2008 C Defense By PMR

by Dan Turkenkopf on Nov 18, 2008 12:00 PM EST in Stat-Colored Glasses Comment 3 comments

Each season, David Pinto releases his Probablistic Measure of Range (PMR) ratings based on play-by-play data from Baseball Info Solutions. PMR measures how many plays above or below expected each team or player made based on batted ball characteristics like velocity and location. Here at Beyond the Box Score, we're translating the play numbers into runs (following a method developed by LA Black Hawk of Waterloo). More information can be found in this post.

This entry, we look at catchers - first on the team level and then for individuals.

Team	In Play	Actual Outs	Predicted Outs	Outs Delta	Runs Delta	Runs / 4000	RAA / 4000
Brewers	4354	71	63.52	7.48	5.61	5.15	5.22
Mets	4335	54	48.85	5.15	3.8625	3.56	3.63
Pirates	4683	53	48.61	4.39	3.2925	2.81	2.88
Astros	4292	41	37.24	3.76	2.82	2.63	2.7
Yankees	4349	56	52.39	3.61	2.7075	2.49	2.56
Twins	4607	45	41.93	3.07	2.3025	2	2.07
Rockies	4535	58	55.02	2.98	2.235	1.97	2.04
Rangers	4667	49	46.47	2.53	1.8975	1.63	1.7
Orioles	4540	41	39.1	1.9	1.425	1.26	1.33
Phillies	4396	58	56.28	1.72	1.29	1.17	1.24
Braves	4383	63	61.73	1.27	0.9525	0.87	0.94
Diamondbacks	4224	50	49.19	0.81	0.6075	0.58	0.65
Padres	4419	64	63.44	0.56	0.42	0.38	0.45
Nationals	4417	34	33.64	0.36	0.27	0.24	0.31
Mariners	4512	42	42.22	-0.22	-0.165	-0.15	-0.08
Dodgers	4265	38	38.45	-0.45	-0.3375	-0.32	-0.25
Angels	4374	44	44.74	-0.74	-0.555	-0.51	-0.44
Blue Jays	4215	57	57.84	-0.84	-0.63	-0.6	-0.53
White Sox	4409	39	39.88	-0.88	-0.66	-0.6	-0.53
Tigers	4536	58	59.27	-1.27	-0.9525	-0.84	-0.77
Giants	4232	48	49.8	-1.8	-1.35	-1.28	-1.21
Rays	4264	50	51.91	-1.91	-1.4325	-1.34	-1.27
Red Sox	4232	51	53.09	-2.09	-1.5675	-1.48	-1.41
Royals	4413	49	51.24	-2.24	-1.68	-1.52	-1.45
Marlins	4338	58	60.75	-2.75	-2.0625	-1.9	-1.83
Indians	4513	45	47.9	-2.9	-2.175	-1.93	-1.86
Cardinals	4597	47	50.66	-3.66	-2.745	-2.39	-2.32
Athletics	4285	28	31.42	-3.42	-2.565	-2.39	-2.32
Reds	4299	52	60.3	-8.3	-6.225	-5.79	-5.72
Cubs	4156	42	51.03	-9.03	-6.7725	-6.52	-6.45

