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2011 Beyond the Box Score Catcher Defense Ratings: Year-End Edition

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)

I often go through a number of qualifications at this point, but you can read past installments for that stuff. I wondered if I should even bother keep doing this, given the great stuff that has come out lately on stuff that is covered here like Bojan Koprivica's work on pitch blocking and other stuff like Mike Fast's revolutionary work on pitch framing. BtBS' own Michael Schatz has some cool stuff coming out, too. Along with WOWY approaches (discussed in the methodological stuff at the end), this is the future of catcher defense evaluation. However, there are virtues to a more simple approach. I originally began doing this for my own sake, to have something that can easily be copied, pasted, and "manipulated" for my own tastes the Baseball-Reference basic fielding tables. My own quick perusal seems to show basics agreement with more complex approaches, which, along with the Fans Scouting Report, I encourage you to check out. I will not pursue those comparisons here. I may use a different approach in future seasons, or just leave this stuff to others. For now, I'll just make some comments on a few of the leaders and trailers. Brief methodological comments and summaries can be found after the table.

 

One more thing: please remember to keep the distinction between "observed performance" and "true talent" in mind before getting to worked up about a particular rating.

 

The overall leader is the same guy who has been running away with it all season, Matt Wieters, who dominated these leader boards like he was supposed to dominate major-league pitching immediately upon his promotion in 2009. He is not just the overall leader, but also the best at blocking pitches and catching base stealers according to these rankings. His offense may not ever reach expectations, but by itself it was good enough relative to his position without good defense. With his defense, he probably had a better than five-win season. Maybe it is not the way Orioles fans envisioned, but Wieters has become a star, even if it is mostly going unnoticed.

There are some other notable players near the top of the ratings. Some of the usual suspects come in as above average, like Yadier Molina (#8) and Carlos Ruiz (#5). However, the players who rank immediately below Wieters are a bit surprising. Miguel Montero (#2) is not a catcher with much of a defensive reputation, but his good fielding and strong bat adds up to an underrated piece of the Diamondbacks' surprising run to the playoffs. Lou Marson has an absolutely dreadful bat, but his glove makes him quite playable, especially has a backup. Kelly Shoppach (#4) used to be known as an offense-first, right-handed platoon catcher, but in a season when hit bat fell apart, he thrived on defense. Speaking of catchers with a reputation for bad defensive and platoon offense, how about thatMike Napoli (#12)? I will be generous and not name the person who told me, at the time of the trade, that Mike Scioscia was "right about Napoli."

Among those at the bottom we have the Mr. Hockey Jersey "C," Jason Varitek (#109) and part of Milwaukee's SuperGlove combo, Jonathan Lucroy (#110). A.J. Pierzynski (#111) might be better served to stick with commentary. Well, better serving his team, not his listeners. Jarrod Saltalamacchia (#112) restored his credibility on offense, but his defensive numbers aren't so hot. However, his =passed ball and wild pitch numbers have to be taken with a grain of salt given that he caught a knuckleballer. Speaking of passed balls and wild pitches, Miguel Olivo (#113) continued his reign of terror. Oh well, at least he gets on-base. Oh, wait. At the very bottom is another guy who was basically at the same rank all year, a Blue Jays rookie J.P. Arencibia. Arencibia hit a lot of home runs this season, but that was about all he did well. If he doesn't develop, he could be another Olivo. That has its uses, but with Travis D'Arnaud hitting in the minors, Arencibia's time to prove himself in Toronto may be running short.

 

