It was a big week for me: vacation on Cape Cod, my first trip to Fenway Park, having my car’s malfunctioning engine fan hot-wired by helpful small town folks in a Tim Horton’s parking lot at midnight, running over a skunk. Bobby V even threw a pointless and grandstanding tantrum in honor of my presence.

But back to brass tacks, or Parkes is going to have me flogged. I have been doing my simple catcher defense ratings on a roughly monthly basis, but with less than two months to go, I am actually not going to do a September edition. Instead, in order to avoid redundancy, I will do a final version some time after the regular season is done. So this will have to hold you over in the meantime. There have actually been some big changes at the top since I last updated these ratings, so I suppose there are some possibilities for down-to-the-wire excitement.

Feel the rush!

As always, there is a boring methodological postscript at the end after the chart. But first, some brief comments. Recent trades have made some of this stuff a bit confusing because I take the raw stats from Baseball-Reference and they do not “merge” the numbers of players who have been traded.

Pitch Blocking (Passed Balls and Wild Pitches):

Kurt Suzuki’s bat bottomed out so badly at the plate this year that the As traded for George Kottaras and let Suzuki go the Nationals. His Oakland numbers would have him in the lead in this category, but a small sample of activity in Washington put him in the middle of the pack. Suzuki has always been considered a defense-first guy.

Matt Wieters is still the real leader. The Amazing Carlos Ruiz and the Underrated Ryan Hanigan are the real second- and third-place guys here, although Geovany Soto of the Cubs would be third if he hadn’t gone to Texas. The bottom remains basically unchanged: Wilin “Olivo” Rosario, A.J. “Wait, I Hit for Power Now?” Pierzynski, and Carlos “What Ever Happened to Me?” Santana.

Caught Stealing:

Yadier Molina has been doing work, surging into first place at almost six runs above average after not being in the top three in this category last month. Did teams forget not to run on him? With last year’s offense not looking like a fluke (even if he isn’t really as good as he has been with the bat this year), Molina may really finally be an actual superstar. Speaking of underrated superstars, Miguel Montero is second, and after a slow start to the season with the bat, he is on his way to the best year of his career in terms of wOBA. Ryan “Above Average” Hanigan quietly plods along in third place.

Poor ol’ Rod Barajas is still bringing up the rear, although Jesus Flores is making a late run at catching him (which probably explains the Suzuki trade). Making his debut in the bottom three of any category this year is Joe “Hometown Discount” Mauer. Remember when he saved baseball by staying in Minnesota?

Overall:

Let’s begin from the bottom and start with a shout out to Jason Castro. Castro moved out of the basement this month. Sure, part of that was missing time to injury, but nice job, anyway, Jason! Russell Martin has also moved out of the near-bottom. Wilin Rosario continues his stranglehold on being the worst of the worst behind the plate so far (at least according to this crude method). John Baker has made a strong move into second-worst. The hapless Jesus Flores really lost the ability to throw runners out lately, which is why he is now third-worst, although with the reduced playing time he probably won’t stay there long.

The real “news” from this update is on top. Carlos Ruiz has had a huge year with the bat for Philadelphia, and was also the top defensive catcher according to last month’s update. He has not been bad behind the plate since then, but he has been leapfrogged by three different players (Suzuki does not count if you include his Washington numbers so far).

In third, we now have Matt Wieters, who had a big defensive month in all respects — he’s an excellent player even with only a “good for a catcher bat.”

In second place, we have Ryan Hanigan.

And in first, we have the guy people forgot to stop running on: Yadier Molina, who is now at 11 runs above average with almost two months to go. Molina and Ruiz are both putting on shows as defense-first catchers who previously had “decent” bats, and now have awesome bats. They also provide two things to watch for one team struggling to stay relevant to the playoff race (St. Louis) and another for which age and contracts are finally coming home to roost.

