National leagues. This time around, I'll plot the two against each other to allow for some comparisons. (The code below assumes that you've read the data into your workspace and calculated the LOESS...

Last time around I used R to plot the average runs per game for the American League, starting in 1901. Now I’ll do the same for the National League. I'll save a comparison of the two leagues for my next post.A fundamental principal of programming is that code can be repurposed for different sets of datas. So...

I have started to explore the functionality of R, the statistical and graphics programming language. And with what better data to play than that of Major League Baseball?There have already been some good examples of using R to analyze baseball data. The most comprehensive is the on-going series at The Prince of Slides (Brian Mills, aka...