"Virtually no correlation between payroll and win%" - wrong

[vergogna]

finals
conference finals
conference semifinals
first round

1 L.A. Lakers 91.569.650
2 Dallas Mavericks 90.289.530
3 Orlando Magic 89.139.540
4 Boston Celtics 83.330.700
5 Utah Jazz 73.968.477
6 Houston Rockets 72.587.610
7 Atlanta Hawks 70.257.365
8 Portland Trail Blazers 70.145.633
9 Memphis Grizzlies 69.957.370
10 Philadelphia 76ers 69.361.140
11 Toronto Raptors 69.207.988
12 San Antonio Spurs 69.004.626
13 Milwaukee Bucks 68.645.120
14 New Orleans Hornets 68.371.614
15 Golden State Warriors 67.222.521
16 New York Knicks 66.576.080
17 Detroit Pistons 65.917.860
18 Denver Nuggets 65.870.870
19 Charlotte Bobcats 65.840.630
20 Miami Heat 65.837.150
21 Phoenix Suns 65.686.161
22 Indiana Pacers 64.368.430
23 New Jersey Nets 59.855.163
24 Washington Wizards 59.113.370
25 Oklahoma City Thunder 57.478.992
26 Chicago Bulls 54.905.410
27 Cleveland Cavs 53.299.990
28 Minnesota Timberwolves 53.139.750
29 L.A. Clippers 51.888.797
30 Sacramento Kings 44.050.620

[vergogna]

finalist - (2+20) - 11/30 payroll
conference finalist - (2+20+25+26) - 16/30 payroll
conference semifinals - (1+2+4+7+9+20+25+26) - 12/30 payroll
first round - (1+2+3+4+7+8+9+10+12+14+16+18+20+22+25+26) - 12/30 payroll

[shrink]

I think you are seeing that the lottery is one good way to create parity (superstars matter) after a few years. Teams that are attractive free agent destinations sometimes need to go down under the cap to sign their superstar, and hurts the correlation. However, spending over the lux seems to correlate quite highly with a spot in the play-offs.

[jambalaya]

http://www.jeremyscheff.com/2011/07/the ... d-by-team/

A .32 correlation between team salaries and wins in 2002-11 and a .54 correlation in 2010-11.


About 2/3rds of all the conference finalists in the last 6 seasons were teams who spent in the top 30% across that 6 season time period. All the champs were in this group.

[EvanZ]

That correlation for 2011 equates to R^2=0.29.

Well, I guess I was off by 1% due to using the "incorrect" data. This...changes...everything.

[Wizenheimer]

Andrew Zimablist biographical info: "serves as consultant ....to the National Basketball Players’ Association in collective bargaining"

http://www.smith.edu/economics/faculty_zimbalist.php

LOL...and here is the most critical 'data'

[LakerLegend]

LMAO at him using the Heat and Knicks as examples that there IS competative balance. It's not just about money...it's about market attractiveness. Orlando vs Detroit for example.

[jambalaya]

"by EvanZ on Wed Oct 12, 2011 5:46 pm
That correlation for 2011 equates to R^2=0.29.

Well, I guess I was off by 1% due to using the "incorrect" data. This...changes...everything. "


Ha.

Of course it is good to correct the things that can be corrected.

There was a salary database problem in this article 2 years ago.
http://hawkonomics.blogspot.com/2009/04 ... -2008.html
Somebody else (Phil Birnbaum) caught it. But in that case it did fairly substantially affect the conclusion.

Not a really simple issue fully answered by one simple measure. Plenty of complexity to consider and analyze, if one has the time and skill.

[Wizenheimer]

finalist - (2+20) - 11/30 payroll
conference finalist - (2+20+25+26) - 16/30 payroll
conference semifinals - (1+2+4+7+9+20+25+26) - 12/30 payroll
first round - (1+2+3+4+7+8+9+10+12+14+16+18+20+22+25+26) - 12/30 payroll

and even those numbers are skewed

In the EC you can't use Miami as a template for anything except perhaps as something the other owners want to prevent in the future. For Chicago, both Noah & Rose are still on their rookie deals. That's will change next season as Noah's extension kicks in, and Rose's kicks in the following season

In the WC, OKC has a low salary but that will change dramatically nest season as Durant's extension kicks in. The following season it will be Westbrook's extension. Next, it will be Harden and Ibaka. Add Perkins to that high-paid foursome and the Thunder will be deep into the luxury tax

[doctorfunk]

Someone needs to tell him that the last 4 NBA championship teams spent heavily into the luxury tax. The only reason the Heat were competitive this year is because they signed LeBron, Bosh and Wade at below market value. Under the old CBA, the Heat almost certainly would have become a tax team, likely starting this season through use of the MLE.

as simple as it sounds this is basically it
just look at budget of last 10 champions, probably only spurs were close to NBA average, rest was WAY WAY above it.

[EvanZ]

You may not have to pay to get to the top. But you definitely have to pay to stay at the top.

[HartfordWhalers]

LMAO at him using the Heat and Knicks as examples that there IS competative balance. It's not just about money...it's about market attractiveness. Orlando vs Detroit for example.