2011 Beyond the Box Score Catcher Defense Rankings
Rank Player Age Tm PA FERns ThERuns PBWPRns CSRns Total
1 Matt Wieters 25 BAL 4971 -0.9 2.2 6.8 7.1 15.2
2 Miguel Montero 27 ARI 4903 0.6 -1.7 3.3 5.7 7.8
3 Lou Marson 25 CLE 2872 0.8 -0.6 2.3 4.7 7.2
4 Kelly Shoppach 31 TBR 2601 0.0 0.7 2.6 3.5 6.8
5 Carlos Ruiz 32 PHI 4327 0.4 1.3 6.4 -2.4 5.7
6 Wilson Ramos 23 WSN 4038 1.1 0.1 1.7 2.3 5.2
7 Ramon Hernandez 35 CIN 2832 0.8 1.3 -0.1 3.1 5.1
8 Yadier Molina 28 STL 4896 1.3 0.7 2.4 0.6 5.1
9 Nick Hundley 27 SDP 2726 0.8 -1.2 1.6 3.4 4.6
10 Ryan Hanigan 30 CIN 2906 0.1 0.4 2.6 1.4 4.5
11 Chris Iannetta 28 COL 4033 0.4 2.1 -0.6 2.5 4.3
12 Mike Napoli 29 TEX 2052 0.6 0.3 1.6 1.8 4.3
13 Drew Butera 27 MIN 2954 0.8 -0.5 0.5 2.8 3.6
14 Henry Blanco 39 ARI 1199 0.3 0.3 0.6 2.0 3.2
15 Chris Stewart 29 SFG 1930 0.5 -2.1 1.0 3.8 3.2
16 Buster Posey 24 SFG 1506 -0.3 0.5 1.5 1.4 3.0
17 Ivan Rodriguez 39 WSN 1279 -1.9 0.8 -0.3 3.6 2.2
18 Rod Barajas 35 LAD 3085 0.1 1.5 2.3 -1.9 2.0
19 Josh Bard 33 SEA 849 0.2 -0.4 1.0 1.2 2.0
20 Craig Tatum 28 BAL 1100 -0.4 -0.3 1.7 1.0 2.0
21 Chris Gimenez 28 SEA 653 0.2 0.4 0.5 0.9 1.9
22 Taylor Teagarden 27 TEX 360 0.1 0.2 -0.1 1.6 1.8
23 Geovany Soto 28 CHC 4503 -0.3 -2.4 2.1 2.3 1.7
24 Brayan Pena 29 KCR 2325 0.6 0.5 0.2 0.3 1.6
25 Rene Rivera 27 MIN 1274 -0.4 -0.2 1.4 0.7 1.6
26 George Kottaras 28 MIL 1073 0.3 0.7 1.4 -1.1 1.2
27 Humberto Quintero 31 HOU 2829 -0.7 0.3 3.5 -2.1 1.1
28 Yorvit Torrealba 32 TEX 3510 -1.3 -0.7 1.0 2.1 1.1
29 Ryan Lavarnway 23 BOS 113 0.0 0.1 0.3 0.5 0.9
30 Luis Martinez 26 SDP 627 0.2 0.4 0.9 -0.6 0.9
31 Landon Powell 29 OAK 1130 -0.4 0.2 0.4 0.6 0.8
32 Jose Molina 36 TOR 1697 0.5 0.6 -2.7 2.4 0.7
33 Mike Rivera 34 MIL 51 0.0 0.0 0.1 0.5 0.7
34 Gustavo Molina 29 NYY 78 0.0 0.0 0.2 0.3 0.6
35 Dane Sardinha 32 PHI 448 0.1 0.3 -0.1 0.3 0.6
36 Bobby Wilson 28 LAA 1344 0.4 0.4 -0.4 0.3 0.6
37 David Ross 34 ATL 1575 -1.1 0.5 -0.6 1.7 0.5
38 Brian Schneider 34 PHI 1250 0.3 0.3 1.3 -1.4 0.5
39 John Buck 30 FLA 4863 1.3 0.7 3.1 -4.7 0.4
40 Eric Fryer 25 PIT 271 0.1 -0.3 0.2 0.4 0.4
41 Brett Hayes 27 FLA 1325 0.4 0.8 -0.4 -0.5 0.3
42 Jorge Posada 39 NYY 32 0.0 0.0 -0.2 0.5 0.3
43 J.C. Boscan 31 ATL 80 0.0 0.1 -0.1 0.2 0.2
44 Jose Lobaton 26 TBR 350 -0.7 0.2 0.7 0.0 0.2
45 Matt Pagnozzi 28 COL 284 0.1 0.2 -0.3 0.2 0.2
46 Chris Snyder 30 PIT 1113 0.3 0.7 -0.8 0.0 0.2
47 A.J. Ellis 30 LAD 930 0.3 0.6 -0.2 -0.6 0.1
48 Tim Federowicz 23 LAD 169 0.0 -0.4 -0.1 0.5 0.1
49 Donny Lucy 28 CHW 98 0.0 0.1 0.0 0.0 0.1
50 Jesus Montero 21 NYY 117 0.0 0.1 0.1 -0.1 0.1
51 Wyatt Toregas 28 PIT 43 0.0 0.0 -0.2 0.2 0.1
52 Matt Treanor 35 TEX 99 0.0 0.1 0.0 0.0 0.1
53 John Baker 30 FLA 12 0.0 0.0 0.0 0.0 0.0
54 Steve Clevenger 25 CHC 51 0.0 0.0 0.1 -0.1 0.0
55 Tony Cruz 24 STL 415 0.1 0.3 -1.1 0.7 0.0
56 Jesus Flores 26 WSN 824 0.2 0.0 0.1 -0.4 0.0
57 Martin Maldonado 24 MIL 9 0.0 0.0 0.0 0.0 0.0
58 Adam Moore 27 SEA 67 0.0 0.0 0.2 -0.3 0.0
