7 thoughts on “Interesting”

  1. Like Jerry Seinfeld and his coffee, the Braves get most of their good pitching (especially starters) from the outside. I don’t think you can make a case for the Braves building better pitching from the inside than other teams. At least, I’ve never seen a good one made. Shanks tried to in his book, but that list seemed to make the opposite point. My goodness, Bruce Chen is on the list of successes.

  2. The Braves just keep the fit ones and end up trading the injured ones for the likes of J.D. Drew and Tim Hudson.

  3. Here’s another stat, I found odd, which you are welcome to double-check at Baseball Prospectus, assuming you are a member. It is the percentage of double-plays hit into, per opportunity. Here are a few (opportunities in parentheses):

    Orr (no surprise) 8.3% (24);
    Langerhans 8.3% (48);
    Chipper 12.3% (81);
    Marcus 13.2% (91);
    Andruw 13.6% (125);
    Furcal (!) 15.7% (70);
    Estrada 15.9% (63);
    Laroche 18.7% (91);
    KJ 20.6% (63);
    Julio 20.8% (53)

    With Andruw, it’s the opportunities that create the impression (just like with the RBIs). And Laroche is bad, but no worse than fan favorites like Julio and Kelly Johnson….

    These are small numbers, by the way: The +6.3% difference between Laroche and Chipper has a 95% confidence interval of +17.1% to -4.4%; which is to say that by standard statistical criteria, you would be disinclined to reject the proposition that the 6.3% difference occurred by chance and chance alone.

    Unless you actually had to watch Laroche at the plate…

  4. I’ll go ahead and cross-post my comment on USSM, just in case people don’t click through:

    After looking at this distribution a bit in Excel (by “distribution” I mean a binomial distribution with a mean of .80 and 30-player “teams”), what stands out to me is not the Mariners’ poor performance but rather the A’s excellence. Tango’s huge caveat that the data is basically indistinguishable from random data definitely applies, but there are still some conclusions that can safely be drawn. First, because of the location of the mean, one of the tails will be much longer than the other – the tail with more injuries. The shorter tail is bounded at 0 injuries, whereas the long tail stretches all the way to the other side of the distribution, even if reaching those extremities is unlikely. The end result is that outliers on the “long tail side” are much more likely.

    I simulated the equivalent of 1000 “teams” (i.e. groups of 30 players, each with binomial injury p = .80) and looked at the resulting histogram. The number of injuries per team ranged from 1 (10 times) to 14 (1 time). There were no “teams” in the sample with 0 injuries. The median value was 6 (as expected). 120 of the teams (12%) had 9 or more injuries (injury p >= .30), while 42 of the teams (4.2%) had 2 or fewer injuries.

    I hope people with more statistical training than myself can augment or criticize my mini-study. And all the caveats Tango mentions definitely apply. But the question of the hour (in my eyes at least) is not “What did the Mariners do wrong?” but rather “What did the A’s do right?”

  5. Regarding double plays, in my fantasy league, our commish added GIDP as a category this year. I had never really given much thought to who is good/bad at that so I looked up the players who hit into the most DP’s last year. Among the names at the top of the list were:
    M. Tejada – 24
    A. Ramirez – 25
    Pujols – 21
    Vlad – 19
    A-Rod – 18
    M. Cabrera – 20
    Manny – 17
    V. Martinez -16
    Sheffield – 16

    At that point, I decided not to worry about that category because the hitters who hit into the most DP’s were some of the best hitters in the league. 1- They had the most opportunities (which Diehl illustrates) and 2. They aren’t afraid to swing the bat with runners on which is good even if it means a few extra DP’s.

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