It is way worse then that. The Heat, that small market team, had a payroll over 10 million above the salary cap when they won it. Considering the actual correlation being discussed was money spent and not market size, this example sucks when the exception to the rule that you need to spend to win it all is within a few hundred thousand of the luxury tax.

Everything I have seen shows a correlation, typically in that .2-.3 range between straight money spent and team winning percentage. I'm guessing if you want that correlation gone, it can be easily done by controlling for last seasons success. In effect running the correlation of change in money spent on change in winning percentage, that way you capture enough teams paying players after success, as you do teams getting a new (successful) free agent.

And and for slightly off topic rants:

LOL at telling the professional statistician that theyre wrong. NBA player sided fans have been saying this for months. Small market fans constantly turning a blind eye to facts.

He's not a professional statistician. He's an economics professor. I'm an engineering professor. Does he have more right to use statistics than I do?

Yes. This is a rule that every economics professor knows. Lets face it, your ill equipped to conceptualize the data in the appropriate situation.
First, your using Pwins which might sound nice as a noise reducing effect but has the effect of making your correlation between how many wins a team should have (although this would take some convincing), versus the more immediate how many the actually have. Second, as previously noted you cannot use next season's payroll, that would be explaining Cleveland's 2010 run with Boobie and without Lebron.

Andrew Zimablist biographical info: "serves as consultant ....to the National Basketball Players’ Association in collective bargaining"

http://www.smith.edu/economics/faculty_zimbalist.php

See, that man knows how to conceptualize.

[shawngoat23]

This conclusion is laughably false. He shows no statistics whatsoever to back up his conclusion, but since he's a self-described expert, some of the drones on RealGM will parrot his "result" despite clear evidence to the contrary.

The plot that EvanZ showed says it all. There are many people on these forums who are very comfortable with statistical analysis. There are a few exceptions, but there is a strong correlation between payroll and win percentage, and the statistics bear that out.

Since people are complaining that these data are only for last season, I will write a script to grab the data for all seasons from 1999-2011 (last CBA). I will use salary data from Basketball Reference, which I believe only shows the payroll for the final roster (i.e., Pau Gasol would count towards the 2007-08 Lakers, but Kwame Brown would not).

[Don Draper]

This conclusion is laughably false. He shows no statistics whatsoever to back up his conclusion, but since he's a self-described expert, some of the drones on RealGM will parrot his "result" despite clear evidence to the contrary.

The plot that EvanZ showed says it all. There are many people on these forums who are very comfortable with statistical analysis. There are a few exceptions, but there is a strong correlation between payroll and win percentage, and the statistics bear that out.

Since people are complaining that these data are only for last season, I will write a script to grab the data for all seasons from 1999-2011 (last CBA). I will use salary data from Basketball Reference, which I believe only shows the payroll for the final roster (i.e., Pau Gasol would count towards the 2007-08 Lakers, but Kwame Brown would not).

There are countless other examples.

[Wizenheimer]

This conclusion is laughably false. He shows no statistics whatsoever to back up his conclusion, but since he's a self-described expert, some of the drones on RealGM will parrot his "result" despite clear evidence to the contrary.

The plot that EvanZ showed says it all. There are many people on these forums who are very comfortable with statistical analysis. There are a few exceptions, but there is a strong correlation between payroll and win percentage, and the statistics bear that out.

Since people are complaining that these data are only for last season, I will write a script to grab the data for all seasons from 1999-2011 (last CBA). I will use salary data from Basketball Reference, which I believe only shows the payroll for the final roster (i.e., Pau Gasol would count towards the 2007-08 Lakers, but Kwame Brown would not).

There are countless other examples.

why don't you just count a couple that aren't simply anecdotal assertions from union reps

[shawngoat23]

Here's the data which I was able to pull off Basketball-Reference using some scripts. I'm going to crunch it later.

I think one thing to watch out for is that the 1999 season was lockout shortened, so Win% or SRS is a better measurement of team success than Wins alone. Also, league-averaged salaries vary from year-to-year, so either you'll have to normalize for salary within a year, or you'll have to compare each season separately. I don't have access to the statistical analysis software I like at the moment, but I'm sure the data will show a strong correlation between payroll and win%.

