I noticed that Gadzuric has a very high PF/MIN (7.1PF/48min), and
I'm curious:

A. How many minutes per game can he average?
B. Can he lower that rate & by how much?

To do some a quick (and nowhere near complete) study, I looked at
high PF/MIN last year, and the highest MIN/G they had over their
career:

8.7PF/48 - J. James highest MIN/G - 16.9
8.6 - A. DeClercq - 25.6
8.2 - R. Traylor - 17.3
7.8 - A. Pavlovic - 14.5
7.7 - Voskuhl - 24.3
7.5 - C. Mihm - 22.4
7.1 - J. Collins - 21.4
6.7 - M. Madsen - 17.3
6.6 - M. Doleac - 18.2

And for the high minute guys - during the year they had their
highest MIN/G what was their PF/48 that year?

DeClercq - 6.1 PF/48 (lower)
Voskuhl  same
C. Mihm 7.5 PF/48 (higher)
J. Collins same
Doleac 8.1 PF/48

Declerq had a low foul year, but otherwise it might appear that
Gadzuric is limited to 21-25 M/G. (otherwise it's a real low sample
size.)

Anyone else do a study on this?

Thanks!

-----Original Message-----
From: sultanoswat@... [mailto:sultanoswat@...]
Sent: Monday, November 01, 2004 9:05 PM

>I noticed that Gadzuric has a very high PF/MIN (7.1PF/48min), and
>I'm curious:
>
>A. How many minutes per game can he average?
>B. Can he lower that rate & by how much?
>
>To do some a quick (and nowhere near complete) study, I looked at
>high PF/MIN last year, and the highest MIN/G they had over their
              ^^^^
>career:

If you want to come up with some sort of prediction for Gadzuric, then
instead of looking at players with high PF/min THIS year, you want to
look at players from PAST years who had high PF/min, and who were similar
in some way to Gadzuric (young centers with similar stats) -- and then
look to see what subsequently happened to their PF/min and Min/G stats.

Many of the players on your list are either players who are new, so
we don't know how their career Min/G will play out (Mihm), or they
are old players who may not be comparable to Gadzuric (Traylor,
although for all I know maybe he is comparable).

My guess is that the majority of these high PF/Min players never do
become big-minutes players.  There are undoubtedly some exceptions,
ones who became either better players or learned to reduce their
foulling or most likely both.  How to decide whether a player such
as Gadzuric is in that category or not is I suspect not an easy task.
Anyone who can make the prediction reliably should get hired as an
assistant GM or player personnel director.


--MKT

--- In APBR_analysis@yahoogroups.com, sultanoswat@y... wrote:
>
> I noticed that Gadzuric has a very high PF/MIN (7.1PF/48min), and
> I'm curious:
>
> A. How many minutes per game can he average?
> B. Can he lower that rate & by how much?

The players in this list are all rebounders and/or shotblockers,
except for Pavlovic (not sure what he's supposed to do; listed as SF)

[Doleac doesn't seem to belong here.  One of us has an error in
their data.]

Other than Gadzuric and Traylor, I'm not sure why you'd want these
guys to cut down on their fouls.  It looks like a major component of
their job description.

I guess I still believe in the "good foul".  Aside of hacking Shaq,
there are many instances when you would prefer to put a player at
the line; if only to make him think twice about trying that again.

But most fouls are "good" only in the sense that they come with the
territory.  Going after rebounds entails lots of contact, and you
will get called for some.  If your objective is to stay in the game
(not get fouls), you might not get many rebounds (or blocks).

>
> To do some a quick (and nowhere near complete) study, I looked at
> high PF/MIN last year, and the highest MIN/G they had over their
> career:
>
> 8.7PF/48 - J. James highest MIN/G - 16.9
> 8.6 - A. DeClercq - 25.6
> 8.2 - R. Traylor - 17.3
> 7.8 - A. Pavlovic - 14.5
> 7.7 - Voskuhl - 24.3
> 7.5 - C. Mihm - 22.4
> 7.1 - J. Collins - 21.4
> 6.7 - M. Madsen - 17.3
> 6.6 - M. Doleac - 18.2

It looks like you took guys with 900+ minutes.  But also in that
range are Ervin Johnson, Olowokandi; if you allow 800 minute guys,
you get Jahidi White, Othella Harrington, Elden Campbell.  These
players have been around the block.  They know what their job is.