59 Carlos Santana 25 CLE 3363 0.9 -1.2 1.1 -0.8 0.0
60 Wil Nieves 33 MIL 554 -0.6 0.3 0.2 0.0 -0.1
61 Don Kelly 31 DET 25 0.0 0.0 -0.2 0.0 -0.2
62 Jeff Mathis 28 LAA 2866 0.8 0.4 -0.3 -1.1 -0.2
63 Manny Pina 24 KCR 147 0.0 0.1 -0.7 0.3 -0.2
64 Omir Santos 30 DET 243 0.1 0.2 -0.2 -0.2 -0.2
65 Robinson Cancel 35 HOU 73 0.0 0.0 -0.1 -0.3 -0.3
66 Hector Gimenez 28 LAD 45 0.0 0.0 -0.2 -0.1 -0.3
67 Erik Kratz 31 PHI 44 0.0 0.0 -0.2 -0.1 -0.3
68 Kyle Phillips 27 SDP 725 -0.6 -0.5 0.4 0.4 -0.3
69 Austin Romine 22 NYY 214 -0.7 0.1 0.3 -0.1 -0.3
70 Jordan Pacheco 25 COL 44 0.0 0.0 -0.2 -0.3 -0.4
71 Robinson Chirinos 27 TBR 563 0.2 0.4 1.0 -2.1 -0.5
72 Steve Holm 31 MIN 198 0.1 0.1 0.0 -0.7 -0.5
73 Welington Castillo 24 CHC 159 -1.5 0.1 -0.1 0.8 -0.6
74 Joe Mauer 28 MIN 1784 -0.3 -0.3 -0.8 0.8 -0.6
75 Mike Nickeas 28 NYM 607 0.2 0.4 -0.8 -0.3 -0.6
76 Matt Pagnozzi 28 PIT 68 0.0 0.0 0.2 -0.9 -0.6
77 Tyler Flowers 25 CHW 1079 -0.5 0.2 0.3 -0.7 -0.7
78 Russell Martin 28 NYY 4435 1.2 -2.0 -3.1 3.2 -0.7
79 Ramon Castro 35 CHW 728 -0.5 0.5 0.7 -1.3 -0.8
80 Michael McKenry 26 PIT 2118 -0.9 -0.1 1.0 -0.8 -0.8
81 Hector Sanchez 21 SFG 285 0.1 0.2 -0.6 -0.5 -0.8
82 Wilin Rosario 22 COL 533 0.1 -0.1 -3.0 2.0 -1.0
83 Dusty Brown 29 PIT 341 0.1 0.2 -1.0 -0.4 -1.1
84 Jake Fox 28 BAL 261 0.1 0.2 -0.7 -0.7 -1.1
85 Victor Martinez 32 DET 974 -0.5 0.1 0.0 -0.8 -1.2
86 Anthony Recker 27 OAK 218 0.1 -0.3 -0.2 -0.7 -1.2
87 Jason Jaramillo 28 PIT 320 0.1 0.2 -1.3 -0.2 -1.3
88 Kurt Suzuki 27 OAK 4811 1.3 -0.3 0.8 -3.0 -1.3
89 Gerald Laird 31 STL 900 0.2 -0.9 0.0 -0.9 -1.5
90 Eliezer Alfonzo 32 COL 694 -1.3 -1.0 -0.6 1.0 -1.9
91 Devin Mesoraco 23 CIN 521 -1.4 -0.2 -0.5 -0.2 -2.2
92 Rob Johnson 27 SDP 1987 -0.2 0.8 -1.1 -1.8 -2.3
93 Josh Thole 24 NYM 3459 1.0 1.2 -1.4 -3.1 -2.3
94 J.R. Towles 27 HOU 1602 -1.1 -0.9 2.3 -2.6 -2.3
95 Matt Treanor 35 KCR 2347 -0.1 0.0 -1.7 -0.4 -2.3
96 Alex Avila 24 DET 4866 -0.2 1.6 -3.8 -0.2 -2.5
97 Ryan Doumit 30 PIT 2043 -0.2 -1.1 -0.6 -0.6 -2.5
98 Jose Morales 28 COL 627 -1.3 -1.0 -0.7 0.6 -2.5
99 Koyie Hill 32 CHC 1549 -0.3 -1.4 -0.6 -0.2 -2.6
100 Eli Whiteside 31 SFG 2409 -1.6 0.6 -0.2 -1.4 -2.6
101 Salvador Perez 21 KCR 1461 0.4 -0.5 -1.5 -1.3 -2.9
102 Francisco Cervelli 25 NYY 1340 0.4 -2.0 -0.4 -1.5 -3.6
103 Hank Conger 23 LAA 1914 -0.2 -1.2 0.7 -2.8 -3.6
104 Ronny Paulino 30 NYM 2250 -0.1 -1.5 -0.1 -1.9 -3.6
105 Brian McCann 27 ATL 4565 0.5 1.0 -1.3 -4.4 -4.2
106 Carlos Corporan 27 HOU 1764 0.5 -1.8 -1.2 -1.9 -4.3
107 Dioner Navarro 27 LAD 1768 -0.3 -1.8 -1.1 -1.1 -4.3
108 John Jaso 27 TBR 2496 -0.1 0.1 -1.3 -3.4 -4.6
109 Jason Varitek 39 BOS 2408 -0.1 0.1 0.4 -5.7 -5.3
110 Jonathan Lucroy 25 MIL 4361 0.5 -0.1 -5.3 -1.4 -6.4
111 A.J. Pierzynski 34 CHW 4283 1.2 0.8 -1.6 -7.3 -6.9
112 Jarrod Saltalamacchia 26 BOS 3721 -1.2 0.9 -8.2 1.6 -7.0
113 Miguel Olivo 32 SEA 4445 -1.0 -1.0 -6.7 0.7 -8.1
114 J.P. Arencibia 25 TOR 4589 0.5 0.5 -5.5 -3.9 -8.3

 

 

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.