Baseball stats: making a boring sport even worse

As I mentioned in my first post, I am not a big baseball fan.  I read Moneyball a few years ago, and I really enjoyed the book.  The main idea was to use basic statistics to measure the performance of a baseball player.  Since the A's were the (one of the) first team to do this, they could rely on simple measures that were easily interpretable (which spellchecker is telling me is not a word, but I don't believe it).  For example, someone decided that getting on base by being walked is just as important as hitting a single.  So they developed OBP, which is essentially the percent of times a batter gets on base (hits + walks)*.  Of all of the baseball stats out there, OBP may be my favorite.  Why?

Simple + Easy to Understand/Interpret = Great Statistic

But now that every club in MLB hires statisticians (or quantitative analysts or whatever they are called), the margin of profit from using these simple statistics has dried up.  So now these guys are making more complicated statistics and models while losing interpretability.  Look at this list of baseball statistics.  Extrapolated runs?  Base runs? Gross Production Average? No thanks. Plus imagine all of the secret formulas that MLB clubs are using to assess talent.  (On a side note, some of the top brass must be ignoring their statisticians and economists with the number of $200+ million contracts handed out this winter.)

Now let me get off my soapbox and stop hating on baseball for a while.  In my future posts, when I perform statistical analyses, I promise that they will be simple and easy to interpret.  Most will be related to problems that I presented as in-class examples when I taught an Introduction to Statistics course to undergrads. 

* Its not quite this simple (nothing ever is), but you get the point.