While fielding analysis has come a long way, pretty much everyone agrees that we still have a long way to go. Catcher defense is in many ways further behind other sorts of analysis (although on the most advanced level I think that gap is exaggerated).

There are several emerging sophisticated ways of evaluating a catcher’s defensive contribution. This is not one of them.

What follows is the output of a simple “system” (that is far from original) that I can put together relatively quickly in-season to keep track of how catchers seem to be doing relative to the rest of the league with respect to throwing out base stealers, blocking pitches, and making errors. Yes, it’s early in the season, but we have to start at some point.

In past postings of these ratings at Beyond the Box Score, I have gone through all the the reasons I do it this way, and qualified the samples, the data, and linked to more complex systems. I will simply refer you to those posts rather than regurgitating it all here. I have included a “reprint” of the methodological postscript that gives a basic explanation of how all this stuff is calculated. I will try to update these each month or so. Let’s get right to the commentary. And, one more time — remember that it is early, and that there is a difference between observed performance and true talent.

Pitch Blocking (Passed Balls and Wild Pitches) Leaders and Trailers:

During the off-season, the Padres rewarded Nick Hundley’s .354 wOBA with a nice contract extension. He has thanked them so far in 2012 with a .272 wOBA, which isn’t even good for a catcher in Petco. Still, he’s playing good defense.

Hundley is tied with Matt Wieters, whom I had as the best defensive catcher in baseball in 2011, as the best pitch blocker in the league. Wieters is off to a hot start with the bat this season, but even if he slides back into the .330-.340 wOBA range, his defense at a tough position still makes him a near superstar-level player, so let’s chill with the disappointment, okay? One of my favorite players, former Royals and Blue Jays catcher, now with the Miami Marlins, John Buck rounds out the top three.

I am really disappointed that another former Royal, Miguel Olivo, is not at his usual position at the bottom of these rankings, and with his injury, I’m not sure he will ever get there this season. Jason Castro is doing his part, though, and is “followed” by Wilin Rosario of Colorado (good thing they got rid of defensive hack Chris Iannetta, amrite?). Former Jay Jose Molina is third-worst so far, is he being “Framed” (har har)? [Editorial Note: Matt Klassen is on fire, everyone. - D.P.]

Caught Stealing Leaders and Trailers:

This is the Big Thing we usually associate with defensive catchers. The leader is Miguel Montero at 2.4 runs. I used to think of Montero as a below-average defensive catcher, but I assume that is the usual bias against a catcher who can hit (although Joe “Hometown Discount” Mauer seems to be un-mysteriously exempt).

Tyler Flowers, who did not have a good defensive reputation as a prospect, is anomalously tied with Montero. After that, it’s Kurt Suzuki, an underrated catcher not done any favors by playing for Oakland. Well, he used to be underrated. If he can’t get over a .300 wOBA, he may just be another catcher.

Rounding out the bottom of the list of “gunners,” we have poor ol’ Jason Castro again, for whom I almost feel pity. Do the Astros have a knuckleballer I haven’t heard about? Wilson Ramos is second-worst so far, but he was good last season, so it is too early to get worried. Third from last we have Humberto Quintero who was actually pretty good in 2011 and 2010, so this is probably an effect of sample size so far.

Overall Catcher Leaders and Trailers:

Nick Hundley is the overall leader in these rankings so far at just over three runs saved. He did not rate as a defensive wizard in either 2011 and 2010, but he has been above average. Coming in at #2 is Chicago White Sox backup Tyler Flowers, which just shows how weird things can be this early in the season. Carlos Ruiz and Miguel Montero come in at a very close third and fourth — Montero is really an underrated overall player, in my opinion.

At the very bottom we have the previously mentioned Jason Castro at almost 5 runs below average already. Hey, at least he hits. Oh, Astros. Either Mike Fast has some metrics showing Castro is a lot better than this, or they’re just stuck with a terrible player back there as they rebuild. Geovany Soto comes in second-worst — remember when he was a budding star? Now he isn’t hitting, either. Third to last is the Royals’ Humberto Quintero, a “catch-and-throw” guy who was, you guessed it, was brought in for his defense after Salvador Perez went down. Quintero is, somewhat humorously, actually hitting decently this season. Yeah, that will last.