Player	In Play	Actual Outs	Predicted Outs	Outs Delta	Runs Delta	Runs / 4000	RAA / 4000
Wil Nieves	1327	14	9.94	4.06	3.045	9.18	9.25
Kevin Cash	1131	14	10.77	3.23	2.4225	8.57	8.64
Carlos Ruiz	2517	42	36.54	5.46	4.095	6.51	6.58
J.R. Towles	1252	8	6.01	1.99	1.4925	4.77	4.84
Chris Iannetta	2633	35	30.83	4.17	3.1275	4.75	4.82
Jason Kendall	3988	67	60.93	6.07	4.5525	4.57	4.64
Ryan Doumit	2933	31	26.57	4.43	3.3225	4.53	4.6
Humberto Quintero	1321	15	13.41	1.59	1.1925	3.61	3.68
Jason LaRue	1288	16	14.58	1.42	1.065	3.31	3.38
Victor Martinez	1388	16	14.48	1.52	1.14	3.29	3.36
Gregg Zaun	1807	30	28.04	1.96	1.47	3.25	3.32
Ramon Castro	1041	14	12.97	1.03	0.7725	2.97	3.04
Joe Mauer	3805	41	37.6	3.4	2.55	2.68	2.75
Guillermo Quiroz	1176	8	7.01	0.99	0.7425	2.53	2.6
Dioner Navarro	2911	38	35.59	2.41	1.8075	2.48	2.55
Ivan Rodriguez	2947	42	39.65	2.35	1.7625	2.39	2.46
Jeff Mathis	2351	33	31.46	1.54	1.155	1.97	2.04
Brian Schneider	2575	30	28.52	1.48	1.11	1.72	1.79
Josh Bard	1253	21	20.28	0.72	0.54	1.72	1.79
Ramon Hernandez	3272	33	32.09	0.91	0.6825	0.83	0.9
Miguel Montero	1191	15	14.77	0.23	0.1725	0.58	0.65
Chris Snyder	2733	33	32.54	0.46	0.345	0.5	0.57
Brad Ausmus	1719	18	17.82	0.18	0.135	0.31	0.38
Jarrod Saltalamacchia	1470	17	16.85	0.15	0.1125	0.31	0.38
Gerald Laird	2419	24	23.76	0.24	0.18	0.3	0.37
Jose Molina	2152	23	22.8	0.2	0.15	0.28	0.35
Brandon Inge	1541	21	21.16	-0.16	-0.12	-0.31	-0.24
A.J. Pierzynski	3428	31	31.53	-0.53	-0.3975	-0.46	-0.39
Kurt Suzuki	3608	25	26.45	-1.45	-1.0875	-1.21	-1.14
John Buck	2902	30	31.39	-1.39	-1.0425	-1.44	-1.37
Brian McCann	3470	49	50.81	-1.81	-1.3575	-1.56	-1.49
Miguel Olivo	1509	19	19.85	-0.85	-0.6375	-1.69	-1.62
Yorvit Torrealba	1819	21	22.19	-1.19	-0.8925	-1.96	-1.89
Nick Hundley	1482	18	19.13	-1.13	-0.8475	-2.29	-2.22
Matt Treanor	1561	23	24.36	-1.36	-1.02	-2.61	-2.54
Bengie Molina	3272	36	39	-3	-2.25	-2.75	-2.68
Jesus Flores	2116	13	15.03	-2.03	-1.5225	-2.88	-2.81
Russell Martin	3655	31	34.63	-3.63	-2.7225	-2.98	-2.91
Geovany Soto	3302	34	37.47	-3.47	-2.6025	-3.15	-3.08
Mike Napoli	1931	10	12.08	-2.08	-1.56	-3.23	-3.16
Rod Barajas	2262	24	26.6	-2.6	-1.95	-3.45	-3.38
Kenji Johjima	2617	20	23.53	-3.53	-2.6475	-4.05	-3.98
Yadier Molina	3185	29	34.24	-5.24	-3.93	-4.94	-4.87
Jason Varitek	3002	37	42.26	-5.26	-3.945	-5.26	-5.19
Paul Bako	2272	20	24.25	-4.25	-3.1875	-5.61	-5.54
Chris Coste	1853	15	18.62	-3.62	-2.715	-5.86	-5.79
John Baker	1477	13	15.96	-2.96	-2.22	-6.01	-5.94
Kelly Shoppach	2774	25	30.66	-5.66	-4.245	-6.12	-6.05
David Ross	1238	17	19.96	-2.96	-2.22	-7.17	-7.1
Shawn Riggans	1041	11	14.08	-3.08	-2.31	-8.88	-8.81

It's important to identify that these numbers only take into account a catcher's fielding. In other words, all we're looking at are bunts, nubbers and foul balls. Controlling the running game, calling pitches and blocking the ball aren't included here. Since catchers handle so few plays, these numbers really shouldn't be taken as gospel. Also, I've assumed that every play a catcher doesn't convert becomes a single, so each play made is an additional .75 runs (the value of an out minus the value of a single).

Because of the uncertainty included in such a small sample, there's really not a whole lot to say. People often talk about Jarrod Saltalamacchia having to be moved to first base, but he rated pretty close to average in this piece of catcher defense. Yadier Molina, who's generally considered a very strong defensive catcher, didn't do that well fielding balls in play, at nearly 5 runs below average. Jason Varitek didn't just lose a lot at the plate, he performed poorly in front of it as well, scoring 5 runs below average. I'm sure a lot of Red Sox fans are hoping the captain can turn it around next season. Chris Iannetta looks like a star in the making if he can keep it up, with his 127 OPS+ and nearly 5 runs saved above average fielding balls.

For those who are interested in catcher's defense, I'll be releasing the 2008 results for Catcher Block Percentage soon after Retrosheet releases their 2008 play-by-play data. Keep an eye out for it.

I'll also be posting the full spreadsheet used for the PMR calculations in the next day or so. I plan to attempt some additional analysis using some more historical data, and may even get into PMR projections.

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