Code: Select all

Team Year Salary W-L Win% SRS
ATL 1999 40954940 31-19 0.62 2.82
BOS 1999 32258856 19-31 0.38 -1.75
CHH 1999 29914500 26-24 0.52 0.63
CHI 1999 28640500 13-37 0.26 -8.58
CLE 1999 27778000 22-28 0.44 -0.94
DAL 1999 35565568 19-31 0.38 -2.50
DEN 1999 29392200 14-36 0.28 -6.67
DET 1999 34699620 29-21 0.58 3.97
GSW 1999 30985000 21-29 0.42 -2.63
HOU 1999 30297100 31-19 0.62 1.39
IND 1999 45401500 33-17 0.66 3.86
LAC 1999 28417580 9-41 0.18 -8.94
LAL 1999 41872000 31-19 0.62 2.67
MIA 1999 42844000 33-17 0.66 5.11
MIL 1999 33703240 28-22 0.56 1.66
MIN 1999 32331480 25-25 0.5 -0.17
NJN 1999 43735000 16-34 0.32 -3.20
NYK 1999 59945400 27-23 0.54 1.45
ORL 1999 46118000 33-17 0.66 3.11
PHI 1999 41509920 28-22 0.56 2.56
PHO 1999 36101500 27-23 0.54 2.15
POR 1999 54725500 35-15 0.7 5.67
SAC 1999 31692000 27-23 0.54 -0.89
SAS 1999 43681143 37-13 0.74 7.12
SEA 1999 30413082 25-25 0.5 -1.43
TOR 1999 34368500 23-27 0.46 -1.31
UTA 1999 30298560 37-13 0.74 5.54
VAN 1999 30793800 8-42 0.16 -8.94
WAS 1999 34018500 18-32 0.36 -1.75
ATL 2000 44169202 28-54 0.341463 -5.41
BOS 2000 46152875 35-47 0.426829 -1.00
CHH 2000 38619012 49-33 0.597561 2.34
CHI 2000 27032368 17-65 0.207317 -9.23
CLE 2000 46547966 32-50 0.390244 -3.64
DAL 2000 40014500 40-42 0.487805 -0.28
DEN 2000 40677095 35-47 0.426829 -1.76
DET 2000 42141801 42-40 0.512195 1.13
GSW 2000 36133518 19-63 0.231707 -7.62
HOU 2000 52269367 34-48 0.414634 -0.56
IND 2000 54988605 56-26 0.682927 4.16
LAC 2000 22489343 15-67 0.182927 -10.73
LAL 2000 55018533 67-15 0.817073 8.41
MIA 2000 52496573 52-30 0.634146 2.75
MIL 2000 44680197 42-40 0.512195 -0.05
MIN 2000 42642272 50-32 0.609756 2.67
NJN 2000 53245461 31-51 0.378049 -1.18
NYK 2000 72288001 50-32 0.609756 1.30
ORL 2000 41586801 41-41 0.5 0.43
PHI 2000 43890593 49-33 0.597561 1.02
PHO 2000 46544037 53-29 0.646341 5.24
POR 2000 73898705 59-23 0.719512 6.37
SAC 2000 40113125 44-38 0.536585 3.04
SAS 2000 42529801 53-29 0.646341 5.92
SEA 2000 38258910 45-37 0.54878 1.17
TOR 2000 34730320 45-37 0.54878 -0.46
UTA 2000 50348426 55-27 0.670732 4.52
VAN 2000 37432688 22-60 0.268293 -5.10
WAS 2000 53194441 29-53 0.353659 -3.47
ATL 2001 39297129 25-57 0.304878 -5.55
BOS 2001 51478707 36-46 0.439024 -2.40
CHH 2001 46441558 46-36 0.560976 1.45
CHI 2001 29691907 15-67 0.182927 -9.09
CLE 2001 49780549 30-52 0.365854 -4.48
DAL 2001 51445574 53-29 0.646341 4.60
DEN 2001 52189220 40-42 0.487805 -1.83
DET 2001 40475338 32-50 0.390244 -2.08
GSW 2001 42363018 17-65 0.207317 -8.11
HOU 2001 49283309 45-37 0.54878 2.71
IND 2001 55086140 41-41 0.5 -0.77
LAC 2001 29606189 31-51 0.378049 -2.23
LAL 2001 58968213 56-26 0.682927 3.74
MIA 2001 73472329 50-32 0.609756 1.73
MIL 2001 57819318 52-30 0.634146 3.13
MIN 2001 47488500 47-35 0.573171 1.81
NJN 2001 68977578 26-56 0.317073 -5.30
NYK 2001 74007738 48-34 0.585366 1.98
ORL 2001 37459860 43-39 0.52439 0.38
PHI 2001 51085458 56-26 0.682927 3.63
PHO 2001 53906347 51-31 0.621951 2.63
POR 2001 87395140 50-32 0.609756 4.52
SAC 2001 46266289 55-27 0.670732 6.07
SAS 2001 57215938 58-24 0.707317 7.92
SEA 2001 51538658 44-38 0.536585 0.55
TOR 2001 38313749 47-35 0.573171 1.69
UTA 2001 53893860 53-29 0.646341 5.00
VAN 2001 48899840 23-59 0.280488 -4.94
WAS 2001 59085969 19-63 0.231707 -6.75
ATL 2002 51525207 33-49 0.402439 -4.41
BOS 2002 47515677 49-33 0.597561 1.75
CHH 2002 49999445 44-38 0.536585 0.56
CHI 2002 42592857 21-61 0.256098 -8.52
CLE 2002 45649974 29-53 0.353659 -3.52
DAL 2002 57960080 57-25 0.695122 4.41
DEN 2002 54460475 27-55 0.329268 -5.19
DET 2002 42417677 50-32 0.609756 1.69
GSW 2002 47681152 21-61 0.256098 -4.80
HOU 2002 49168169 28-54 0.341463 -4.31
