2010 Caught Stealing Projections

As we all know, catcher defense is difficult to quantify and probably even more difficult to predict. Nevertheless, one of a catcher’s most important jobs behind the plate is to prevent base runners from swiping bases. Dan Turkenkopf’s article over at Beyond the Boxscore about a month ago projected catchers’ block percentages for the upcoming season and it gave me the idea of attempting to project catchers’ ability to prevent runs by preventing the stolen base.

For this experiment, I used essentially the same methodology used by Turkenkopf in his article, specifically the Marcel based 5-4-3 approach to projecting runs prevented for the 2010 season. This means that I used catcher data from the last three seasons to project caught stealing percentage as well as the number of stolen base attempts against each catcher if they all played 120 games (1080 innings) behind the plate. For the run values, I used those identified in The Book — plus 0.467 runs per caught stealing and minus 0.175 runs per stolen base. Then I determined the average number of runs prevented by the catchers over those 1080 innings and figured each catcher’s runs above or below average. For those catchers with less than three full years in the league, I used minor league caught stealing percentages and major league attempts against over a 120 game period.

The table below shows the results. (For purposes of conciseness, I’m only including primary backstops. The full google spreadsheet may be found here.) ProjSBA is projected stolen base attempts. ProjCS% is projected caught stealing percentage. SBRAA and CSRAA are stolen base and caught stealing runs above average, respectively, based on their respective run values. 2010RAA is simply CSRAA minus SBRAA and 2010RAA is 2010RAA/120 based on 120 games of work.

Pittsburgh Pirates vs St. Louis Cardinals
**Yadier Molina would be much further ahead of the pack if runners dared to run against him more frequently.** (Icon/SMI)







































































































































































































































































2010 Catcher Caught Stealing Projections
Catcher ProjSBA ProjCS% SBRAA CSRAA 2010RAA 2010RAA/120
Gerald Laird 104 36.6 11.5 17.8 6.2 6.2
Yadier Molina 55 42.4 5.5 10.9 5.4 5.3
Ryan Hannigan 91 35.9 10.2 15.2 5.0 4.9
Rod Barajas 83 34.6 9.5 13.4 3.9 3.9
Joe Mauer 75 35.0 8.5 12.2 3.7 3.7
Miguel Olivo 86 33.3 10.1 13.4 3.3 3.3
Matt Wieters 126 31.2 15.2 18.3 3.2 3.1
Ivan Rodriguez 76 33.0 9.0 11.8 2.8 2.8
Russell Martin 94 29.8 11.5 13.0 1.5 1.5
Benjie Molina 99 28.1 12.5 13.0 0.5 0.5
Geovany Soto 106 27.8 13.4 13.7 0.3 0.3
Kurt Suzuki 85 27.4 10.8 10.9 0.1 0.0
Ryan Doumit 116 27.3 14.8 14.8 0.0 0.0
Carlos Ruiz 104 26.9 13.3 13.1 -0.2 -0.3
Kelly Shoppach 85 26.4 11.0 10.5 -0.5 -0.5
Victor Martinez 97 25.6 12.7 11.6 -1.1 -1.1
Jason Kendall 88 25.1 11.5 10.3 -1.2 -1.3
Chris Iannetta 86 24.6 11.4 9.9 -1.5 -1.5
Rob Johnson 132 24.7 17.4 15.2 -2.2 -2.2
Miguel Montero 98 23.2 13.2 10.6 -2.6 -2.6
Brian McCann 101 22.9 13.6 10.8 -2.8 -2.9
A.J. Pierzynski 111 21.7 15.2 11.2 -4.0 -4.0
Greg Zaun 97 20.7 13.5 9.4 -4.1 -4.2
Jorge Posada 159 22.8 21.5 17.0 -4.5 -4.6
Mike Napoli 122 21.0 16.8 11.9 -4.9 -4.9
Jarrod Saltalamacchia 121 20.4 16.9 11.6 -5.3 -5.4
John Baker 116 20.1 16.2 10.8 -5.4 -5.4
Jason Varitek 106 17.3 15.4 8.6 -6.8 -6.9

Some observations:

First of all, this is based on historical catcher data over the previous 3 years and pays no attention to new pitchers on the catchers’ respective teams and their ability to hold runners on. Second, Yadier Molina — the best defensive backstop in the game — would be much further ahead of the pack if teams were willing to run against him. The fact that many catchers have twice as many stolen base attempts against tells us that teams realize that running against Yadi is a risky proposition. Third, I was surprised at how high Wieters and Mauer finished on this list. The primary reason, beside the fact that they are respectable at throwing runners out, is that they may be better than their reputation. That is, by risking running against them, teams make them better. Ryan Doumit and Kurt Suzuki are projected to be roughly league average catchers at throwing out base runners. The difference between the best and worst in the game is just more than one win per year.

