College Baseball, In Nerd Terms

One of my favorite tools when evaluating players is Equivalent Average (EqA). First of all, it enables us to compare apples (traditional sluggers) and oranges (high batting average/base stealers), along with the occasional kumquat (high OBP guys). Secondly, it makes the comparisons in the language of batting average, perhaps the statistic most ingrained in the American consciousness. This makes EqA easy to appreciate (more so, at least, than something like WARP-3). Finally, it provides easy opportunities for the person calculating the stat (in this case, me) to adjust for things like park effects. As anyone who has ever seen the cavernous Zephyr Field knows, this can be important.

Basically, EqA takes the traditional statistics we know and love -- batting average, slugging percentage, and on-base percentage -- and rolls them together, tacking on things like sacrifices and stolen bases. To measure EqA, we take the player's offensive production, and using the number of outs made by the player as a rate statistic, we get an accurate measure of the player's run production in game (were he to bat in all nine slots). EqA takes that measure, balances it against league performances, and divides by a constant. Sounds complicated, but the whole idea is to make Joe Average's production equal to .260.

Think of it on the same terms as batting average -- a guy who hits .230 is a terrible baseball player; a guy who hits .300 is a really good one. Albert Pujols, for example, clocks in around .335 for his career. Neifi Perez? Not so much.

We'll probably play with a few other statistics as we go along, but this should lay the groundwork for EqA. Later today (or perhaps tomorrow), we'll do a rundown of Tulane's current team.