IND 2002 53398621 42-40 0.512195 -0.07
LAC 2002 33849932 39-43 0.47561 -0.09
LAL 2002 54262017 58-24 0.707317 7.14
MEM 2002 50920631 23-59 0.280488 -6.74
MIA 2002 53351186 36-46 0.439024 -1.85
MIL 2002 56224266 41-41 0.5 -0.62
MIN 2002 55093782 50-32 0.609756 3.58
NJN 2002 75193712 52-30 0.634146 3.67
NYK 2002 85993039 30-52 0.365854 -4.15
ORL 2002 45984001 44-38 0.536585 1.25
PHI 2002 58073366 43-39 0.52439 1.27
PHO 2002 56596369 36-46 0.439024 -0.30
POR 2002 84292850 49-33 0.597561 3.20
SAC 2002 54921012 61-21 0.743902 7.61
SAS 2002 45844814 58-24 0.707317 6.27
SEA 2002 45556733 45-37 0.54878 3.24
TOR 2002 52657161 42-40 0.512195 -0.71
UTA 2002 52642362 44-38 0.536585 1.20
WAS 2002 54776087 37-45 0.45122 -1.58
ATL 2003 55711549 35-47 0.426829 -3.87
BOS 2003 52548195 44-38 0.536585 -0.74
CHI 2003 44531095 30-52 0.365854 -5.30
CLE 2003 49610448 17-65 0.207317 -9.58
DAL 2003 72940316 60-22 0.731707 7.91
DEN 2003 49109209 17-65 0.207317 -7.41
DET 2003 47777888 50-32 0.609756 2.98
GSW 2003 47737715 38-44 0.463415 -0.59
HOU 2003 50181239 43-39 0.52439 1.89
IND 2003 53472323 48-34 0.585366 2.79
LAC 2003 42955777 27-55 0.329268 -3.44
LAL 2003 63151182 50-32 0.609756 2.71
MEM 2003 61009172 28-54 0.341463 -2.60
MIA 2003 57378326 25-57 0.304878 -5.13
MIL 2003 57995152 42-40 0.512195 -0.24
MIN 2003 59518801 51-31 0.621951 2.46
NJN 2003 60412919 49-33 0.597561 4.42
NOH 2003 44458882 47-35 0.573171 1.52
NYK 2003 93452379 37-45 0.45122 -1.60
ORL 2003 50435346 42-40 0.512195 -0.39
PHI 2003 64822487 48-34 0.585366 1.76
PHO 2003 55225080 44-38 0.536585 1.57
POR 2003 105595657 50-32 0.609756 2.98
SAC 2003 70416596 59-23 0.719512 6.68
SAS 2003 53182559 60-22 0.731707 5.65
SEA 2003 53167479 40-42 0.487805 0.37
TOR 2003 55408207 24-58 0.292683 -6.09
UTA 2003 50934629 47-35 0.573171 2.77
WAS 2003 46691190 37-45 0.45122 -1.47
ATL 2004 64497340 28-54 0.341463 -5.00
BOS 2004 60185915 36-46 0.439024 -1.99
CHI 2004 55489797 23-59 0.280488 -6.69
CLE 2004 46186472 35-47 0.426829 -3.07
DAL 2004 79536723 52-30 0.634146 4.86
DEN 2004 39398646 43-39 0.52439 1.65
DET 2004 53442834 54-28 0.658537 5.04
GSW 2004 53376708 37-45 0.45122 -0.07
HOU 2004 55401430 45-37 0.54878 2.28
IND 2004 58156236 61-21 0.743902 4.93
LAC 2004 39114363 28-54 0.341463 -3.74
LAL 2004 64123085 56-26 0.682927 4.35
MEM 2004 57378323 50-32 0.609756 2.95
MIA 2004 47349374 42-40 0.512195 -0.13
MIL 2004 53229826 41-41 0.5 0.42
MIN 2004 71272042 58-24 0.707317 5.86
NJN 2004 63697123 47-35 0.573171 1.88
NOH 2004 49800204 41-41 0.5 -0.72
NYK 2004 89444820 39-43 0.47561 -1.97
ORL 2004 50588419 21-61 0.256098 -7.25
PHI 2004 60411079 33-49 0.402439 -2.95
PHO 2004 66931770 29-53 0.353659 -2.94
POR 2004 82956768 41-41 0.5 -0.58
SAC 2004 68372826 55-27 0.670732 5.41
SAS 2004 46464064 57-25 0.695122 7.51
SEA 2004 52347476 37-45 0.45122 0.02
TOR 2004 63033243 33-49 0.402439 -3.42
UTA 2004 34747674 42-40 0.512195 -0.53
WAS 2004 45682902 25-57 0.304878 -6.12
ATL 2005 41059616 13-69 0.158537 -9.62
BOS 2005 64577356 45-37 0.54878 0.34
CHA 2005 23922578 18-64 0.219512 -6.16
CHI 2005 57276129 47-35 0.573171 0.65
CLE 2005 49175274 42-40 0.512195 0.27
DAL 2005 91908443 58-24 0.707317 5.85
DEN 2005 46101759 49-33 0.597561 2.22
DET 2005 54762481 54-28 0.658537 3.31
GSW 2005 54943723 34-48 0.414634 -1.74
HOU 2005 60284303 51-31 0.621951 4.26
IND 2005 66064780 44-38 0.536585 0.49
LAC 2005 45483265 37-45 0.45122 -0.47
LAL 2005 65059098 34-48 0.414634 -2.33
MEM 2005 67010830 45-37 0.54878 2.63
MIA 2005 59523529 59-23 0.719512 5.76
MIL 2005 57448246 30-52 0.365854 -3.09
MIN 2005 70123411 44-38 0.536585 1.73
NJN 2005 54983980 42-40 0.512195 -1.82
NOH 2005 56572882 18-64 0.219512 -6.30