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Comments

  1. DrBGiantsfan said...

    You partially addressed my concern near the end of the article.  Aren’t SB/CS stats kind of like the defensive equivalent of Runs and RBI’s in that stopping the running game is really a team effort? 

    Pitcher’s moves to first.

    Game calling/pitchouts.

    Slide steps vs leg kicks.

    Yes, Catcher’s arm strength/quickness of release.

  2. TCQ said...

    Key point is right at the end; it just doesn’t matter that much. Kind of like non-steals baserunning. Only matters if the players you’re comparing are really, really similar anyway.

  3. Chuck Brownson said...

    It’s fair to say that there’s not a ton of difference between top and bottom but it’s important to remember that this is just part of catcher defense as well.  It can be a useful tool, I think, when comparing similar catchers on the same team to see who should play more, for example.  Also, take Yadier Molina, for example.  He’s half a win above average here and nearly a full win better than McCann, for example (8.3 runs).  If you look at Turkenkopf’s projections on blocking balls in the dirt, he’s another half a win better there.  Add it together, and Molina’s projected to be better than McCann by about 1.3 wins defensively.  Now, McCann’s much better than Molina offensively but this closes the gap somewhat.

    Also, the gap between Mike Napoli and Jeff Mathis on the Angels, for example, isn’t that great.  It’s certainly not enough to make up for the huge gap in their offensive talents which tells me that Napoli ought to get a lot more time behind the plate than he does.  And when you compare two catchers on the same team, you come much closer to a useful comparison b/c they’re often catching the same pitchers (though not always, of course).

  4. MikeS said...

    I’m always cautious when I’m told something doesn’t matter that much because the spread from top to bottom is small.  It would be more accurate to say that this model predicts it doesn’t matter much.  If the model is accurate then it is true but assuming your model is 100% accurate is an easy trap for a researcher to fall into.  It is posiible that the spread in talent is just as big for throwing, defense and baserunning as it is for hitting and pitching which are much easier to measure.  Maybe we just do not yet have measurements or models that are accurate enough to show that.

  5. Joe R said...

    Personally, I think CS% underrates good catchers even more so.

    Example: if the CS% of catcher A is 50%, and the CS% of catcher B is 25%, catcher A is more than 2x as good at gunning down baserunners as catcher B, because odds are, most guys aren’t even bothering to run.

  6. Joe S formerly of Brooklyn said...

    There are a lot of variables that go into this. I am a Yankees’ fan who was able to follow the team pretty closely in 2009.

    I expected Jorge Posada’s weakness at throwing at baserunners to hurt the team. Note that I don’t dispute his ranking in what’s above!!!

    If that weakness did hurt the team, I didn’t notice it. There may be reasons for THAT, which matter in the discussion above:

    1. Posada didn’t catch AJ Burnett. He throws right-handed and can be wild—which increases base-running options. Having a better defensive catcher handle AJP helped in (at least) the base-running dept.

    2. 1/4th of the time, Posada was catching when Pettitte was pitching. That holds down baserunning, doncha think? Another 1/4th of the time, CCS was pitching; he’s left-handed, isn’t he?

    3. Some of the time, the NYY’s were ahead by a significant margin. That holds down baserunning, I think.

    4. The Yankees played a lot of games against some teams (in the East, teams other than the Rays) that do not run a lot. This prob. isn’t the case in the NL, I am guessing.

    [orioles 76 sb, 37 cs]
    [r-sox 126 sb, 39 cs]
    [jays 73 sb, 23 cs]
    [rays, 194 sb, 61 cs]

    5. Posada caught a lot of games in which Rivera closed. Teams don’t seem to run on Rivera; perhaps that’s b/c teams don’t seem to get baserunners on against Rivera.

    6. Posada caught a lot of games in which the NYY bullpen was involved. It had a relatively high strikeout ratio. That tends to reduce baserunning, doesn’t it?

    7. In 2009, Phil Coke got into a lot of games. He throws left-handed which (in theory) reduces the stolen base possibilities.

    I am sure the stat guys are geniuses, but I’m not sure all of this can be taken into account. Based on what we all think we know about his defensive abilities AND his recovery from injury, Posada should have had a WORSE 2009 behind the plate. It should have hurt the team for which he played.

    It didn’t appear so.

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