Looking at younger players, I suppose, means you are looking for a
bigger future for them.  But unless they learn some real skills,
what's the point of going for more minutes?

Several I've mentioned and at least one (Traylor) you've listed are
seriously overweight.  That and getting old will make one slow.
Being slow means you aren't ahead of your man, but are always trying
to catch up to him ( = Foul ).

So, in short, Gadzuric is the one guy who's young and got skills and
isn't fat (or is he?), among those we've mentioned.  Stamina is also
a factor; maybe he's a smoker.  Or lazy.

>
> And for the high minute guys - during the year they had their
> highest MIN/G what was their PF/48 that year?
>
> DeClercq - 6.1 PF/48 (lower)
> Voskuhl  same
> C. Mihm 7.5 PF/48 (higher)
> J. Collins same
> Doleac 8.1 PF/48
>
> Declerq had a low foul year, but otherwise it might appear that
> Gadzuric is limited to 21-25 M/G. (otherwise it's a real low
sample
> size.)
>
> Anyone else do a study on this?
>
> Thanks!

ivan ivan wrote:
> this is a simple question
> but i can't find it anywhere....
>
>
> I'm doing analysis on how a history of winning or losing affects your
> chances of winning at the end of close games... so does anyone know
> where i can standings for the 2001-2002 NBA season?
> i want the home and away records?
>

http://www.shrpsports.com/nba/stand/2002.htm

--
ed

I have to wonder how much of a factor teammates are as well. If you
pair Gadzuric with a big burly power forward, maybe he can avoid
matchups that require him to foul incessantly. But pair him with Joe
Smith or Toni Kukoc and you've got a problem.

In the "I wish ..." category, it'd help answer our question if the
NBA differentiated among types of fouls, especially between over the
back offensive rebound fouls, stupid 30-foot-from-the-basket fouls,
and cracking a guy in the skull to save a layup fouls.


> So, in short, Gadzuric is the one guy who's young and got skills
and
> isn't fat (or is he?), among those we've mentioned.  Stamina is
also
> a factor; maybe he's a smoker.  Or lazy.
>
>

I'm interested to see what the different approaches are to predicting
regular season winning percentage. Anyone care to predict a team or
all the teams, and share their methodology?

I'm not a gambler, but it would be interesting to see if statistical
analysis produces significantly different predictions than the
bookies. For example the over/under on the Jazz is 45 games and I'm
convinced they'll win at least 50 based on the PER-differentials of
their starters.

> I'm interested to see what the different approaches are to
predicting
> regular season winning percentage. Anyone care to predict a team or
> all the teams, and share their methodology?

OK, here goes. I took the PER of each player from the previous season
and made adjustments for his individual defense until the sum of (PER
x minute) for each team approximated their expected wins for the
season. Then I put the players on their new teams, rated the top nine
guys on each roster (making subjective adjustments for second-year
improvement, age, flukes, injuries, etc.), estimated the
effectiveness of the rookies, and summed up the results for each team.

What I got was:

EAST
Indiana      55 27
Detroit      52 30
Washington   47 35
Miami        44 38
Milwaukee    43 39
New York     41 41
Cleveland    40 42
Philadelphia 38 44

Toronto      38 44
Boston       37 45
Chicago      30 52
Orlando      30 52
New Jersey   27 55
Charlotte    25 57
Atlanta      22 60


WEST
San Antonio  59 23
Dallas       56 26
Memphis      51 31
Denver       50 32
Minnesota    48 34
Houston      48 34
Utah         47 35
Sacramento   45 37

L.A. Lakers  41 41
New Orleans  39 43
Phoenix      37 45
Golden State 37 45
Portland     35 47
Seattle      34 48
LA Clippers  33 49

--- In APBR_analysis@yahoogroups.com, "mrintp2000" <shzys@n...> wrote:
>
> I'm interested to see what the different approaches are to
predicting
> regular season winning percentage. Anyone care to predict a team or
> all the teams, and share their methodology?
>.

> I'm interested to see what the different approaches are to
predicting
> regular season winning percentage. Anyone care to predict a team or
> all the teams, and share their methodology?