NYK 2005 102567539 33-49 0.402439 -2.73
ORL 2005 66445249 36-46 0.439024 -2.52
PHI 2005 71951878 43-39 0.52439 -1.07
PHO 2005 44598682 62-20 0.756098 7.08
POR 2005 83671309 27-55 0.329268 -3.45
SAC 2005 61807688 50-32 0.609756 2.55
SAS 2005 47504123 59-23 0.719512 7.83
SEA 2005 53821301 52-30 0.634146 2.59
TOR 2005 61703775 33-49 0.402439 -1.81
UTA 2005 43515760 26-56 0.317073 -3.74
WAS 2005 49797050 45-37 0.54878 -0.71
ATL 2006 42944553 26-56 0.317073 -4.69
BOS 2006 56907300 33-49 0.402439 -1.59
CHA 2006 33458932 26-56 0.317073 -3.90
CHI 2006 57166530 41-41 0.5 0.51
CLE 2006 51303962 50-32 0.609756 2.17
DAL 2006 98454832 60-22 0.731707 5.96
DEN 2006 56492172 44-38 0.536585 0.36
DET 2006 59619275 64-18 0.780488 6.23
GSW 2006 57114566 34-48 0.414634 -1.11
HOU 2006 69257404 34-48 0.414634 -1.31
IND 2006 78791779 41-41 0.5 1.62
LAC 2006 51358645 47-35 0.573171 1.75
LAL 2006 72917945 45-37 0.54878 2.52
MEM 2006 67525538 49-33 0.597561 3.74
MIA 2006 60732452 52-30 0.634146 3.59
MIL 2006 63022514 40-42 0.487805 -1.07
MIN 2006 61830186 33-49 0.402439 -1.75
NJN 2006 66449350 49-33 0.597561 1.11
NOK 2006 41277617 38-44 0.463415 -2.51
NYK 2006 126631098 23-59 0.280488 -6.30
ORL 2006 75784782 36-46 0.439024 -1.26
PHI 2006 84807300 38-44 0.463415 -2.10
PHO 2006 53626924 54-28 0.658537 5.48
POR 2006 60017964 21-61 0.256098 -8.91
SAC 2006 62811975 44-38 0.536585 1.61
SAS 2006 63570274 63-19 0.768293 6.69
SEA 2006 49253379 35-47 0.426829 -2.88
TOR 2006 62411884 27-55 0.329268 -3.03
UTA 2006 57372902 41-41 0.5 -2.49
WAS 2006 54555947 42-40 0.512195 1.56
ATL 2007 48581972 30-52 0.365854 -4.86
BOS 2007 62981479 24-58 0.292683 -3.71
CHA 2007 41964046 33-49 0.402439 -3.97
CHI 2007 54754904 49-33 0.597561 4.52
CLE 2007 62992729 50-32 0.609756 3.33
DAL 2007 88531846 67-15 0.817073 7.28
DEN 2007 65517776 45-37 0.54878 1.69
DET 2007 59010951 53-29 0.646341 3.68
GSW 2007 65012368 42-40 0.512195 -0.01
HOU 2007 63837566 52-30 0.634146 5.04
IND 2007 63118965 35-47 0.426829 -2.62
LAC 2007 59181038 40-42 0.487805 -0.07
LAL 2007 77099949 42-40 0.512195 0.24
MEM 2007 61960489 22-60 0.268293 -4.44
MIA 2007 64416312 44-38 0.536585 -1.21
MIL 2007 63498518 28-54 0.341463 -4.44
MIN 2007 66820673 32-50 0.390244 -3.16
NJN 2007 64486110 41-41 0.5 -1.00
NOK 2007 53748991 39-43 0.47561 -1.20
NYK 2007 117350866 33-49 0.402439 -3.06
ORL 2007 61447108 40-42 0.487805 0.34
PHI 2007 69140163 35-47 0.426829 -3.26
PHO 2007 65841120 61-21 0.743902 7.27
POR 2007 75026386 32-50 0.390244 -3.78
SAC 2007 64296611 33-49 0.402439 -1.35
SAS 2007 65654320 58-24 0.707317 8.35
SEA 2007 56986831 31-51 0.378049 -2.45
TOR 2007 51015491 47-35 0.573171 0.61
UTA 2007 62364364 51-31 0.621951 3.06
WAS 2007 62733705 41-41 0.5 -0.80
ATL 2008 55501133 37-45 0.45122 -2.23
BOS 2008 74509455 66-16 0.804878 9.31
CHA 2008 53745468 32-50 0.390244 -4.48
CHI 2008 63084166 33-49 0.402439 -3.19
CLE 2008 82217583 45-37 0.54878 -0.53
DAL 2008 101694879 51-31 0.621951 4.70
DEN 2008 82958227 50-32 0.609756 3.74
DET 2008 65898875 59-23 0.719512 6.67
GSW 2008 62148303 48-34 0.585366 2.38
HOU 2008 69894114 55-27 0.670732 4.83
IND 2008 66260246 36-46 0.439024 -1.86
LAC 2008 64847945 23-59 0.280488 -6.56
LAL 2008 72626796 57-25 0.695122 7.34
MEM 2008 54118526 22-60 0.268293 -5.75
MIA 2008 74767603 15-67 0.182927 -8.53
MIL 2008 62571522 26-56 0.317073 -6.91
MIN 2008 69043895 22-60 0.268293 -6.25
NJN 2008 61836211 34-48 0.414634 -5.15
NOH 2008 62609991 56-26 0.682927 5.46
NYK 2008 96190114 23-59 0.280488 -6.54
ORL 2008 58165973 52-30 0.634146 4.79
PHI 2008 74038229 40-42 0.487805 0.19
PHO 2008 71323049 55-27 0.670732 5.14
POR 2008 73241335 41-41 0.5 -0.52
