About a year ago, I posted an article to Flotsam Media that introduced GRIT to the world of sabermetrics. GRIT had a nice night and said it was going to call the world of sabermetrics back in a few days, but it never did because it’s a good for nothing loser with a one-track mind. Flotsam is now defunct, so I’ve posted the article here for posterity’s sake. I also spent a few days in my laptop science lair working on an update. That’s what this post is about.

Just as a refresher, here’s the idea behind GRIT laid out in the original article.

Gritty players are those who are determined to win or succeed at baseball, but due to a lack of natural skill or talent, are forced to do so through the least efficient means possible. This inefficient play results in excessive dirt on their uniform.

If this hypothesis is true and dirt, determination and talent can be reasonably quantified, then it should follow that each of these three components can be plugged in to a formula to determine a given player’s grittiness (GRIT).

GRIT’s a bit of a work in progress, but I hope to continue to refine it and serve up lots of pseudo-statistics about your favorite baseball players–unless your favorite player happens to be Cesar Izturis. In that case, you’re welcome to leave.

CHANGE LOG

There are three major changes since last year’s article.

1. The Acronym

Originally, GRIT was comprised of some simple criteria that gritty players seemed to have in common. Thus, it made sense way back then that the acronym stood for ÒGeneral Requirements of Intangible TalentÓ, but not anymore. ÒGeneral Rating of Intangible TalentÓ is probably the most logical name, so I’m going with that. Sweet!

2. The Dirt Formula

I capitulated to public opinion and overhauled the Dirt component pretty substantially. Dirt changed from:

DIRT = HBP – IBB + ((CS +1)*CS))/(SB + CS + 1))

to

DIRT = HBP – IBB – (HR/2) + ((SB*-.3)+(CS*.6))

What’s the rationale for the addition of (HR/2)? You can pick one or both of two explanations.

• Home runs are a way of avoiding dirt since you get to trot around the bases like a pony. Ponies aren’t gritty. Burros? Gritty. Ponies? Not gritty.
• Because Don Baylor was ranked really high in last year’s rankings. I’m not dumb enough to call Don Baylor a pony. That said, he wasn’t gritty.

And the stolen base stuff? Well, the new statistic is a fairly rough estimate for the number of runs that a player costs his team with his (lack of) base-stealing ability. This link explains the logic behind valuating stolen bases. I didn’t feel like manually pulling the data for each individual year from BP’s website, so I used some unscientific estimates.

3. Normalization Methodology

Another change is the way the component values are normalized. I’ve switched to using averages and standard deviations grouped by year. This has the benefit of keeping the GRIT score of a given player-season consistent because it’s only dependent upon other players’ component scores from the same year.

As an example, under the old methodology, Hank Aaron’s TALENT score from 1965 could change if Ryan Howard put up an extremely high TALENT score in 2008. While the effect would be negligible, the new method ensures consistency from year to year. This modification resulted in slight changes to the GRIT scores for all player-seasons and, consequently, there has been a slight reordering of the all-time GRIT leaders.