OK, here goes. I took the PER of each player from the previous season
and made adjustments for his individual defense until the sum of (PER
x minute) for each team approximated their expected wins for the
season. Then I put the players on their new teams, rated the top nine
guys on each roster (making subjective adjustments for second-year
improvement, age, flukes, injuries, etc.), estimated the
effectiveness of the rookies, and summed up the results for each team.

What I got was:

EAST                 
Indiana      55      27
Detroit      52      30
Washington   47      35
Miami        44      38
Milwaukee    43      39
New York     41      41
Cleveland    40      42
Philadelphia 38      44

Toronto      38      44
Boston       37      45
Chicago      30      52
Orlando      30      52
New Jersey   27      55
Charlotte    25      57
Atlanta      22      60


WEST
San Antonio  59      23
Dallas       56      26
Memphis      51      31
Denver       50      32
Minnesota    48      34
Houston      48      34
Utah         47      35
Sacramento   45      37

L.A. Lakers  41      41
New Orleans  39      43
Phoenix      37      45
Golden State 37      45
Portland     35      47
Seattle      34      48
LA Clippers  33      49

--- In APBR_analysis@yahoogroups.com, "mrintp2000" <shzys@n...> wrote:
>
> I'm interested to see what the different approaches are to
predicting
> regular season winning percentage. Anyone care to predict a team or
> all the teams, and share their methodology?
>.

Minnesota surprised me too. Age of Cassell and Spre is a big issue,
and they had 56 expected wins compared to 58 real wins.

For Washington, having Jamison replace Hayes/Jeffries at small
forwards is worth at least 10 wins alone. Having Arenas and Hughes
for a full year (theoretically) and the huge number of second and
third year players on the roster make them likely to pull off a major
gain in wins.


--- In APBR_analysis@yahoogroups.com, Coach McCormick
<highfivehoopschool@y...> wrote:
> Looks good. However, why did Minnesota drop precipitously? And, how
did Washington get so high?
>
> There are a few that I think will change (Philly will be higher,
LAL will make the play-offs, Phoenix a couple more wins), but it is
definitely an intereting way to gamble....
>
> B
>
> John Hollinger <alleyoop2@y...> wrote:
>
> > I'm interested to see what the different approaches are to
> predicting
> > regular season winning percentage. Anyone care to predict a team
or
> > all the teams, and share their methodology?
>
> OK, here goes. I took the PER of each player from the previous
season
> and made adjustments for his individual defense until the sum of
(PER
> x minute) for each team approximated their expected wins for the
> season. Then I put the players on their new teams, rated the top
nine
> guys on each roster (making subjective adjustments for second-year
> improvement, age, flukes, injuries, etc.), estimated the
> effectiveness of the rookies, and summed up the results for each
team.
>
> What I got was:
>
> EAST
> Indiana      55      27
> Detroit      52      30
> Washington   47      35
> Miami        44      38
> Milwaukee    43      39
> New York     41      41
> Cleveland    40      42
> Philadelphia 38      44
>
> Toronto      38      44
> Boston       37      45
> Chicago      30      52
> Orlando      30      52
> New Jersey   27      55
> Charlotte    25      57
> Atlanta      22      60
>
>
> WEST
> San Antonio  59      23
> Dallas       56      26
> Memphis      51      31
> Denver       50      32
> Minnesota    48      34
> Houston      48      34
> Utah         47      35
> Sacramento   45      37
>
> L.A. Lakers  41      41
> New Orleans  39      43
> Phoenix      37      45
> Golden State 37      45
> Portland     35      47
> Seattle      34      48
> LA Clippers  33      49
>
> --- In APBR_analysis@yahoogroups.com, "mrintp2000" <shzys@n...>
wrote:
> >
> > I'm interested to see what the different approaches are to
> predicting
> > regular season winning percentage. Anyone care to predict a team
or
> > all the teams, and share their methodology?
> >.
>
>
>
>
> Yahoo! Groups SponsorADVERTISEMENT
>
>
> ---------------------------------
> Yahoo! Groups Links
>
>    To visit your group on the web, go to:
> http://groups.yahoo.com/group/APBR_analysis/
>
>    To unsubscribe from this group, send an email to:
> APBR_analysis-unsubscribe@yahoogroups.com
>
>    Your use of Yahoo! Groups is subject to the Yahoo! Terms of
Service.
>
>
>
> ---------------------------------
> Do you Yahoo!?
>  Check out the new Yahoo! Front Page.  www.yahoo.com/a

Interesting approach, I think your predictions are probably closer to
the midline than what the actual records will be. I expect Atlanta and
Charlotte for example, to do much worse than 22 and 25 wins respectively.