SAC 2008 63403225 38-44 0.463415 -1.85
SAS 2008 70048523 56-26 0.682927 5.10
SEA 2008 60861388 20-62 0.243902 -8.04
TOR 2008 66042375 41-41 0.5 2.47
UTA 2008 64959089 54-28 0.658537 6.87
WAS 2008 65278996 43-39 0.52439 -0.60
ATL 2009 68168841 47-35 0.573171 1.71
BOS 2009 79188973 62-20 0.756098 7.44
CHA 2009 62866926 35-47 0.426829 -1.19
CHI 2009 68126774 41-41 0.5 -0.16
CLE 2009 91298233 66-16 0.804878 8.68
DAL 2009 95045559 50-32 0.609756 1.68
DEN 2009 70121003 54-28 0.658537 3.13
DET 2009 71434174 39-43 0.47561 -0.36
GSW 2009 67416431 29-53 0.353659 -3.80
HOU 2009 73302272 53-29 0.646341 3.73
IND 2009 69668818 36-46 0.439024 -0.76
LAC 2009 62764206 19-63 0.231707 -8.46
LAL 2009 78245793 65-17 0.792683 7.11
MEM 2009 55958148 24-58 0.292683 -5.22
MIA 2009 70297059 43-39 0.52439 0.49
MIL 2009 71360656 34-48 0.414634 -0.87
MIN 2009 66445144 24-58 0.292683 -4.74
NJN 2009 62666523 34-48 0.414634 -2.31
NOH 2009 67530808 49-33 0.597561 1.41
NYK 2009 96643646 32-50 0.390244 -2.33
OKC 2009 68341605 23-59 0.280488 -6.03
ORL 2009 69672979 59-23 0.719512 6.49
PHI 2009 68301007 41-41 0.5 0.16
PHO 2009 76130408 46-36 0.560976 1.62
POR 2009 80260059 54-28 0.658537 5.00
SAC 2009 69204512 17-65 0.207317 -8.59
SAS 2009 68020487 54-28 0.658537 3.36
TOR 2009 73446970 33-49 0.402439 -2.53
UTA 2009 65841407 48-34 0.585366 2.31
WAS 2009 70743317 19-63 0.231707 -6.98
ATL 2010 65883642 53-29 0.646341 4.44
BOS 2010 83552174 50-32 0.609756 3.37
CHA 2010 68681758 44-38 0.536585 1.30
CHI 2010 69700359 41-41 0.5 -1.63
CLE 2010 83398534 61-21 0.743902 6.17
DAL 2010 88916075 55-27 0.670732 2.67
DEN 2010 74935538 53-29 0.646341 4.15
DET 2010 60185833 27-55 0.329268 -5.02
GSW 2010 65352372 26-56 0.317073 -3.27
HOU 2010 68914971 42-40 0.512195 -0.01
IND 2010 66733257 32-50 0.390244 -3.10
LAC 2010 61616409 29-53 0.353659 -6.01
LAL 2010 91378064 57-25 0.695122 4.78
MEM 2010 57287474 40-42 0.487805 -1.38
MIA 2010 74208013 47-35 0.573171 2.00
MIL 2010 66775602 46-36 0.560976 1.38
MIN 2010 62253360 15-67 0.182927 -9.06
NJN 2010 59366715 12-70 0.146341 -8.93
NOH 2010 70163827 37-45 0.45122 -2.27
NYK 2010 85710076 29-53 0.353659 -4.00
OKC 2010 58438646 50-32 0.609756 3.55
ORL 2010 82200916 59-23 0.719512 7.12
PHI 2010 64883448 27-55 0.329268 -3.92
PHO 2010 65288544 54-28 0.658537 4.68
POR 2010 56946258 50-32 0.609756 3.18
SAC 2010 67515718 25-57 0.304878 -4.06
SAS 2010 79338309 50-32 0.609756 5.07
TOR 2010 67822433 40-42 0.487805 -1.83
UTA 2010 71905244 53-29 0.646341 5.33
WAS 2010 73440274 26-56 0.317073 -4.72
ATL 2011 71469843 44-38 0.536585 -1.10
BOS 2011 82045867 56-26 0.682927 4.83
CHA 2011 66542696 34-48 0.414634 -4.08
CHI 2011 54538076 62-20 0.756098 6.53
CLE 2011 53990021 19-63 0.231707 -8.88
DAL 2011 85409890 57-25 0.695122 4.41
DEN 2011 68019290 50-32 0.609756 4.80
DET 2011 65517821 30-52 0.365854 -3.78
GSW 2011 68415336 36-46 0.439024 -2.00
HOU 2011 72315654 43-39 0.52439 2.37
IND 2011 65088630 37-45 0.45122 -1.38
LAC 2011 53225329 32-50 0.390244 -2.71
LAL 2011 91428140 57-25 0.695122 6.01
MEM 2011 70241344 46-36 0.560976 2.55
MIA 2011 66205855 58-24 0.707317 6.76
MIL 2011 69076690 35-47 0.426829 -1.01
MIN 2011 53461123 17-65 0.207317 -5.97
NJN 2011 58495989 24-58 0.292683 -6.28
NOH 2011 68230729 46-36 0.560976 1.28
NYK 2011 67016562 42-40 0.512195 0.48
OKC 2011 55922488 55-27 0.670732 3.81
ORL 2011 90770804 52-30 0.634146 4.92
PHI 2011 68915246 41-41 0.5 1.00
PHO 2011 65979054 40-42 0.487805 -0.46
POR 2011 74584058 48-34 0.585366 1.84
SAC 2011 45268465 24-58 0.292683 -4.80
SAS 2011 69522311 61-21 0.743902 5.86
TOR 2011 69992648 22-60 0.268293 -6.28
UTA 2011 75855296 39-43 0.47561 -1.44
WAS 2011 58324988 23-59 0.280488 -7.30