 

Rank Player Tm PA FERuns TERuns PBWPRuns CSruns Total
1 Yadier Molina STL 3418 1.0 0.7 3.4 5.9 11.0
2 Ryan Hanigan CIN 2517 0.8 0.1 3.9 3.9 8.7
3 Kurt Suzuki OAK 2720 0.8 0.7 7.3 -0.9 7.9
4 Matt Wieters BAL 3421 0.3 -1.2 5.4 3.2 7.6
5 Carlos Ruiz PHI 3043 -2.1 1.4 4.3 3.3 6.9
6 Miguel Montero ARI 3362 0.3 -0.3 1.8 4.8 6.6
7 Buster Posey SFG 2850 -0.6 -0.1 3.2 1.8 4.2
8 Bobby Wilson LAA 1865 0.6 -0.7 2.6 1.2 3.6
9 Brian McCann ATL 3000 0.2 1.4 1.4 0.5 3.5
10 Tyler Flowers CHW 988 0.3 0.6 -0.2 2.7 3.4
11 Jeff Mathis TOR 1288 0.4 0.8 0.1 1.2 2.5
12 Nick Hundley SDP 1995 -0.1 -0.2 0.4 2.3 2.4
13 A.J. Ellis LAD 3229 0.2 0.1 -0.8 2.8 2.4
14 Brian Schneider PHI 804 0.2 0.5 0.6 1.0 2.4
15 Devin Mesoraco CIN 1553 0.5 0.5 0.8 0.4 2.2
16 Erik Kratz PHI 333 0.1 0.2 0.4 1.3 2.0
17 John Buck MIA 3083 0.9 -1.4 2.4 0.0 1.9
18 Geovany Soto CHC 1911 -0.9 -1.2 4.4 -0.4 1.9
19 John Jaso SEA 906 0.3 0.6 0.1 0.3 1.2
20 Alex Avila DET 2719 0.8 0.3 -0.3 0.2 1.0
21 Welington Castillo CHC 541 0.2 -0.1 0.7 0.2 0.9
22 Koyie Hill CHC 373 0.1 -0.2 0.8 0.2 0.9
23 David Ross ATL 1063 0.3 0.2 -1.7 2.0 0.8
24 Tony Cruz STL 776 0.2 -0.5 0.3 0.8 0.8
25 Kelly Shoppach BOS 1476 -0.3 -0.5 0.6 1.0 0.8
26 Anthony Recker OAK 339 0.1 0.2 -0.1 0.6 0.7
27 J.P. Arencibia TOR 2786 0.1 0.3 -0.9 1.2 0.7
28 Chris Iannetta LAA 1057 0.3 0.7 -0.3 -0.1 0.6
29 Jose Molina TBR 1994 0.6 -0.7 -1.3 1.9 0.6
30 Luis Exposito BAL 255 0.1 0.2 0.5 -0.1 0.6
31 Miguel Olivo SEA 1886 -0.2 -0.3 -2.1 2.9 0.4
32 J.C. Boscan ATL 91 0.0 0.1 0.3 0.0 0.3
33 Jhonatan Solano WSN 384 0.1 0.2 -0.9 0.8 0.3
34 Humberto Quintero KCR 1529 0.5 -1.4 0.5 0.7 0.2
35 Jonathan Lucroy MIL 1676 0.5 -0.9 0.6 -0.1 0.2
36 Drew Butera MIN 846 0.3 0.5 -0.1 -0.5 0.2
37 Salvador Perez KCR 1263 0.4 -0.2 -1.4 1.4 0.2
38 Taylor Teagarden BAL 318 0.1 0.2 -0.2 0.1 0.2
39 Derek Norris OAK 887 -0.5 0.6 0.3 -0.2 0.2
40 Ryan Lavarnway BOS 35 0.0 0.0 0.1 0.0 0.1
41 Stephen Vogt TBR 20 0.0 0.0 0.1 0.0 0.1
42 Carlos Corporan HOU 490 0.1 0.3 -0.8 0.4 0.1
43 Brandon Snyder TEX 3 0.0 0.0 0.0 0.0 0.0
44 Luis Martinez TEX 1 0.0 0.0 0.0 0.0 0.0
45 Bryan Holaday DET 135 0.0 0.1 0.1 -0.3 0.0
46 Matt Treanor LAD 980 0.3 -0.3 0.6 -0.6 -0.1
47 Carlos Maldonado WSN 118 0.0 0.1 0.1 -0.3 -0.1
48 Michael McKenry PIT 1591 0.5 0.5 1.2 -2.4 -0.2
49 Henry Blanco ARI 715 -1.3 0.4 -0.5 1.1 -0.2
50 Rob Johnson NYM 532 0.2 0.3 -0.1 -0.6 -0.2
51 Hank Conger LAA 185 -0.7 0.1 0.0 0.3 -0.3
52 Eddy Rodriguez SDP 76 0.0 0.0 -0.1 -0.4 -0.4
