From: mjones@fenway.aix.kingston.ibm.com (Mike Jones)
Subject: Re: Sheffield is NL MVP
Date: Fri, 09 Oct 92 17:18:18 GMT
Reply-To: mjones@donald.aix.kingston.ibm.com
Organization: IBM Corp. Kingston NY

In article <1992Oct8.151416.1615@island.COM> fester@island.COM (Mike Fester) writes:
>In article <1992Oct06.221113.16526@watson.ibm.com> mjones@donald.aix.kingston.ibm.com writes:
>>In article <1992Oct6.182056.1015@island.COM> fester@island.COM (Mike Fester) writes:
>>>>value or anything like that.  It's simply the percentage of the time a
>>>>player doesn't make an out.  Why should homers count more in OBP than
>>>>walks?  Slugging, OTOH, is measuring how much a player can move runners
>>>>along (and how far he can get by himself), and walks do move other
>>>>players along.
>>>Sometimes.
>>Almost as much as singles, in fact. (If you're the Red Sox, almost *exactly*
>>as much.) Therefore, if SLG is a measure of runner (including batter-runner)
>>advancement, then walks should count almost as much as singles.
>But it is NOT a measure of runner advancement, now is it, Mr Jones? It is a
>measure of BATTER advancement in a charged at-bat, where he doesn't force
>possible other runners into making outs. 

Strictly speaking, you're right. On the other hand, SLG is, practically a
very good measure of runner advancement. Do you dispute this?

>>>>>>Of course it can.  But if two players have the same OPS but different OBP and
>>>>>>SLG, you should take the higher OBP, unless it's an extreme case like a taller
>>>>>>version of Eddie Gaedel.
>>>>>Nope. Way too many exceptions (even at the team level) to make a statement like
>>>>>that. I'd take a guy that matched my team's needs the best.
>>Mike, I've become convinced that you are deliberately being difficult on
>>this point. In general, OBP is a scarcer skill than SLG. Take a random
>What do you think you mean by "scarcer"? In fact, the average OBP values
>are lower, but this is LARGELY an artifact of the way the two are measured.
>Period. 

Irrelevant. OK, number alert:
  stat                 LIV    LAVG    UIV   VAR     SD
batting average       .173    .263   .345  .0009  .0302
on base percentage    .230    .330   .456  .0015  .0382
slugging percentage   .226    .391   .624  .0045  .0673

These numbers are for all batters, AL and NL, with over 150 PAs (AB+BB) in
1992. LIV is "lowest individual value", LAVG is league average, UIV is
"upper individual value", VAR is variance, and SD is standard deviation. As
you can plainly see, the standard deviation for SLG is almost twice the
standard deviation for OBP. What does this mean? Well, it means that it's
much easier to find batters who are significantly above average in SLG than
in OBP, or that the "spread" of SLGs is larger than that of OBPs. That's
what I mean by "scarcer". The fact that the numbers are lower for OBP is
because they measure two different things, and is also completely
irrelevant.

>>sampling of players if you don't believe me. Also, OBP is a skill that
>>improves your *team* more than SLG, because adding OBP increases the number
>>of PA's a team will get in a season. There *are* exceptions to the RC model
>>at the team level, but there are really pretty few of them. Even with the
>Pretty few, hunh? This year, Baltimore, Milwaukee, Minnesota, Detroit, Toronto,
>all seem to be a bit out of whack with each other.

So bloody what? This is statistical analysis, not physics. There are no
"laws" governing the production of runs. The fact is (and it *is* a fact)
that if you look at a large sample of teams over a period of years, Runs
Created seldom misses by more than 7% or so in predicting their scoring. Is
it perfect? Of course not. Does it work? Pretty well, thank you. A number of
people (including me, in a small way) have looked for causes of error and
(to my knowledge) haven't found any systematic errors (i.e., the errors
don't correspond to any factor yet found). The errors are of a size that
indicates that it may partially (possibly completely) be the result of
random fluctuations - luck. 

>>exceptions, RC fits the team run scoring model better than anything else
>>anyone's come up with. In the real world, where there are realistically
>>never players whose OBP is more than, say, .020 higher than their SLG over a
>>reasonable number of PA's, a player with equivalent OPS and higher OBP is
>I suppose id you define "realistic # of PA's" as that for which this is true,`
>you are correct. In any event, it's a pretty meaningless statement: MOST of
>your OBP and MOST of your SLG are from the same source- hits.

Actually, I think I'll have to take some of this back. I'd pick 150 as a
realistic number of PAs, and a quick look shows 25 players had OBP-SLG>.020
in 1992; seven of them had over 400 PAs, 4 over 500, and 2 over 600. I
doubt it ever happens for a team, though. I dispute your other point,
though. Most of your OBP is from hits, but your SLG is determined much more
by the type of hit. To wit:

 Player     BA  SLG  OBP  G  AB  R  H   TB 2B 3B HR RBI BB
DYKSTRA,L .301 .406 .375  85 345 53 104 140 18 0  6  39 40
LEE,M     .263 .316 .343 128 396 49 104 125 10 1  3  39 50

Same number of hits. 13% difference in PAs. 50% difference in SLG.

>>>?? It depends on your team. As both contribute to scoring (and BTW, for the
>>>most part, they are the same thing) it would depend on your team's needs. 
>>>Another high OBPer behind Thomas isn't going to drive him in any more often.
>>The same thing? I'm afraid I don't understand this at all.
>You don't understand that, for the most part, OBP and SLG have as their 
>largest contributor, hits (actually, entirely, in the case of SLG, which 
>attaches a relative value to the type of hits)?

No, I don't understand this because it's not true. See example above. OBP
and SLG measure COMPLETELY DIFFERENT THINGS. The fact that both use hits in
their calculation is irrelevant.
 
>>Let's consider Thomas. Say that he has George Bell hitting behind him. Bell
>>had a .713 OPS, made up of .417 SLG and .296 OBP. What happens if we
>>exchange him for, say, Chad Curtis? His OPS was .712, on .374/.338. Now what
>>happens? Well, Curtis probably drives in Thomas directly a bit less often.
>How much less often over the course of a season? 10 times? 20 times?

Hard to say. If Curtis wasn't a rookie, I could look up their relative % of
runners driven in from various bases. If you prorate Curtis' stats to Bell's
number of AB's, he has 14 more 1B, 5 fewer 2B, 3 more 3B, and 4 fewer HRs.
Considering that Thomas isn't the sort of guy who's likely to score from
first on a double, it looks like the difference would be on the order of
4 or 5 RBI that Bell would get that Curtis wouldn't. As a guess.
 
>>On the other hand, in the same number of PA's that Bell had (637), Curtis
>>would have made 27 fewer outs. That's another ENTIRE GAME's worth of outs
>>that are now opportunities for other players to drive in Thomas. But, you
>So how many runs can the Sox expect to score in another game?

In general, about 4.5. That's league average. On the other hand, we're
talking about outs here that are made behind a guy who's among the league
leaders in OBP, who also does a pretty good job of getting himself into
scoring position (46 2B, 3 3B, 6 SB), so those outs are going to be worth
relatively more. Also, the 4.5 number is a league average figure. I wouldn't
be terribly surprised to find that the White Sox averaged more than that.

   Mike Jones  |  AIX/ESA Development  |  mjones@donald.aix.kingston.ibm.com

There's facts about dogs, and there's opinions about them. The dogs have the
facts, and the humans have the opinions. If youwant facts about a dog, always
get themstraight from the dog. If you want opinions, get them from humans.
	- Mojave Dan in *Kinship with All Life", by J. Allen Boone