- --- In APBR_analysis@y..., "danthestatman2002" <danthestatman@h...>

wrote:>

performance

> Thanks Mike....

>

> I'm not new to this - I've been attempting to find player

> values since I was quite young (like 11 - I'm 31 now). Of course -

available

> like many - I did this in baseball, thanks to Bill James. I've

> turned to basketball and most recently football because, honestly,

> there isn't that much decent statistical analysis out there

> to the public. There is a TON for baseball.

Funny, I started with football back in the mid 70's. When I saw

James' stuff on baseball in '84, I was impressed with how well it all

linked together. I realized pretty quickly that basketball had a

nice structure as well. Football was waaay too hard (though I have

since mentioned a structure I like to both Pete Palmer and Sean

Lahman and they both have data to do what I want to do). In '87, I

scored my first basketball game and that led me down the apparently

demonic path of points per possession (though it's actually been

around 50 years in the coaching profession, as Dean Smith did it at

UNC) and away from linear weights.

>

There are definite limitations in the #'s, especially prior to 1978

> So, I work on my stuff - and ALWAYS assume I can make it a little

> better at indicating player value in any given season - given the

> limitations of the stats we have to draw from.

and the advent of individual turnovers. I see hugely varying

turnover rates among individuals who play the same position. And

those really make a big difference in how effective they appear to

be. Nate Archibald's turnover rate didn't appear to be a stable

thing and probably varied. He obviously played well, scored a lot of

points, but if he was turning the ball over a ton, that would explain

partially why his team didn't win. MJ was so great in part because

he didn't turn the ball over while using a ton of possessions

(something MikeG has also pointed out, using a comparison

with "expected" turnovers as he defined it). I do have a few tricks

up my sleeve for estimating turnovers from way back when, but the

uncertainty is pretty big.

Regardless, making changes in methodology based upon players pre-1978

is risky. Just too much uncertainty in what the non-measured stats

were.

DeanO - Personally, I found single-number rating extremely handy for the

studies in the book. In particular, the Detroit study (searching for

fluke years) and the Indiana study (comparing playoff performance)

would have been close to impossible without the numerical comparison.

--- In APBR_analysis@y..., "Dean Oliver" <deano@r...> wrote:

> --- In APBR_analysis@y..., "Mike G" <msg_53@h...> wrote:

>

> > > > Realizing that their own system was not passing the laugh

test

> > > ... started taking logarithms of the financial variables before

> > > calculating z-scores,...

> >

> > A logarithm isn't exactly a root is it? The math part of my

brain

> > was destroyed in an experiment. I know a log and a root are both

> > parts of a tree...

> >

>

> A log is different. The log of 10 is 1. The log of 100 is 2. The

> log of 1000 is 3. (All base 10 log).

>

> >

> > > I read US News' rankings of schools and I read MikeG's rankings

> of

> > > players. They are entertaining and they are good for some

> > > trashtalking ...

> >

> > Well, you have the option of talking at the trash level. In the

> end,

> > we may be working together toward something pretty sound.

> >

>

> How can we know what is sound? What objective measure will we use

to

> say that this linear weights method is "pretty sound"? Is it, as

> Kevin P said, just making sure that Shaq is #1 among today's

players?

>

> > I like some of what danthestatman has done. Some of it is

> identical

>

> I guess the question is Why would you use something he has done?

Do

> you like "some" of what he's done only so far as it's the same as

> what you've done? Why don't people just use JohnH's weights? Or

> Doug Steele's weights? What have people learned by looking at

other

> people's weights? Why does anyone adopt other people's ratings?

>

> > Finally, I think single-number player-ranking is pretty handy

when

> > looking at the course of a players's career. Whether or not his

> > scoring is inflated (for example), you can still see how his

> playoffs

> > fared relative to his season, or how one season compares to

another.

>

> Bill James listed a few times when single ratings are handy. I

don't

> recall what they were, other than basic trade analysis and first

cut

> analysis of player evaluation. Anyone else remember?

>

> DeanO - --- In APBR_analysis@y..., "John Hollinger" <alleyoop2@y...> wrote:
> Personally, I found single-number rating extremely handy for the

for

> studies in the book. In particular, the Detroit study (searching

> fluke years) and the Indiana study (comparing playoff performance)

comparison.

> would have been close to impossible without the numerical

I guess I always use individual offensive and defensive ratings, as

well as a player's percentage of the team offense. (%age of team

defense is harder to estimate, so I don't use that).

As a screen, one number gives you a sense and you can do stats on

it. I guess I like to know reasons. How can you change and predict

it? The stats from one number can help make predictions (sometimes

better than with multiple #'s because you don't rationalize a

number), but it doesn't help you _change_ anything, which is how I

like to use my stuff.

Didn't get an answer, though, to how people use each other's weights

or what they've learned from them.

DeanO

>

before

>

>

> --- In APBR_analysis@y..., "Dean Oliver" <deano@r...> wrote:

> > --- In APBR_analysis@y..., "Mike G" <msg_53@h...> wrote:

> >

> > > > > Realizing that their own system was not passing the laugh

> test

> > > > ... started taking logarithms of the financial variables

> > > > calculating z-scores,...

both

> > >

> > > A logarithm isn't exactly a root is it? The math part of my

> brain

> > > was destroyed in an experiment. I know a log and a root are

> > > parts of a tree...

The

> > >

> >

> > A log is different. The log of 10 is 1. The log of 100 is 2.

> > log of 1000 is 3. (All base 10 log).

rankings

> >

> > >

> > > > I read US News' rankings of schools and I read MikeG's

> > of

the

> > > > players. They are entertaining and they are good for some

> > > > trashtalking ...

> > >

> > > Well, you have the option of talking at the trash level. In

> > end,

use

> > > we may be working together toward something pretty sound.

> > >

> >

> > How can we know what is sound? What objective measure will we

> to

his

> > say that this linear weights method is "pretty sound"? Is it, as

> > Kevin P said, just making sure that Shaq is #1 among today's

> players?

> >

> > > I like some of what danthestatman has done. Some of it is

> > identical

> >

> > I guess the question is Why would you use something he has done?

> Do

> > you like "some" of what he's done only so far as it's the same as

> > what you've done? Why don't people just use JohnH's weights? Or

> > Doug Steele's weights? What have people learned by looking at

> other

> > people's weights? Why does anyone adopt other people's ratings?

> >

> > > Finally, I think single-number player-ranking is pretty handy

> when

> > > looking at the course of a players's career. Whether or not

> > > scoring is inflated (for example), you can still see how his

> > playoffs

> > > fared relative to his season, or how one season compares to

> another.

> >

> > Bill James listed a few times when single ratings are handy. I

> don't

> > recall what they were, other than basic trade analysis and first

> cut

> > analysis of player evaluation. Anyone else remember?

> >

> > DeanO