There is undoubtedly much else to find and complain about, so without any further ado, here are the ratings (a short bit on methodology comes after that — please read that before making the inevitable complaints):

Rank Tm PA FERuns TERuns PBWPRuns CSRuns Total
1 Nick Hundley SDP 785 0.3 0.1 1.6 1.3 3.3
2 Tyler Flowers CHW 171 0.1 0.2 0.5 2.4 3.1
3 Carlos Ruiz PHI 715 0.2 0.8 1.1 0.6 2.8
4 Miguel Montero ARI 772 0.3 -0.6 0.7 2.4 2.7
5 Ryan Hanigan CIN 522 0.2 -0.2 1.2 1.0 2.1
6 Kurt Suzuki OAK 839 0.3 0.2 0.1 1.4 2.0
7 A.J. Ellis LAD 737 0.2 0.1 0.6 1.0 1.9
8 Yorvit Torrealba TEX 473 0.2 0.5 0.2 0.8 1.7
9 Yadier Molina STL 750 0.2 0.1 0.7 0.6 1.6
10 Anthony Recker OAK 139 0.0 0.2 0.4 0.8 1.4
11 Ramon Hernandez COL 606 0.2 0.7 0.3 0.2 1.3
12 Jonathan Lucroy MIL 699 0.2 0.0 0.3 0.8 1.3
13 Gerald Laird DET 225 0.1 0.2 0.3 0.5 1.1
14 Chris Snyder HOU 361 0.1 0.4 -0.4 0.8 0.9
15 Matt Wieters BAL 789 0.3 -1.4 1.6 0.3 0.8
16 Chris Stewart NYY 166 0.1 0.2 0.5 0.0 0.7
17 David Ross ATL 176 0.1 0.2 -0.1 0.5 0.7
18 Jesus Flores WSN 241 0.1 0.3 -0.7 0.9 0.6
19 J.P. Arencibia TOR 743 0.2 -0.7 -0.2 1.1 0.5
20 Tony Cruz STL 100 0.0 0.1 0.3 0.0 0.4
21 Brayan Pena KCR 429 0.1 -0.3 0.1 0.5 0.4
22 Jeff Mathis TOR 220 0.1 0.2 0.3 -0.3 0.3
23 Chris Iannetta LAA 679 0.2 0.8 -0.1 -0.6 0.3
24 Brian Schneider PHI 205 0.1 0.2 0.3 -0.3 0.3
25 Michael McKenry PIT 285 0.1 0.3 -0.0 -0.2 0.2
26 John Buck MIA 684 0.2 0.0 1.3 -1.4 0.2
27 Welington Castillo CHC 67 0.0 0.1 0.2 -0.2 0.1
28 Brett Hayes MIA 222 -0.7 -0.5 0.3 0.9 0.1
29 Ronny Paulino BAL 146 0.0 0.2 0.1 -0.3 0.0
30 Carlos Santana CLE 723 0.2 0.1 -1.1 0.8 0.0
31 Ryan Doumit MIN 449 0.1 -0.3 0.7 -0.6 -0.0
32 Brian McCann ATL 777 -0.5 0.9 0.2 -0.6 -0.1
33 John Baker SDP 187 0.1 0.2 -0.0 -0.3 -0.1
34 George Kottaras MIL 274 0.1 0.3 -0.1 -0.5 -0.2
35 A.J. Pierzynski CHW 720 0.2 0.0 -1.1 0.6 -0.2
36 Henry Blanco ARI 169 0.1 0.2 -0.4 -0.2 -0.3
37 Bobby Wilson LAA 222 0.1 -0.5 0.1 0.0 -0.4
38 Miguel Olivo SEA 703 -0.5 -0.7 -0.3 1.1 -0.4
39 Jose Lobaton TBR 93 0.0 -0.6 -0.0 0.2 -0.5
40 Wilin Rosario COL 343 0.1 0.4 -1.6 0.5 -0.6
41 Steve Clevenger CHC 175 0.1 0.2 -0.1 -0.8 -0.6
42 Chris Gimenez TBR 303 -1.4 0.3 0.3 0.2 -0.6
43 Rod Barajas PIT 593 0.2 -0.1 0.5 -1.3 -0.6
44 Devin Mesoraco CIN 370 0.1 0.4 0.2 -1.4 -0.7
45 Kelly Shoppach BOS 334 0.1 0.4 -0.8 -0.5 -0.7
46 Mike Nickeas NYM 215 0.1 -0.5 -0.5 0.2 -0.8
47 Jesus Montero SEA 267 0.1 0.3 -0.9 -0.3 -0.9
48 Russell Martin NYY 763 0.2 0.8 -1.5 -0.5 -0.9
49 Hector Sanchez SFG 353 0.1 -0.4 -1.0 0.3 -0.9
50 Mike Napoli TEX 438 -0.6 0.5 -0.2 -0.6 -0.9
51 Lou Marson CLE 162 0.1 0.2 -0.4 -0.8 -0.9
52 Buster Posey SFG 552 -0.6 -0.9 0.7 -0.3 -1.1
53 Joe Mauer MIN 446 0.1 -0.3 0.4 -1.4 -1.1
54 Matt Treanor LAD 192 0.1 -0.5 -0.0 -0.6 -1.1
55 Wilson Ramos WSN 658 -0.5 0.7 0.1 -1.7 -1.4
56 Jose Molina TBR 553 0.2 -0.1 -1.5 0.0 -1.5
57 Josh Thole NYM 750 -2.0 0.1 0.7 -0.3 -1.5
58 Alex Avila DET 719 0.2 -0.7 -1.1 -0.1 -1.7
59 Jarrod Saltalamacchia BOS 613 0.2 -0.1 -0.8 -1.1 -1.8
60 Humberto Quintero KCR 460 0.1 -0.2 -0.7 -1.6 -2.3
61 Geovany Soto CHC 659 -0.5 -1.5 0.7 -1.6 -2.9
62 Jason Castro HOU 575 0.2 -0.9 -2.0 -2.2 -4.9

