## Re: effeciency per possession versus minutes played, FG%, etc

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• A key philosophy I ve worked on is that players can only stay the same or get less efficient as they take on a greater load of the offense, given their
Message 1 of 5 , Oct 9 7:42 AM
A key philosophy I've worked on is that players can only stay the
same or get less efficient as they take on a greater load of the
offense, given their teammates. Basically, they have to take worse
shots or make more mistakes. This concept has to be true to some
degree, otherwise the Bulls should have ALWAYS given the ball to
Jordan, every single time. Players have to become less efficient as
they take more possessions or else you'd have players like Steve
Kerr, shooting 50% from the 3pt line, who should always shoot the
ball.

There are players who, with a basic look at their numbers, don't
support this. Iverson is one. His efficiency goes up with more
possessions. Why? Because there are nights when a team tries to
cover him 1 on 1 and he gets hot, so he goes all night killing the
horrible defense. But such a look at offensive rating (points
produced per 100 possessions vs possessions used) is mixing cause and
effect. If a team were double teaming him and he kept trying to
score, his efficiency would go down. Fundamentally, it is very hard
to sort out cause and effect in looking at efficiency vs the load
that players take on.

The examples cited below are reasonable, but also ignore the distinct
role players like Ron Harper and Rick Fox. Hersey Hawkins is
probably a fair example of a role player whose role changed, though.

And, oh yeah, I always define efficiency in terms of either a floor %
(scoring possessions per possession) or points produced per 100
possessions. Formulas for these on my website.

I'll get back to this.... Meeting now...

--- In APBR_analysis@y..., "Mike G" <msg_53@h...> wrote:
> Bob, good job on the clarification of methods. I see line 1 and
line
> 2 of the statistics headings are misaligned, and some of the
> categories are actually `effective FG%', `production
> rating', `possession factor', `rebounds/48 min',
> and `points/possession'. Correct me if I didn't get these right.
>
> Then, I see %shot + %fouled + %turnover + % pass = 100 in every
case.
>
> The Possession Factor then must be guesstimated to create a total
> touches out of the possessions used, and determines those
breakdowns
> listed above.
>
>
> >i added some more stats to try to make clear each example:
>
> eff Prod
> Poss reb Pts
> Hawkins mpg ppg fg% To/min FG% Rat Fact %sht %3sht %fld %to %
> pass /48 Poss
> 90-91 38.9 22.1 47.2 .068 .515 .471 1.07 38
> 8 14 6 42 4.8 .533
> 95-96 34.4 15.6 47.3 .058 .554 .387 0.89 37
> 15 10 6 47 5.0 .507
>
> >here for hersey hawkins the turnovers are the same, 6 turnovers
per
> >100 ball possessions, so that's not the difference. he did get
> >fouled quite alot more (4%) in 90-91, in fact his FTM in 90-91 was
> >twice that in 95-96. but he shot better in 95-96, so its not
> >shooting (took twice as many 3pters in 95-96 per ball possession
> >than in 90-91). the biggest difference that i can see is he
handled
> >the ball about 20% more often per minute in 90-91, and add that to
> >his 5 more min/g is the reason he played better
>
> Greater FG %, more 3-point attempts, fewer FT attempts: what does
it
>
> .554 is a lot higher than .515, and 14% is a lot more than 10%.
> However, Hawkins' overall shooting was .579 in '91, and .591
in '96,
> only a small difference. In Charlotte, 1995, he had his career
high
> of .611
>
>
> eff Prod
> >Poss reb Pts
> >Barkley mpg ppg fg% To/min FG% Rat Fact %sht %3sht %fld %to %
> pass /48 Poss
> 95-96 37.1 23.2 50.0 .082 .521 .672 1.25 35
> 5 15 7 43 15.0 .502
> 96-97 37.9 19.2 48.4 .075 .526 .640 1.30 27
> 8 14 6 53 17.1 .389
>
> >. he shot just as well, got fouled just as often, and turned the
> >ball over about the same...
>
> Yep. Barkley's overall shooting was .571 in '96 and .566 in '97,
and
> dropped steadily thereafter. His 1997 rebounding rate was the best
> of his career, outside of 1987.
>
>
> eff Prod
> >Poss reb Pts
> Pippen mpg ppg fg% To/min FG% Rat Fact %sht %3sht %fld %to %
> pass /48 Poss
> 92-93 38.6 18.6 47.3 .079 .482 .513 1.36 31
> 2 7 6 56 9.5 .354
> 93-94 38.3 22.0 49.1 .084 .515 .594 1.38 34
> 5 9 6 51 10.9 .417
>
> > i like many others was expecting pippen to improve much more
than
> >he did
>
> '93 was a bad year for Pippen. In '92 he had approached
> superstardom, and struggled the year after. His shooting % was the
> lowest of any year between his rookie season and last season.
>
> ... the bulls were 57-25 in 92-93 yet only 2 games worse in 93-94
at
> 55-27 without jordan. how is this possible? well in 92-93 they
> outscored their opponents by 6.3 pts/g but just 3.1 pts/g in 93-95,
> so their W-L record of 55-27 was probably a few to a number of
games
> better than their stats would indicate...
>
> This is pretty radical. Does anyone know what team ppg
differential
> typically produces in terms of W-L record? My guess is 6.3 ppg and
> 57-25 is closer to normal, like Bob says, than 3.1 ppg and 55-27 is.
>
>
> >Larry Johnson eff Prod
> >Poss reb Pts
> mpg ppg fg% To/min FG% Rat Fact %sht %3sht %fld %
> to %pass /48 Poss
> 95-96 40.4 20.5 47.6 .056 .503 .508 1.17 32
5
> 13 5 50 10.0 .435
> 96-97 34.4 12.8 51.2 .052 .535 .312 0.80 35
> 5 11 6 48 7.2 .466
>
> >, his shooting even better in 96-97. the biggest difference i can
> >see (other than rebounding) is he handled the ball over 30% less
in
> >NY
>
> Assists were also way down in the NY system. This surprised me,
> since he replaced Mason, another passing forward.
>
> Total shooting pct went from .551 to .560.
>
>
> Mike G
• ... at ... games ... differential ... The 3.1 and 55 wins is the fluke, should be more like 50. A good rule of thumb is to multiply the point differential by
Message 2 of 5 , Oct 10 5:43 PM
> ... the bulls were 57-25 in 92-93 yet only 2 games worse in 93-94
at
> 55-27 without jordan. how is this possible? well in 92-93 they
> outscored their opponents by 6.3 pts/g but just 3.1 pts/g in 93-95,
> so their W-L record of 55-27 was probably a few to a number of
games
> better than their stats would indicate...
>
> This is pretty radical. Does anyone know what team ppg
differential
> typically produces in terms of W-L record? My guess is 6.3 ppg and
> 57-25 is closer to normal, like Bob says, than 3.1 ppg and 55-27 is.
>

