From: niepornt@phoenix.Princeton.EDU (David Marc Nieporent)
Subject: Re: Statheads and park effects
Originator: news@nimaster
Organization: Princeton University
Date: Mon, 21 Dec 1992 06:56:05 GMT

In<28591@optima.cs.arizona.edu> dkl@cs.arizona.edu (David K. Lowenthal) writes:

>I have a question for the stat people.  How can you justify this
>park effect thing?  

Because they're based on OBSERVATIONS over years of time.  The league
hits much better and pitches much worse in certain parks.  Consistently.

(As an aside, park effects are more useful for an estimation of value
than for a prediction of performance.  We know that certain amounts of
production are more valuable in certain parks than in others.  So the
adjustment is necessary for comparison purposes.)

>			In other words, for every park prediction made
>on the net, how many are correct?  Doesn't is seem like stretching
>it a little to say that a player with a different team will play at the
>same level with his new team in a new park?  

Yes, since very few people play at the exact same level every year with
the *same* team in the *same* park.  They play at *about* the same
level, with predictable changes over time (losing speed as they age,
gaining power as they age up to a certain point, then losing it, etc.),
but not exactly the same level.

But to say that a player, OVER A PERIOD OF YEARS, will have "better stats"
(this is in quotes because the stats aren't really better at all.  They
*look* better, but in context they are no different) in certain parks 
than in others is not stretching it at all.

>						Are players robots who you 
>can pick up and place in a new stadium and watch them do exactly the
>same things so that only the change in park matters?

No, of course not.  A player is not a robot.  I've noticed that
non-statheads often use this analogy to question stathead theories, but
it isn't a correct analysis of the way we treat ballplayers.

A better analogy might be that ballplayers are like loaded dice.  A given
ballplayer is weighted in a particular way, so that certain statistics
are more likely to come up than others.  Thus, a HR is much more likely
on a Cecil Fielder die than on a Manuel Lee die.  And Manny Lee hitting
a home run doesn't invalidate this fact, any more than rolling snake
eyes twice in a row invalidates the fact that it's a lot less common
than a roll of 7.

So, Greg Swindell is loaded towards an ERA of about 3.75 or so.  In the
average Cleveland of the past 6 years or so.  (You have to adjust that in
any given year for the park and league he is in.)  But then the fact
that he gets a 3.20 ERA in a given year doesn't invalidate the fact that
he's most likely to get close to a 3.75 ERA.

>Before last season, several netters and I engaged in a "discussion" of
>how Greg Swindell would do with the Reds.  He came from a huge park,
>Cleveland, and went to a homer haven, Riverfront.  He posted an upper
>3's ERA with Cleveland the previous year.  I was scorned, especially
>by Valentine, when I suggested his stats might improve because he was
>playing for a better team, even though the park effect would suggest
>a downward trend.  Netters predicted a mid 4 ERA for him given the 
>park change and his tendency to give up homers.  He ended up with
>a mid to high 2's ERA.

>Obviously this is only one example.  

Precisely, and therefore isn't very relevant.  As an aside, I disagreed
with Valentine about this prediction for the following reasons: (1) the park
adjustment, even from cavernous Cleveland Stadium 1991 to Riverfront,
isn't that big that an ERA in the mid 3s will go to the mid 4s.  Not
when you *also* factor in the 1/2 run National League adjustment. (2)
Swindell is a better pitcher than a 3.48 ERA in a huge stadium would
indicate, so he was likely to bounce back towards his career norm.  

And this year, Swindell happened to have a year *better* than his career
norm.  But not so much better as to be absurd, you know.  He had a 2.70
ERA this year.  That isn't really out of line, with the league adjustment,
with his career numbers.

Incidentally, you wanna bet that his ERA jumps this year back up to
normal career levels?  Well, except that I just remembered that he's now
in Houston.  So, wanna bet that his ERA, after park adjustment for
Houston, jumps to normal career levels?

>					But all i am asking is can you throw
>around park effects like they are gospel?  

No one does this.  

Let me put it this way -- I predict that the AL leader in home runs will 
most likely be either Canseco, Fielder, McGwire, Gonzalez, Belle, or Thomas.  
Now, that isn't guaranteed.  It is possible that Glenallen Hill will
take steroids, hit a bunch of fluke wind-blown homers, or sell his soul
to the devil and hit 40 home runs.  Would *you* bet on that?  Neither would I.

We're dealing with probabilities, not certainties.

>					   What percent of your predictions
>are correct?  

Well, I don't know which predictions these are, but the answer is: Most
of them.  The league as a whole hits much better in certain parks than
in others, and pitches worse in these parks.  So, most players do too.

>		Players can adjust to new surroundings, and stat people
>don't consider that.  These kind of things are called "intangibles", 
>or *luck* by Ms. Nichols.  For example, can't a pitcher who just pipes

No, that isn't what Sherri calls luck.  Adjusting to new surroundings
would be a skill, not luck.  For instance, Wade Boggs had a much BIGGER
park benefit from Fenway than the average player, because his particular
package of skills allowed him to take a unique advantage of Fenway Park.
That's a skill, though it is something that couldn't be predicted if he
hadn't played in Fenway before.

"Luck" is when Freddy Patek hits 3 HRs in a game.  

>the ball because he pitches in the Astrodome start nibbling the corners
>when he gets traded to Riverfront?

He could, which is why a prediction for an individual is always less
reliable than a prediction for a group of players.  This nibbling might 
work for a particular player, but it obviously doesn't work in general,
since the league as a whole pitches worse in Riverfront than in the
Astrodome.

On the other hand, if this nibbling enables him to be more successful in
Riverfront than the adjustment from the Astrodome stats would indicate,
it also shows that he should have been nibbling in the Astrodome.

>                                    Can't a hitter who hits 20 homers
>in Oakland take one look at the short Yankee porch and hit fewer homers
>because he wants to pull everything (cf. Dave Revering)?

You know, I had this sneaking suspicion that the reason most people
don't believe park effects is that they come up with a particular
counterexample (which, of course, wouldn't invalidate park effects at
all) which they've misremembered.  So I decided to look up the example
you brought up, Dave Revering.

Year   AB   HR   SLG
1978   521  16   415	OAKLAND
1979   472  19   483	   "
1980   376  15   492	   "
1981   87   2    333	   "
1981   119  2    336	NEW YORK
1982   40   0    200	   "
1982   135  5    370	TORONTO
1982   82   3    378    SEATTLE

Whatever his problem was, probably an injury, it had nothing to do with
going to New York, as far as I can tell.  He didn't hit in the months
before he got to New York, and he didn't hit after he left.

Anyway, your point is invalid, since this sort of thing can't be
predicted by *anyone.*  If you're playing poker, you don't ordinarily
bet on an inside straight because it *could* come up, though it
certainly could; you play the percentages.

Likewise, you don't bet on Greg Swindell being different from the rest
of the major leagues, though he certainly could be; you play the percentages.

Hope this helps,

-- 
David M. Nieporent   | Is it too early to start making predictions for 1993?
niepornt@phoenix.    | Probably, but that never stopped me before.
   princeton.edu     | ALE: Baltimore ALW: Chicago NLE: Montreal NLW: Atlanta
Baltimore Orioles 93 | AL MVP: Cal Ripken  AL Cy Young: Mike Mussina
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