Concluding Methodological Postscript 

I should make clear that for the purposes that I am not including such debated areas a pitch framing or the more amorphous “game calling.” I am not taking a position one way or the other on either of those, simply making clear the bounds of these rankings.  When I discuss “catcher defense,” like most others, I will be discussing preventing stolen bases, blocking pitches, etc.

One of the difficulties with evaluating catcher defense with regard to even these issues is that, much more than with other fielding positions, the catcher’s performance is dependent on another player — namely, the pitcher. No matter now strong or weak the catcher’s arm is, he can’t escape the reality that he depends on the pitcher’s skill with regard to holding runners, quickness to the plate, etc. While the catcher’s skill with regard to blocking pitches that are off the mark is clearly important, catching Tim Wakefield poses a unique challenge — just ask Josh Bard. And so on.

For these reasons, probably the best way of measuring catcher defense is Tom Tango’s WOWY (With or Without  You) method of defensive evaluation as detailed the 2008 Hardball Times Annual.  You can read about the details in the links provided. Versions of WOWY for catchers have also been done by Brian Cartwright and Dan Turkenkopf. I would do it that way if I could. The main issue is that 1) it’s pretty complicated, and beyond my present capabilities, and 2) it requires something like Retrosheet, which isn’t available until after the World Series is over, so even if I could do it, I couldn’t get the numbers during the season of even now…

While the method used here is neither terribly subtle nor original, I think when compared to things like the Fans’ Scouting Report and WOWY methods, it compares fairly well. Just keep in mind the acknowledged limits (e.g., not taking into account the pitchers’ contributions like WOWY does).

The Method Used Here

For non-WOWY catcher defense, the basic idea is to 1) choose what events you’re going to deal with, 2) determine each catchers performance with respect to league average, and 3) decide the run value of each event.

Stolen Bases/Caught Stealing (CSRuns): First, we figure out the league rate for caught stealing. One cool thing about the new Baseball Reference is that it separates out the catcher caught stealings from the pitcher pickoffs, so we can exclude the pickoffs (not under the catcher’s control) from the equation. So we total the CSctch +SB to get total stolen base attempts (SBA) and then to total CSctch/total SBA for the lgCS rate. We use the weight of .63 runs for each caught stealing, which represents the average linear weight of the caught stealing (.44 runs) plus the weight of the stolen base not achieved (.19 runs). The formula for runs above/below average for each catcher is thus (CS – (lgCSrate) * SBA) * 0.63.

Wild pitches/passed balls (WPPBRuns): The league rate is (WPlg + PBlg)/lgPA. The linear weight for each passed ball/wild pitch is 0.28 runs, which we make negative since the more WP/PBs a catcher has, the worse his defense is. The formula for each player is ((WP + PB) – (lgWPPBrate * PA)) * -0.28.

Errors (FcE and TE Runs): I deal with three different kinds of catcher error recorded by Baseball Reference: throwing errors, catching errors, and fielding errors. I’ve assimilated catching errors to fielding errors. There are separate linear weights for throwing (including catching) errors (-0.48) and fielding errors (-0.75). The method is the same as above. Get the league rate, then see how far over/under the player is. For throwing errors: (TE – (lgTErate * PA)) * -0.48. Fielding errors: (FE – (lgFErate * PA)) * -0.75.

Then you just add them all up to get the total runs above/below average. It’s not perfect, and hopefully, there will be some improved options soon, but the results do seem to reflect reality. I round to one decimal: I aware that gives an illusion of precision that isn’t there, I simply do it to expedite sorting and ranking.  I thought about coming up with a “rate” version like UZR/150, but that isn’t as simple as prorating for innings caught/PA — one needs to normalize each sort of event separately, the chart is confusing enough as it is. For now, this is just a value measurement of what each player did this season.

Comments (2)

  1. Good to see that JPA isn’t riding the bottom of the list, very encouraging considering that framing report that came out awhile ago that really trashed him.

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