Although the season has recently come to a close, there's still a lot of good stuff going on in the baseball blogosphere. One of my favorite annual occurrences is the release of the results from various PBP fielding systems.
David Pinto recently shared the first installment of his Probabilistic Model of Range (PMR) ratings examining the overall performance of teams. I'm not going to delve too deeply into an explanation of David's method (he describes it here), but essentially he uses a variety of batted ball data to determine how hard it was to field a given ball in play. From that information, he calculates how many plays should have been completed for each player or team. Once he has the expected number of outs, he can compare that to the actual number of outs and determine a ranking based on the ratio of actual to expected.
The results are extremely interesting, but their overall impact can be hard to grasp. To better illustrate what PMR means, the intrepid Angels blogger LA Waterloo of Black Hawk (who I'll refer to as LAWoBH going forward) figured out how to convert the PMR results into runs above average. His methodology was to leverage some work by Chris Dial that identifies the run value of turning a ball in play from a hit to an out. Multiplying the number of plays made above or below expectations by the run value transforms the metric into runs above or below expectation. From there, LAWoBH calculated the average runs above expectation and used that as the baseline for a runs above average calculation. Indvidual results from 2004-2006 can be found in the right hand link column of his blog, while 2007 can be found in these archives.
Rather than looking at individual players, I decided to run the same analysis at the team level to see if we can glean anything from the outcome.
|Team||In Play||Actual Outs||Predicted Outs||Outs Delta||Runs Delta||Runs / 4000||RAA / 4000
Feel free to ignore the faux level of precision implied by the decimals and focus on the broad strokes. In case you're curious, we have a different run value for each league based on the numbers found in Chris Dial's post: .9425 for the AL and .9138 for the NL. I've made the extreme assumption that all teams in a league faced the same spread of difficulty on balls in play. In other words, all teams saw the same distribution of balls to each position and the same distribution of possible outcomes if the plays weren't made (the same number of singles and doubles on ground balls to 3B, for example). This is clearly not true in theory, and likely not close enough to even out of the course of one season in practice, but it's the best I could do.
Unsurprisingly, the teams at the top of this list tended to have lower ERAs. A team like the Rays, which was much lauded for its pitching and defense, could credit 3 wins to their defensive prowess. The AL East was a division of fielding extremes in 2008. Three teams, the Blue Jays, Rays and Red Sox, finished in the top 5, at over 25 runs better than the average team, while the Orioles and Yankees lagged behind the field by about the same amount. The fielding difference between the Yankees and the Red Sox was roughly 5 wins, or enough to close the gap to a single game.
It's becoming rather cliche to disparage the Yankees defense, but it truly was horrible last season. Fielding played a big part in turning missing the playoffs into a fait accompli by mid September, and despite losing Abreu and Giambi, things don't look to improve too much. According to Chone Smith's (also known as Anaheim Rally of Monkey) 2009 fielding projections, the current Yankee fielders are estimated to be around -20 runs overall (depending on how the outfield is configured). The big drag on the numbers is obviously Jeter at -13, which the Yankees will need to address at some point (hopefully sooner rather than later).
But this is not intended to be a treatise on the Yankees. Many other teams at the bottom of the rankings could use the help. And there are strong defensive players available this offseason. One of the best, Mark Ellis was already locked up by Oakland, but the otherworldly Adam Everett and the generally very good Orlando Hudson are both free agents who potentially could be worth a win or two with the glove (whether Everett gives that back with his bat is an open question however).
The PMR ratings for individual players have also begun appearing. Check back to this post, which I'll update to include both the raw PMR rankings as well as LAWoBH's translated runs above average results once they're available.
1B: PMR / RAA
2B: PMR / RAA
3B: PMR / RAA
SS: PMR / RAA
LF: PMR / RAA
CF: PMR / RAA
RF: PMR / RAA