The 3.1 and 55 wins is the fluke, should be more like 50. A good rule
of thumb is to multiply the point differential by about 2.8, then add
41. This doesn't work at the extremes (a +15.0 team would have 83
wins and negative one losses), but as a practical matter it's very
effective.
• ... Yup, this is what separates econometrics from most other branches of statistics: heavy reliance on theory or assumptions, to determine the resulting
Message 3 of 5 , Oct 15 4:03 AM
On Wed, 9 Oct 2002, Dean Oliver wrote:

>
> A key philosophy I've worked on is that players can only stay the
> same or get less efficient as they take on a greater load of the
> offense, given their teammates. Basically, they have to take worse

Yup, this is what separates econometrics from most other branches of
statistics: heavy reliance on theory or assumptions, to determine the
resulting statistical procedures or interpretations.

> shots or make more mistakes. This concept has to be true to some
> degree, otherwise the Bulls should have ALWAYS given the ball to
> Jordan, every single time. Players have to become less efficient as
> they take more possessions or else you'd have players like Steve
> Kerr, shooting 50% from the 3pt line, who should always shoot the
> ball.

Yes, two good concepts being used here: proof by contradiction. And the
principle of diminishing marginal returns. They HAVE to diminish.

Another example would be Artis Gilmore late in his career, when he was
shooting something like 65% from the field. Why didn't he just shoot the
ball 40 times per game? For the obvious reason that his FG% (and
efficiency) would've gone way down.

> There are players who, with a basic look at their numbers, don't
> support this. Iverson is one. His efficiency goes up with more
> possessions. Why? Because there are nights when a team tries to
> cover him 1 on 1 and he gets hot, so he goes all night killing the
> horrible defense. But such a look at offensive rating (points
> produced per 100 possessions vs possessions used) is mixing cause and
> effect. If a team were double teaming him and he kept trying to
> score, his efficiency would go down. Fundamentally, it is very hard
> to sort out cause and effect in looking at efficiency vs the load
> that players take on.

This is a good example, but is only one of the complications. It's also
an example of how we rely upon our theory or assumptions: in this case
the assumption that, all else being equal, an increase in possessions by
a player must result in a decrease in his efficiency. If we observe
some player's stats going in the opposite direction, such as Iverson, we
resort to explanations such as DeanO's.

A good procedure, but only as long as the theory or assumptions are good.
In this case, the assumption of diminishing marginal returns is a good
one.

But there are yet other complications which make estimating the
context, there's the teammate context: what sort of teammates does the
player have, how good are they, do their skills complement each other
(Shaq & Kobe) or compete with each other (Bellamy & Willis Reed, Wilt &
Thurmond -- there was no point in having both of those players on one
team, the team was better off trading one of them away). During a season,
most of the teammates remain constant at least so we can try to use
individual game data to explore the relationship between possessions and
efficiency.

But then there's yet another complication, especially when we're looking
at a player's career across time: the quality of the player almost
certainly varies. Most players improve, plateau, and then decline. So
their possession/efficiency tradeoff is going to be varying over time.

It's like trying to estimate the relationship between how fast you drive
and what kind of gas mileage you get: but some days your car is a Ford
Excursion and some days it's a Ford Fiesta or whatever they call those
little cars. Fortunately career swings aren't completely random, there's
some regularity and stability to them.

--MKT
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