--- In APBR_analysis@yahoogroups.com, "John Hollinger"
<alleyoop2@y...> wrote:
>
> > I'm interested to see what the different approaches are to
> predicting
> > regular season winning percentage. Anyone care to predict a team or
> > all the teams, and share their methodology?
>
> OK, here goes. I took the PER of each player from the previous season
> and made adjustments for his individual defense until the sum of (PER
> x minute) for each team approximated their expected wins for the
> season. Then I put the players on their new teams, rated the top nine
> guys on each roster (making subjective adjustments for second-year
> improvement, age, flukes, injuries, etc.), estimated the
> effectiveness of the rookies, and summed up the results for each team.
>
> What I got was:
>
> EAST
> Indiana      55 27
> Detroit      52 30
> Washington   47 35
> Miami        44 38
> Milwaukee    43 39
> New York     41 41
> Cleveland    40 42
> Philadelphia 38 44
>
> Toronto      38 44
> Boston       37 45
> Chicago      30 52
> Orlando      30 52
> New Jersey   27 55
> Charlotte    25 57
> Atlanta      22 60
>
>
> WEST
> San Antonio  59 23
> Dallas       56 26
> Memphis      51 31
> Denver       50 32
> Minnesota    48 34
> Houston      48 34
> Utah         47 35
> Sacramento   45 37
>
> L.A. Lakers  41 41
> New Orleans  39 43
> Phoenix      37 45
> Golden State 37 45
> Portland     35 47
> Seattle      34 48
> LA Clippers  33 49
>
> --- In APBR_analysis@yahoogroups.com, "mrintp2000" <shzys@n...> wrote:
> >
> > I'm interested to see what the different approaches are to
> predicting
> > regular season winning percentage. Anyone care to predict a team or
> > all the teams, and share their methodology?
> >.

I completely agree on the Wizards. Further, based on the recent
extension signed by Haywood I'm expecting he may just get the minutes
he deserves.

--- In APBR_analysis@yahoogroups.com, "John Hollinger"
<alleyoop2@y...> wrote:
>
> Minnesota surprised me too. Age of Cassell and Spre is a big issue,
> and they had 56 expected wins compared to 58 real wins.
>
> For Washington, having Jamison replace Hayes/Jeffries at small
> forwards is worth at least 10 wins alone. Having Arenas and Hughes
> for a full year (theoretically) and the huge number of second and
> third year players on the roster make them likely to pull off a major
> gain in wins.
>
>
> --- In APBR_analysis@yahoogroups.com, Coach McCormick
> <highfivehoopschool@y...> wrote:
> > Looks good. However, why did Minnesota drop precipitously? And, how
> did Washington get so high?
> >
> > There are a few that I think will change (Philly will be higher,
> LAL will make the play-offs, Phoenix a couple more wins), but it is
> definitely an intereting way to gamble....
> >
> > B
> >
> > John Hollinger <alleyoop2@y...> wrote:
> >
> > > I'm interested to see what the different approaches are to
> > predicting
> > > regular season winning percentage. Anyone care to predict a team
> or
> > > all the teams, and share their methodology?
> >
> > OK, here goes. I took the PER of each player from the previous
> season
> > and made adjustments for his individual defense until the sum of
> (PER
> > x minute) for each team approximated their expected wins for the
> > season. Then I put the players on their new teams, rated the top
> nine
> > guys on each roster (making subjective adjustments for second-year
> > improvement, age, flukes, injuries, etc.), estimated the
> > effectiveness of the rookies, and summed up the results for each
> team.
> >
> > What I got was:
> >
> > EAST
> > Indiana      55      27
> > Detroit      52      30
> > Washington   47      35
> > Miami        44      38
> > Milwaukee    43      39
> > New York     41      41
> > Cleveland    40      42
> > Philadelphia 38      44
> >
> > Toronto      38      44
> > Boston       37      45
> > Chicago      30      52
> > Orlando      30      52
> > New Jersey   27      55
> > Charlotte    25      57
> > Atlanta      22      60
> >
> >
> > WEST
> > San Antonio  59      23
> > Dallas       56      26
> > Memphis      51      31
> > Denver       50      32
> > Minnesota    48      34
> > Houston      48      34
> > Utah         47      35
> > Sacramento   45      37
> >
> > L.A. Lakers  41      41
> > New Orleans  39      43
> > Phoenix      37      45
> > Golden State 37      45
> > Portland     35      47
> > Seattle      34      48
> > LA Clippers  33      49
> >
> > --- In APBR_analysis@yahoogroups.com, "mrintp2000" <shzys@n...>
> wrote:
> > >
> > > I'm interested to see what the different approaches are to
> > predicting
> > > regular season winning percentage. Anyone care to predict a team
> or
> > > all the teams, and share their methodology?
> > >.
> >
> >
> >
> >
> > Yahoo! Groups SponsorADVERTISEMENT
> >
> >
> > ---------------------------------
> > Yahoo! Groups Links
> >
> >    To visit your group on the web, go to:
> > http://groups.yahoo.com/group/APBR_analysis/
> >
> >    To unsubscribe from this group, send an email to:
> > APBR_analysis-unsubscribe@yahoogroups.com
> >
> >    Your use of Yahoo! Groups is subject to the Yahoo! Terms of
> Service.
> >
> >
> >
> > ---------------------------------
> > Do you Yahoo!?
> >  Check out the new Yahoo! Front Page.  www.yahoo.com/a