[Don Draper]

why don't you just count a couple that aren't simply anecdotal assertions from union reps

3. There is no relationship between market size and team wins.

The NBA has one team located in Salt Lake City (1.1 million people in metropolitan area) and one team located in Chicago (9.6 million people in metropolitan area). Such disparities in market size leads people to suspect that teams located in smaller markets are at a competitive disadvantage. But when we look at the average number of wins from 1999-00 to 2010-11 and the population in each metropolitan area, we fail to find a statistically significant link. In sum, market size and on-court success are not related.

One can also look at payroll and wins across this same time period. We do find a statistically significant link between team spending and wins. But team payroll only explains 6% of the variation in team wins. In other words, teams are not able to effectively buy wins in the NBA.

4. Fans don’t seem to care much about competitive balance.

But what if the richest teams could actually buy wins effectively? Wouldn’t that cause a problem for the league?

Researchers have looked at the link between competitive balance and league attendance in baseball. As noted in The Wages of Wins, the link is quite small. Two different studies found that in baseball, a movement from the most competitive position in league history to the least competitive position in league history would only result in about a 15% increase in attendance. Yes, that is something. But that is all you get from a move from the least balanced position to the most balance.

Recently I have looked at this same issue in the NBA. And the preliminary results seem quite similar. NBA fans don’t seem to care much about competitive balance. To illustrate, the NBA was much more balanced in the late 1970s, but it was not very popular. As noted, since Stern took over the NBA has not been balanced at all. And yet per game attendance has risen from about 11,000 in 1983-84 to more than 17,000 this past season. Furthermore, the league’s television contract has risen from less than $40 million per year (for the entire league) in 1984 to more than $900 million per year today.

Despite all this evidence, though, owners are still demanding salary concessions in the name of competitive balance. And as noted in the past, owners of professional sports teams have made this argument since the 1870s. So it is not surprising to see this story being told. But one hopes is understood – at least someday – is that the owner’s argument is not supported by the empirical evidence.

http://wagesofwins.net/2011/08/10/nba-o ... e-balance/

This would more closely align the NBA with the NFL model and the myth that football's hard salary cap creates parity. But football's cap doesn't create championship-level parity. Since 2000, 44 teams have played in the conference championships, but just 10 of the league's 32 franchises account for 68 percent of the games (30 of 44 appearances), while just three -- Pittsburgh, Philadelphia and New England -- account for 34 percent (15 of 44) of appearances.

