Once again, I failed to keep up with monthly updates to my catcher defense rankings, although I did get a couple of installments done during the season. The Gold Glove awards are coming out later tonight, so let's see if they get it "right." (ahem)

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So I guess my plan to do monthly updates of the Catcher Defense Ratings is becoming something closer to bimonthly (a tribute to Bi-Mon-Sci-Fi-Con, uh, yeah). As always, take these with a grain of salt. I do think they do reflect something objective, way of "analyzing" events into defensive contributions (not to mention true talent) has acknowledged limitations. Nonetheless, I do think they reflect actual contributions of catchers in the field adequately to be worth doing.

There's a bit of an added "bonus" in this month's post. In response to questions from some of the nerdier of past comments, I've appended a shortened version of the methodological issues from when I originally did this rankings at the end of the post after the big table. They aren't much, but they give some reasons for doing it the way I've done it. If you're curious, they're worth reading if you have questions along those lines.

First, let's take a look at some of the overall leaders and trailers.

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And now... the moment you've all been waiting for...   the first installment of the Beyond the Box Score Catcher defense ratings of the 2011 season! What, you haven't been waiting for them? What, you aren't interested a catcher defense metric that doesn't  give extra credit for a guy hitting like a pitcher or interrupting a generic interview to defend a helpless youngster? Well, too bad.

These rankings are expressed in runs above and below average based on comparing each players fielding errors (FERns), throwing errors (TERns), passed balls and wild pitches (PBWPRns), and of course, caught stealing (CSRuns), and converting them to their linear weight values. For more specifics on the methodology, click here. As I've written before, I don't make any great claims to originality with this, other people have done it before in similar ways, I've simply added my own tweaks. However, I was encouraged to do them again this season, and will try to update them  monthly. Keep in mind that this is over a short sample (we have to start sometime!), that I don't claim that this is anything like great or comprehensive (it is quick and dirty), and, of course, that there is a difference between observed performance and "true talent," particularly over a small sample size. Without any further ado, let's take a look at some leaders and trailers.

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I hate Earned Run Average. I doesn't add anything truly useful over Runs Allowed, unless you think that errors are a Really Good Stat. I mean, I guess they're better than Pitcher Wins or something, but... I don't even have the energy to get into it right now.  I'm not even talking about ERA vs. FIP, or DIPS or tRA or SIERA or anything like that. I just mean the "E" part of it. There are many, many good posts on why the "earned" rules is silly, for example this one by Jack Moore or this classic by Michael Wolverton, and I'm not going to get into it, here. Moreover, if you're, say, calculating pitcher WAR, for example, the ERA scale (with whatever statistics) will undervalue pitchers when compared to position players since you aren't comparing it to a "real" runs scale, the runs-to-win conversion is thrown off, and so forth. Sigh. However, I grant that it is still the most common pitching statistic, and most of the newer pitching stats are scaled to it (not because the creators "believe" in ERA, but because they understandably want to use a scale people are familiar with). But until That Great Day comes when ERA is banished and we're all on an RA scale, having a quick "scale" to convert from one to the other might be helpful.

That's right, it's time for another thrilling Baseball Databank Data Dump.

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I tried to start this baseball-databank data dump series for myself last season, but it didn't take. I'm hoping to have better luck this season with shorter, and, uh, "dumpier" posts. So, for your breathless perusal (drum roll please)... historical runs-per-win conversions!

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A rare photo of Tom Tango, seen here calculating linear weights.

You know what wOBA is, right? If not, get hip to it. In short, wOBA (weighted On-Base Average) was created by Tom Tango as a way of more accurately expressing a player's offensive value (according to the linear weights of offensive events) than more traditional stats like batting average, on-base percentage, OPS, or whatever. While those numbers have their uses, linear weights more accurately reflect what a player has contributed since it does a better job of noting the relative value of walks, singles, doubles, etc. than those stats. wOBA is simply linear weights expressed as a "rate stat" scaled on on-base percentage, so, for example (depending on the run environment) .320-.330 are usually around average, .300 is terrible, and .400 is awesome. 

While the "original recipe" uses some pretty standard and effective weights, since then Tango has published a script that "customizes" wOBA for seasonal run environments. This has been implemented at FanGraphs, for example. However, many people now prefer these "custom" versions, but the values aren't readily available. I'm no sabermetric or SQL wizard, but I do have the script that these things are based. Due to overwhelming demand from my massive fanbase (okay, a couple of people on Twitter), I've run the script and have the weights through this season. I take no great claim to have invented this method or the script, but below you will find the wOBA coefficients updated for each MLB season through 2010.

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