Dee-Fense . . . Dee-Fense . . .

Last year, Justin Inaz popularized a new fielding stat, based on the freely available data from the Hardball Times. This year I decided to set up a spreadsheet (one that can automatically update!) and keep track of fielding performance, using Justin’s process. While there are plenty of advanced fielding metrics out there, such as MGL’s Ultimate Zone Rating, David Pinto’s Probabilistic Model of Range, and viagra John Dewan’s Plus/Minus, I figured, if anything, it wouldn’t hurt to have one more. It may not get as detailed as those listed above, but it’s pretty good and it’s available all the time (and for free).

The Methodology

The Hardball Times provides us with some great information to evaluate fielding performance. On their fielding stats page, they report, for each and every player, the number of balls hit into the player’s zone, the number of plays made on balls in their zone, and the number of plays made on balls hit outside of their zone. With these three numbers in hand, we can get a pretty solid grasp of a player’s fielding performance. But, before we get to that, we’ve got a few definitions to get out of the way:

BIZ (balls in zone) This is the number of balls hit into a player’s zone. A zone (or zones) is defined as the area on the field where at least 50% of balls are turned into outs, at the position in question.

Plays This category is simply plays made on balls in zone.

OOZ (out of zone plays) This is the number of plays a fielder makes on balls hit outside of his zone.

Now, how do we go about turning three numbers into a decent fielding metric? Well, let’s take a look at Mariners’ shortstop Yuniesky Betancourt, as an example. He’s had 244 balls hit into his zone, and of those 244 chances, he’s turned 200 of them into outs. The average shortstop turns about 83% of balls in zone into outs, so we would expect the average SS to make about 203 plays, if they had 244 chances. Betancourt is about -3 compared to average.

How do we handle out of zone performance? Betancourt’s made just 17 out of zone plays so far in 2008. The average shortstop makes about .13 out of zone plays per in zone chance*, so we’d expect the average SS to have about 32 out of zone plays, given Yuni’s in zone chances. This puts Betancourt at -15 on OOZ balls and about -18 plays overall.


*One major assumption is being taken here. That is that the number of in zone chances a player gets also reflects the number of out of zone chances he’ll have. Since we don’t know exactly how many OOZ chances anyone actually has, we have to estimate this number somehow. Some people believe innings or total balls in play or something else would be a better proxy, but I’m using in zone chances here.

We now have Betancourt at -18 plays, but we’re not quite done yet. It’s a lot easier to work in terms of runs because that’s generally how we measure things in baseball, so we have to make one final conversion. Using the numbers derived from Chris Dial, we can turn plays into runs, simply by multiplying plays by .753 for shortstops (it varies by position as saving a play in, say, the outfield, is, on average, more valuable than saving a play in the infield). Betancourt now ends up at about -13 runs, or the second-worst MLB shortstop, ahead of only Bobby pro cialis Crosby (-14.6).

That is essentially what you do, with every player, at every position (of course, Excel makes that a little bit easier, or at least it’s supposed to, if you know what you’re doing).

Carrom ball

The Good and the Bad

There are a number of reasons why this metric (stat, translation, conversion, whatever you want to call it) is pretty darn good, and there are also, of course, many limitations.

Positives:


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