In the NBA during the same period, nine of the 30 franchises account for 75 percent of conference finals appearances, with just three -- San Antonio, Detroit and the Lakers -- accounting 39 percent (17 of the 44) of appearances.

At first glance, it might appear the NBA lacks the parity of the NFL. In the NBA, 16 of those 44 conference finals appearances were made by teams located in top-10 television markets. What does this suggest about Stern's argument that big-money, big-revenue teams are controlling the standings?

In the NFL, the league of the vaunted hard salary cap and far less guaranteed money for its players, 20 of the 44 teams in the NFC of AFC title games came from top-10 TV markets -- and there isn't even a franchise in Los Angeles, the second-biggest market in the country.

Expand this analysis to the top-15 television markets (even though Stern vacated 15th-ranked Seattle for 45th-ranked Oklahoma City) and nine different NBA franchises have played in conference finals. In the vaunted NFL, where every franchise has a chance, that number is 11.

http://espn.go.com/espn/commentary/stor ... gic-flawed

Others
http://offthedribble.blogs.nytimes.com/ ... dy-has-it/
http://wagesofwins.net/2011/09/23/nba-p ... mpossible/

Parity isn't the problem.

[Hye4Life]

On the one hand, owners want to keep the stars that they draft. Yet, on the other hand they want to keep salaries equal between teams.

What they don't realize is that teams usually go over the cap to resign their own drafted players. In fact, teams can only increase in salary 5 million (MLE) per year once they are over the cap. I would venture to guess that most teams that are over the cap right now got there through resigning their own players.

The Lakers got to their salary by giving Bynum close to max money, giving Kobe a massive extension (30 million a year) , followed by giving Gasol close to 20 million a year. They didn't get that way by giving Artest, Blake, and Walton about 5 million a piece. In fact if you take all those MLE signings out, they would still be above the cap.

Now if the owners want to equalize the salary that each team can offer, by creating a HARD CAP, then they better be ready to lose their favorite players when their rookie contracts expire. Therefore, in the new system, the Bulls and Thunder would not be able to resign their star players.

Furthermore, if all teams could offer the same contracts to the players, then this makes the attractive markets even more attractive. Why play for the same salary in Milwaukee if you can play for the same amount in LA or NY or Chi? I think this would lead to more turnover of players from around the league and make it very hard to follow a team as players would be constantly changing teams from season to season.

I might be wrong, but this is what I feel would happen...

[Teh-Monkey-Man]

Furthermore, if all teams could offer the same contracts to the players, then this makes the attractive markets even more attractive. Why play for the same salary in Milwaukee if you can play for the same amount in LA or NY or Chi? I think this would lead to more turnover of players from around the league and make it very hard to follow a team as players would be constantly changing teams from season to season.

I might be wrong, but this is what I feel would happen...

I think this is a really good point

In fact, if i was a player there would be situations where i would possibly take a little less money in order to play somewhere where i really want to be

[Wizenheimer]

why don't you just count a couple that aren't simply anecdotal assertions from union reps

....edited out the superfluous.....

Parity isn't the problem.

I tossed out the opinion columns you posted. We've had enough of ESPN writers and such trying to protect their access to players by writing favorable opinion pieces

you only had one 'study' of data there, the one by Dave Berri

and even though I know you will ignore it, I'll point out that Dave Berri is talking about a correlation between market size and competitive balance (not parity) while this thread is talking about a correlation between payroll and winning percentage

there's a fundamental difference between those two correlations. And it's very evident there is a correlation between spending on payroll and winning percentage. How big of an impact payroll level has to winning is open for debate as the other factors are introduced. But there is no debate that the correlation is real.

Finally, Dave Berri is a pretty good statistical analyst. Sometimes however, his conclusions are debatable. What he did state in that article is that the NBA has by far the worst competitive balance of any major professional sport in this country

anyway, if you can focus on the topic of this thread instead of your crusade in favor of the players you can read the article I link below, here's an excerpt:

So, in conclusion, there is a clear and unquestionable positive correlation between spending and winning in the NBA. However, the correlation isn’t that strong, and there are plenty of outliers every (not just the Knicks). Furthermore, it seems like the correlation may be increasing in recent years, but there isn’t really enough data to be sure.

http://www.jeremyscheff.com/2011/07/the-correlation-between-spending-and-winning-in-the-nba-trends-by-year-and-by-team/

my opinion is that the correlation is even bigger then the data shows because teams who draft well in the lottery get 4 years of cheap talent due to the rookie scale. That adds a skew to data that isn't recognized by any models I've seen

For example, OKC has been a high win team with a low payroll because Durant, Westbrook, Harden, & Ibaka have all been playing under rookie salaries. That ended last season as Durant will be in his first year of his extension next season, Westbrook the following year, with Harden & Ibaka next. In other words, they bought their wins cheap the last couple of years but those wins are going to significantly increase in price going forward.

The same was true of the Blazers till last season, and has been true for other teams as well.

The rookie scale artificially introduces inexpensive wins into the data. But teams can't keep flushing veterans and drafting rookies while expecting their wins to remain high