From: hbrooks@uiatma.atmos.uiuc.edu (Harold_Brooks)
Newsgroups: rec.sport.baseball
Subject: Re: AL RC/27 Leaders
Date: 12 Aug 92 19:25:06 GMT
Organization: NSSL

In article <1992Aug12.175224.27309@leland.Stanford.EDU> claudius@leland.Stanford.EDU (Nelson Lu) writes:
>In article <BsvI1A.7B8@news.cso.uiuc.edu> hbrooks@uiatma.atmos.uiuc.edu (Harold_Brooks) writes:
>>We can't sum RC/27 into anything meaningful, but we can sum Runs Created.
>>Bill James did this back in the '82 Abstract and I've done it here using
>>Don Hearth's posted AL stats from a week ago.  I've used the simplest
>>runs created formula
>>
>>(Hits + Walks)*(Total Bases)/(At Bats + Walks) = RC
>>
>>for everyone in the AL and summed to get team and league predicted runs.
>>More detailed versions of the formula, which might be what Nelson is
>>using, should have smaller errors but the necessary data are not 
>>available.  (%Error = 100*(Created-Scored)/Scored).  In any case, 
>>the fit isn't bad, 8 of the 14 within 12 runs, none worse than 10%--
>
>Harold, can you (since I don't know how to :-)) do it with this formula:
>
  
(So all those things your boss was saying about you being lazy are true.:-)

Since you asked...

I've also done the team and league numbers two different ways.  The first
is to sum the individual players' Runs Created.  The second is to sum the
individual players' raw numbers and then calculate RC from the sums.

RC1 = simple RC = (H+BB)*TB/(AB+BB)

RC2 = A * B / C where

A = TB + (.26 * BB) + (.52 * SB)
B = H + BB - CS
C = AB + BB

RC1 looks like it does a little bettter.  RC2 appears to have a bias to 
overestimate.  I don't recall that from the past, but I seldom look at
anything beyond RC1 or a simple variant anyway.  (It's always nice to see 
simple things do well in our complex world.:-)  RC2 gets hammered over-
estimating the Orioles and the Mariners.  The former may be related to
our recent discussion about the Orioles' batting order.  I don't know
enough about the Mariners to commment on their situation.  RC2 does 
get close to the Brewers, however.  Error in %.  (Data through 9 August.)

                   Sum(Individual RC)           Sum(Individual raw stats)
Team           R     RC1     RC2  E(RC1) E(RC2)  RC1     RC2  E(RC1) E(RC2)
California    416   387.3   407.0  -6.9  -2.2   384.4   402.9  -7.6  -3.2
Milwaukee     493   464.1   494.8  -5.9    .4   458.3   487.3  -7.0  -1.2
Detroit       549   528.4   563.2  -3.7   2.6   525.1   557.5  -4.4   1.5
Minnesota     553   538.4   568.6  -2.6   2.8   532.1   560.6  -3.8   1.4
Chicago       507   494.8   539.7  -2.4   6.4   486.5   528.6  -4.0   4.3
Boston        385   382.1   411.0   -.8   6.7   377.6   405.8  -1.9   5.4
Oakland       520   519.0   567.3   -.2   9.1   512.3   558.2  -1.5   7.3
Toronto       520   518.9   556.9   -.2   7.1   515.3   551.6   -.9   6.1
New York      479   482.7   514.9    .8   7.5   480.3   510.5    .3   6.6
Texas         500   508.4   542.5   1.7   8.5   505.6   538.2   1.1   7.6
Kansas City   436   446.6   469.6   2.4   7.7   441.2   463.1   1.2   6.2
Baltimore     520   536.8   579.3   3.2  11.4   534.7   576.3   2.8  10.8
Cleveland     440   461.1   482.0   4.8   9.5   456.1   475.8   3.7   8.1
Seattle       478   515.4   539.7   7.8  12.9   503.8   526.5   5.4  10.2
AL Totals    6796  6784.0  7236.4   -.2   6.5  6707.7  7133.8  -1.3   5.0

Harold
-- 
Harold Brooks                    hbrooks@uiatma.atmos.uiuc.edu
National Severe Storms Laboratory/CIMMS (Norman, OK)
Andres Galarraga (Through 11 August)  .235 BA  .359 SLG  .273 OBA
24 H away from .300  7 HBP  6 BB    664+ PA w/o a sacrifice
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