# Tag Archives: sabermetrics is dead

## The Soul of Sabermetrics

Graham MacAree tried to shock the SABR world with his screed “The Problem with Sabermetrics” but I’m not buying it. After wasting a few paragraphs pointing out that baseball analysts can’t conduct controlled experiments (gee whiz!), he drops a few thinly-veiled insults.

Data analysis methods are being misapplied and sold to readers as the next big thing.

Didn’t I just cover this?

Articles are being written for the sake of sharing irrelevant changes in irrelevant metrics.

That sounds familiar, too.

Certain personalities are so revered that their word is taken as gospel when fighting dogma was what brought them the respect they’re now given in the first place.

Maybe he’s just stealing my material. Anyway, MacAree at least has a way to fix the sorry state of sabermetrics.

Sabermetrics shouldn’t be so incomprehensible so as not to call up the smell of fresh mown grass in midsummer, or the crack of the ball off the bat, the blur of seams as an outfielder whips a throw in towards his cutoff man. Statistics shouldn’t be sterile and clean and shiny and soulless. They shouldn’t just be about baseball; they should invoke it. Otherwise, they run the risk of losing the language which makes them so special.

I’m happy someone has finally made this point. What I love most about good sabermetrics is that when I look at

$tRA=27*\frac{K*-.105+BB*.329+HBP*.345+LD*.384+GB*.053*OFB*.046-IFB*.096+HR*1.394}{K+LD*.305+GB*.812+OFB*.830+IFB*.985}$

I see a hit-and-run executed to perfection; I smell the hot dogs and popcorn, chewing tobacco and sweat; I hear the umpire calling “Steeee-rike three!” That’s what makes tRA maybe not the best ERA estimator, but my favorite ERA estimator. And that’s what sabermetrics is all about.