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Bloops: Sabermetric Cartoons!

Posted by Neil Paine on March 17, 2011

Curious about the role of luck in pitching statistics? Then prepare yourself for a series of sabermetric cartoons courtesy of DRaysBay's Bradley Woodrum...

I'm pretty sure he's going to continue making these, so check out Bradley's YouTube account to keep up with future sabermetric cartoons.

This entry was posted on Thursday, March 17th, 2011 at 12:30 pm and is filed under Bloops, Sabermetrics, Videos. You can follow any responses to this entry through the RSS 2.0 feed. Both comments and pings are currently closed.

6 Responses to “Bloops: Sabermetric Cartoons!”

  1. John Autin Says:

    Thanks, Neil. Those are surprisingly fun and effective, in spite of the fairly primitive animation -- or maybe because of that.

  2. Thomas Court Says:

    Hmmmm... Very interesting. Anything that gives me a better understanding about what makes a great player is fine by me. I am totally on board with things like OPS because at its core it measures important things overlooked by old school analysts who cling to a player's batting average. Looking at the 1996 Yankees: A sabermetrician who fields a team of Paul O'Neills and his .302 avg is going to circle the track with the unenlightened person who drools at Mariano Duncan's .340 avg. Why? Because we have learned that a .340 avg means little when a player cannot do the things that OPS measures - namely finding other ways to get on base, and cracking the ball off of, and occasionally over, the wall. We as fans are in a much better place because of this. Sabermetrics is truly outgrowing the work of the early pioneers.

    But is it growing too fast?

    I have reservations about some of the conclusions of these cartoons. FIP seems pretty sound to me, because like OPS it measures what a player does to help his own cause.

    But LOB% is where you lose me. Are we supposed to believe that "Roy" was extremely lucky last year because he stranded 83% of the baserunners he allowed? I would think that it's his ability that allowed him to do that. Imagine a random game in 2010. Runners on first and second, one out. You have the choice of bringing in "Roy" or grabbing "Sidney" out of retirement to get your team out of the jam. Is the reason you bring Roy in because he has tamed the Luck Dragon in 2010, or because he is just more talented? How did those runners that did score off of Roy and Cliff reach home plate? Is there a coin that comes up 28% "score" and 72% "stranded" that is flipped? And somehow Roy's flips favored him while Cliff's did not?

    And what about "Mariano?" Is he the luckiest pitcher to ever live? Remember the movie Rounders? When Matt Damon tries to explain that poker, (although appearing to most to be a game of chance) at its highest level, is a skill game? So is "Mariano" the luckiest guy in Vegas? Or is he precisely the guy you would want on the mound with runners on because of his ability to pitch in that situation.

    I am intrigued by what I see here. I am NOT saying I disagree with it completely. But I do feel that Roy's success with runners has a lot more to do with more tangible things like:
    1. Him being a very talented pitcher to begin with.
    2. Moving to the National League.
    3. Decisions about pitching in jams that HE makes (didn't Mariano teach him the cutter?).

    Tangible things... Not some Green Dragon that happened to find other pitchers to eat last year. And BABIP? Well, again I think we are talking about the same thing. If I faced major league pitching... would my astoundingly low BABIP be the result of luck or because of the fact that my ability dictates that I do not belong out there? With BABIP and LOB% I think it is ability and not luck that allows players to consistently deviate above the norm.

  3. Neil Paine Says:

    #2 - Right, and I think a lot of that is what TangoTiger touched on as well -- given a big enough prior sample, players are going to regress to their previous career LOB% (and to a lesser extent, BABIP) rather than the league average.

    That said, the theory behind LOB% regressing is basically a way to filter out who's been "bunching" hits. Brian Burke had a good example in this post: http://www.advancednflstats.com/2007/08/what-i-mean-by-luck.html

    "Consider a baseball game between a team and its perfect equal in every measure. In this evenly matched game, each team hits 9 singles. Team A happens to get its singles within 3 innings, then goes hitless for 6. Each inning of 3 singles produces 1 run. Team B's 9 singles happen to be spread across 9 innings, resulting in zero runs. Team A wins 3-0, although each team performed equally well.

    The total number of singles produced by a team is controlled by the interaction of skills between batters, pitchers, and defense--certainly not luck. But, when the singles occur and how they are bunched cannot be controlled, and their distribution is equally likely throughout the game. Batters have zero ability to chose when their hits occur. If they did, everyone's average with 'runners in scoring position' would be much higher. Therefore, when the hits occur is indeed random, and consequently, a sizable part of the outcome of a any single game is random."

    So regressing LOB% is about equalizing that "bunching" effect, and taking away the luck factor of when the hits take place.

  4. Johnny Twisto Says:

    players are going to regress to their previous career LOB%

    I didn't watch the videos, so I apologize if I'm way off-base. But how does a pitcher have any control over his LOB%? It's entirely a function of the base-out state he leaves and the quality of his relief pitchers. So how does a pitcher have a specific career LOB% to regress to?

  5. Nash Bruce Says:

    please, jesus, let the season start tomorrow....(i.e.,"today", in your time zones....)

  6. Neil Paine Says:

    #4 - LOB% measures more than just the rate at which bequeathed runners score; it measures how often a pitcher allows his own runners to score as well. So a good strand rate is at least partly a function of being a good pitcher and avoiding hits once you get in a jam (and avoiding the really bad types of jams if you have to allow baserunners at all). Of course, a bigger part is luck with "bunching" hits and luck with how the reliever deals with the situation you left him.