> I'm interested to see what the different approaches are to
> predicting regular season winning percentage. Anyone care to
> predict a team or all the teams, and share their methodology?

I did something similar to John's method and posted it today:

http://www.nba.com/sonics/news/nbapreview04.html

> I'm interested to see what the different approaches are to
> predicting regular season winning percentage. Anyone care to
> predict a team or all the teams, and share their methodology?

I did something similar to John's method and posted it today:

http://www.nba.com/sonics/news/nbapreview04.html

--- In APBR_analysis@yahoogroups.com, "thedawgsareout"
<kpelton08@h...> wrote:
> ... posted it today:
>
> http://www.nba.com/sonics/news/nbapreview04.html


^^ Another prediction system that doesn't expect any team to win
fewer than 22 games.

Even the Warriors are projected to 32 wins.  And the Clipps 41 !

I doubt I can do any better, though.  One thing I do believe in, is
getting rid of "leading zeroes" in your decimal fractions:
i.e.,  .488 instead of 0.488

Who needs that Zero? I know statisticians are fond of them.  It
looks like clutter to me; like any other insignificant digit.

"Ted Williams batted four-hundred" sounds better than "Ted Williams
batted oh-four-hundred".

In Excel: Cell Format/ Number/ at the bottom of the list is Custom.
Just enter ".000" (no parentheses), and your columns come up that
way.

What's the Real reason you didn't include the Sonics ?

OK, for the curious:  I've tabulated John's and Kevin's predictions
and ranked them by the size of the teams' difference in the two
lists.

John H gives the Bulls 8 more wins than Kevin P does, so they head
the list.  Kevin gives the Clippers and Magics 8 more wins than John
does, and they're at the bottom.

[I guess some people just have to believe in Magic.]

Sonics' "wins" by Kevin are inserted by deduction.

KP Tm. JH
22 Chi 30
49 Dal 56
45 Den 50
32 GSW 37
43 Was 47
55 SAS 59
49 Det 52
37 Cle 40
36 NO 39
42 Mia 44
46 Min 48
49 Mem 51
47 Hou 48
37 Phl 38
41 LAL 41
41 NYK 41
27 NJN 27
56 Ind 55
44 Mil 43
36 Sea 35
24 Atl 22
38 Por 35
40 Phe 37
51 Uta 47
42 Tor 38
41 Bos 37
30 Cha 25
51 Sac 45
38 Orl 30
41 LAC 33

I don't suppose there are common factors shared by teams at the top
or bottom of this listing.  If there are, they might indicate what
factors play heavily in these 2 guys' systems.

The "subjective" factor is the most daunting to myself.  I don't
read much background or watch them play very often.



