data.3news-bydate.train.rec.sport.baseball.104998 Maven / Gradle / Ivy
From: [email protected] (Harold_Brooks)
Subject: Re: Bases loaded walk gives Reds win in 12
Organization: Happy Mangum Rattlesnake Festival!
Lines: 71
In article [email protected] (Mark Singer) writes:
>In article [email protected] (Harold_Brooks) writes:
>>In article [email protected] (Mark Singer) writes:
>
>Actually, I think the large-scale sample size is part of the problem.
>It seems to me that if we were to plot all the players in baseball
>in regard to BA vs. Clutch BA deviation we would get some kind of
>bell curve. (The X-axis being the +/- deviation in clutch hitting
>vs. non-clutch; the Y-axis being the number of players.) Certainly
>there would be *some* players on the extreme ends of the bell. My
>*supposition* is that if we were to find the SAME players consistently
>(year after year) at one end of the bell or the other, then we might
>be able to make some reasonable conclusions about *those* players
>(as opposed to all baseball players).
Let's be careful here. If players' performance was completely random
in (Clutch-No Clutch), then you would still expect some players to be
good in the clutch every year and some to be not-so-good every year.
With two years worth of data, you'd have 1/4 of the players good each
year, 1/4 bad each year, and 1/2 would have one good and one bad year.
We have 96 players for 5 years ('84-'88). Just flipping a coin, you'd
expect 3 players to be good all 5 years and 3 to be bad every year.
This is what we actually get--
No. of good years 0 1 2 3 4 5
Clutch performers 4 10 37 24 18 3
Coin flip (random) 3 15 30 30 15 3
Essentially the distribution of clutch performers by number of years
of good performance is the same as what you would get if the process
leading to deviations from non-clutch performance was completely random.
If there was anything to clutch hitting (at least in this definition)
that had any predictive capability, you expect to see the number of
players at the ends to be much larger than that predicted by flipping
a coin. Further, if you limit yourself to players who were a lot above
or below average in clutch situations (say, 1 standard deviation from
the mean) more than one year, the random explanation still looks good.
In the four years ('84-'87) that I looked at the data from Elias, there
were 79 (29) players with a minimum of 25 (50) at bats in clutch
situations that were 1 sigma from the mean two different years. Of
those 79 (29) players, 38 (14) of them changed sign between the two
years. In other words, they were great clutch hitters one year and
really horrible the other year. If it was just a random process,
you'd expect those numbers to be 39.5 (14.5).
Everything that's been measured about clutch hitting over a period
of years that could be used to predict any ability with any
proposed definition has looked like a random process (with the
caveat that there may be something related to platoon advantage
that could be dragged out of the data--e.g., John Lowenstein
probably never had a "clutch" AB against a left-handed pitcher,
but he might well have had some in blowouts, so that there would
be a bias since his clutch ABs would be more geared to his
platoon advantage). This is not a subject that has been glanced
at casually. A lot of people have put a lot of effort into
studying it and every one of them, with the exception of the
Elias study, has been unable to find anything that would allow
you to predict how someone will do in clutch situations better
than flipping a coin. (Self-serving plug follows: some of the
flaws in the Elias study are discussed in my paper in the forth-
coming SABR book, _The Perfect Game_, by Taylor Publishing. The
authors are supposed to get a slice of the advance, so go bug
your local bookstores now, and maybe I can get enough to take my
wife to dinner once.:-)
Harold
--
Harold Brooks [email protected]
National Severe Storms Laboratory (Norman, OK)
"I used to work for a brewery, too, but I didn't drink on the job."
-P. Bavasi on Dal Maxvill's view that Florida can win the NL East in '93