53 Ryan Doumit MIN 1516 0.5 0.5 -0.7 -0.8 -0.5
54 Eli Whiteside SFG 108 0.0 0.1 -0.5 -0.1 -0.6
55 Yan Gomes TOR 130 0.0 0.1 -0.7 0.0 -0.6
56 Blake Lalli CHC 121 0.0 0.1 -0.2 -0.5 -0.6
57 Ronny Paulino BAL 362 0.1 0.2 -0.4 -0.7 -0.7
58 Konrad Schmidt ARI 39 0.0 0.0 -0.7 0.0 -0.7
59 Jordan Pacheco COL 33 0.0 0.0 -0.5 -0.3 -0.7
60 Luke Carlin CLE 139 0.0 0.1 -0.4 -0.4 -0.7
61 Josh Thole NYM 2468 -3.0 1.1 1.5 -0.3 -0.7
62 George Kottaras MIL 854 0.3 0.5 0.2 -1.8 -0.8
63 Josh Donaldson OAK 104 0.0 -0.4 0.0 -0.5 -0.9
64 Dioner Navarro CIN 80 0.0 -0.4 -0.3 -0.3 -1.0
65 Mike Napoli TEX 2304 -0.1 0.5 0.5 -2.0 -1.1
66 Wilson Ramos WSN 900 -0.5 0.6 -0.2 -1.0 -1.1
67 John Hester LAA 1084 0.3 0.7 0.3 -2.5 -1.1
68 Hector Sanchez SFG 1254 -0.4 -0.2 -1.7 1.0 -1.3
69 Sandy Leon WSN 297 0.1 -0.3 -0.8 -0.3 -1.3
70 Jose Lobaton TBR 1343 -1.1 0.4 -0.3 -0.3 -1.4
71 Brayan Pena KCR 1466 -1.1 0.0 1.1 -1.5 -1.4
72 Brett Hayes MIA 1167 -1.1 -0.7 0.8 -0.4 -1.4
73 Yorvit Torrealba TEX 1670 0.5 0.1 -1.1 -1.0 -1.5
74 Mike Nickeas NYM 1206 -0.4 0.3 -1.0 -0.4 -1.5
75 Russell Martin NYY 2964 -0.6 0.4 -1.3 -0.1 -1.6
76 George Kottaras OAK 166 0.1 -0.9 0.2 -1.1 -1.7
77 Yasmani Grandal SDP 731 0.2 -1.0 0.1 -1.1 -1.7
78 Wil Nieves COL 472 0.1 -0.2 0.0 -1.6 -1.7
79 Chris Stewart NYY 1174 0.4 -1.2 -0.5 -0.5 -1.9
80 Chris Gimenez TBR 776 -2.0 0.5 0.3 -0.8 -2.0
81 Jesus Montero SEA 1420 -0.3 0.4 -1.5 -0.6 -2.0
82 Steve Clevenger CHC 1154 -1.2 0.2 0.5 -1.7 -2.1
83 Jarrod Saltalamacchia BOS 2753 -0.7 -0.2 0.6 -2.0 -2.2
84 Ramon Hernandez COL 1454 0.4 0.0 -0.9 -1.7 -2.2
85 Carlos Santana CLE 2660 0.8 -1.2 -3.8 2.0 -2.2
86 Omir Santos DET 122 -0.7 -0.4 -0.2 -0.9 -2.3
87 Gerald Laird DET 1190 -0.4 0.3 0.3 -2.5 -2.3
88 Kurt Suzuki WSN 127 0.0 0.1 -5.5 3.1 -2.3
89 Chris Snyder HOU 1935 -0.2 0.7 -1.4 -1.5 -2.4
90 Martin Maldonado MIL 1741 0.5 -1.8 -0.3 -0.9 -2.4
91 Joe Mauer MIN 1895 0.6 0.2 0.1 -3.4 -2.5
92 Lou Marson CLE 1501 -0.3 0.9 -0.2 -3.1 -2.6
93 Geovany Soto TEX 162 0.0 0.1 -2.9 -0.4 -3.2
94 Rod Barajas PIT 2477 0.8 0.6 1.0 -5.8 -3.5
95 Jason Castro HOU 1911 0.6 -1.2 -1.8 -1.2 -3.6
96 A.J. Pierzynski CHW 3157 1.0 0.5 -4.1 -1.0 -3.6
97 Jesus Flores WSN 2390 0.0 0.1 -1.0 -4.0 -4.9
98 John Baker SDP 1463 -0.3 0.0 -2.5 -2.5 -5.4
99 Wilin Rosario COL 2364 0.7 -2.8 -7.5 1.7 -7.9

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 (1)

  1. thank you for sharing

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