--- In APBR_analysis@yahoogroups.com, "John Hollinger"
<alleyoop2@y...> wrote:
> ..I took the PER of each player from the previous season
> and made adjustments for his individual defense until the sum of
(PER
> x minute) for each team approximated their expected wins for the
> season. Then I put the players on their new teams, rated the top
nine
> guys on each roster (making subjective adjustments for second-year
> improvement, age, flukes, injuries, etc.), estimated the
> effectiveness of the rookies, and summed up the results for each
team.

> ^^ Another prediction system that doesn't expect any team to win
> fewer than 22 games.

I think that's to be expected -- fundamentally, projections have to
be pretty conservative to be accurate and place teams relatively
closer to .500 than they actually are. Injuries are usually the
reason that doesn't turn out.

> Who needs that Zero? I know statisticians are fond of them.  It
> looks like clutter to me; like any other insignificant digit.

I just put it there because it's in the NBA's actual standings and I
copied over them for the HTML.

> What's the Real reason you didn't include the Sonics ?

I think you explained that in the second post.

... is pretty much the same as the old one: the usual analytic stats, some
graphs, not too many bells and whistles. Intended solely as a handy
reference, nothing too deep. Mostly team stats, although I will add some
player stuff in a little while. Last year, I was pretty good about updating
daily, or near daily. Maybe the same thing will happen this year.

http://members.rogers.com/edkupfer/nba/nba_2005.htm

Ignore the stats that are there now. They are, I think, preseason numbers,
or whatever Doug has on his page right now.

--

ed
"I ain't the world's best writer, ain't the world's best speller
But when I believe in something I'm the loudest yeller."
     - Woody Guthrie

-----Original Message-----
From: thedawgsareout [mailto:kpelton08@...]
Sent: Wednesday, November 03, 2004 8:09 AM

>> ^^ Another prediction system that doesn't expect any team to win
>> fewer than 22 games.
>
>I think that's to be expected -- fundamentally, projections have to
>be pretty conservative to be accurate and place teams relatively
>closer to .500 than they actually are. Injuries are usually the
>reason that doesn't turn out.

Yup, it is often a good idea to "shrink" or "regress" forecasts
and estimates towards the mean.  Even if this results in biased
estimates, they may nonetheless have lower expected error.  A
canonical example is batting averages early in the season; after
a week or two, the leaderboard will have some guy hitting .456.
Standard simple statistics would say that that represents a sample
of his hitting and we should estimate his eventual batting average
by using his sample mean, i.e. .456.  Common sense, as well as
more sophisticated "shrinkage to the mean" statistics, tell us that
by the end of the season, he'll be batting something well under
.456.

The best easy-to-read article that I've seen explaining this phenomenon
is by the statistician Bradley Efron, in a 1977 _Scientific
American_ article, "Stein's Paradox in Statistics".

>> Who needs that Zero? I know statisticians are fond of them.  It
>> looks like clutter to me; like any other insignificant digit.
>
>I just put it there because it's in the NBA's actual standings and I
>copied over them for the HTML.

Depends on the circumstance.  Leading 0s can be highly valuable
at improving readability, and also reducing reader error.  If you're
looking at a column of numbers such as

56
.81
4.2

it may not be instantly obvious that one of those numbers is much
smaller than the others. There are some circumstance where the
extra 0 is unnecessary or unhelpful, but there are other circumstances
where, just like adding commas (e.g. try reading 1648756 vs 1,648,756),
they vastly improve readability.



--MKT

With apologies to ed for hijacking his thread, I just found a neat
new function which I've never seen mentioned here.

This site -- http://www.popcornmachine.net/GameFlows.html -- has
Game Flows for each game showing the lineup combinations each team
had in the game at all times and approximately how they performed.
If you want to get a feel for a team's rotation, this seems like the
next best thing to watching a game.

A nice piece by DeanO on 82games.com http://www.82games.com/comm54.htm .

I was especially intrigued by this remark "Part of this is definitely
expansion. In years where the NBA has added two expansion teams,
individuality has gone up league-wide (it didn't go up with the single
addition of Dallas in 1980-81). It would make sense for offenses to
cluster a bit more around top individuals if their support is suddenly
downgraded, even if it is a small downgrade.". It seems to suggest
that the dilution of the talent pool through expansion may be a bigger
factor than we usually think.
I was also interested in this "Slowing the game, which has been a
steady trend for more than 25 years, may also have something to do
with individuality, though cause and effect are not clear." A way to
check this relationship would be to see if slower teams played more
individual basketball than their peers.

Carlos

Has  it  ever  happened in expansion history for the team in its first ever
game  to have a better FG%, more rebounds (off and def) and still manage to
lose the game?
They were awful from the stripe and in the TO department, but has that ever
happened??

hi guys,

I have some questions came across:

Who's the first international player to play in the NBA?

Who's the first international player to win a NBA championship?

Which international player has the longest NBA tenure?

thank you very much!

yours,
Shawn

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Last night Richard Jefferson put up the following stat line:

min FGM/A Threes Reb Ast tos stl blcks pf pts
57   9/23   1/3  21   9  11   3    1    2  26

How does this score on people's rating systems.  To what extent does
the poor shooting and tos eat away at his scoring/boarding?

--- In APBR_analysis@yahoogroups.com, "harlanzo" <harlanzo@y...>
wrote:
>
> Last night Richard Jefferson put up the following stat line:
>
> min FGM/A Threes Reb Ast tos stl blcks pf pts
> 57   9/23   1/3  21   9  11   3    1    2  26
>
> How does this score on people's rating systems.  To what extent
does
> the poor shooting and tos eat away at his scoring/boarding?

At first glance, it doesn't look like that big a deal to score 26
pts in 57 minutes.  But the fact he stayed in the game that long is
impressive, as are the rebounds.

If there were 100+ rebounds in the game, I'd be less impressed; but
in fact it was 50-46 in favor of NJ.

Under his line in my file from last season, I've created an "RJ2"
line based only on this one game.  Here's how they compare:

-- min eff% Sco. Reb Ast P.F Stl T.O Blk - Total
RJ1 38 .571 17.9 5.3 3.5 2.7 1.1 2.4 0.3 - 26.4
RJ2 57 .497 17.4 15. 6.1 1.5 2.2 8.0 0.7 - 34.1

A good game by any standards; just not as good as some 26-21-9
nights.

He was 7-7 from the FT line, so that moderates his eff% somewhat

along those lines, what's the record for most TOs by a
team in a single game? i would think it's around 44 or
so.


--- bchaikin@... wrote:

> Last night Richard Jefferson put up the following
> stat line:
>
> min FGM/A Threes Reb Ast tos stl blcks pf  pts
> 57   9/23   1/3  21   9   11   3    1    2  26
>
> How  does this score on people's rating systems.  To
> what extent does he poor
>  shooting and tos eat away at his scoring/boarding?
>
> if i'm reading that right - that's eleven
> turnovers?? if that's the case
> then there is nothing in that stat line makes up for
> 11 turnovers...
>
> imagine if he was one of 4 players on the same team
> to score 26  points.
> that'd be 100+ points. but if each had 11 turnovers
> that'd be 44  turnovers. can
> you think of the last time a team won a game with
> anywhere near  that many
> turnovers?...
>
> bob chaikin
> _bchaikin@..._
> (mailto:bchaikin@...)
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>


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I mistakenly posted the wrong line for Jefferson of '04; here is the
relevant line of comparison with his near-quad-double night:

-- min eff% Sco. Reb Ast P.F Stl T.O Blk - Total
RJ1 38 .571 21.6 6.0 4.2 2.7 1.1 2.4 0.3 - 31.8
RJ2 57 .497 17.4 15. 6.1 1.5 2.2 8.0 0.7 - 34.1

..the 2nd line being his 57-minute effort last night.


--- In APBR_analysis@yahoogroups.com, bchaikin@a... wrote:
>
> if i'm reading that right - that's eleven turnovers?? if that's
the case
> then there is nothing in that stat line makes up for 11
turnovers...

Well, 21 rebounds in a game that is 50-46 for his team, in that
category, does a lot of good.

>
> imagine if he was one of 4 players on the same team to score 26
points.
> that'd be 100+ points. but if each had 11 turnovers that'd be 44
turnovers. can
> you think of the last time a team won a game with anywhere near
that many
> turnovers?...

Wilt Chamberlain would have been having a typical game, to go 26-21-
9, around '67 or '68.  And we don't know about turnovers, "back
then".

What if the 4 players in your example got 84 boards to the
opponents' total of 46?  How many teams don't win with that kind of
rebounding advantage ?

The fact the player had 11 TO and his team DID win says that one
player with that stat line can contribute to a winning effort.  His
coach didn't take him out much.