Will an Amnesty Clause Help Competitive Balance?

Posted on July 31, 2011 by Andres Alvarez

Dre Alvarez (@nerdnumbers) is a Co-Editor for the Wages of Wins Network and is also in charge of handling the stats data. He’s a long time fan of Colorado Sports, depending on the weather. He’s an even bigger fan of the stats, data and all things nerdy.

The Cap Guru’s Take

Here is a Tweet from NBA-CBA guru Larry Coon (@LarryCoon)

[Amnesty] helps from a competitive balance standpoint, but not from an overall revenue standpoint.

Larry is pretty much the only person in the world who understands all of the NBA CBA. When the new CBA is signed I am sure that fact will remain true. When it comes to competitive balance, though, I think he is wrong. Here’s how amnesty would work:

You’ve signed a bad player to a bad contract, and this contract is tying up your cap.
You get an option to pay the player some amount of money to go away.
You now have cap space to sign better players and compete.

Let’s take a quick look into the idea of getting a better player.

NBA Great and Terrible Players

Great and Terrible.

I looked over each NBA position for players that fit the two following requirements:

Played at least 1500 minutes in the 2010-2011 season
Played at least 1000 minutes at the required position (PG,SG,SF,PF and C)

This limited me to 181 players. I found out what an average player was in each position. I then looked for players above average and below average. In this case I used a threshold of 5.0 wins. Here’s what I came up with.

Table 1: Players who were more than 5.0 Wins Better than Average at Position

Name	Team	Pos	G	MP	WP48	WP
Kevin Love*	Minnesota	4.5	73	2611	0.458	24.9
Dwight Howard	Orlando	5.0	78	2935	0.397	24.3
LeBron James	Miami	3.2	79	3063	0.356	22.7
Chris Paul	New Orleans	1.0	80	2880	0.348	20.9
Dwyane Wade	Miami	1.9	76	2824	0.309	18.2
Pau Gasol	L.A. Lakers	4.8	82	3037	0.268	16.9
Zach Randolph	Memphs	4.3	75	2724	0.288	16.3
Blake Griffin*	L.A. Clippers	4.5	82	3112	0.237	15.3
Kevin Garnett	Boston	4.0	71	2220	0.312	14.4
Kevin Durant	Oklahoma City	3.0	78	3038	0.227	14.4
Al Horford	Atlanta	4.6	77	2704	0.255	14.3
Steve Nash	Phoenix	1.0	75	2497	0.275	14.3
Kris Humphries	New Jersey	4.0	74	2061	0.332	14.3
Paul Pierce	Boston	3.0	80	2774	0.240	13.9
Lamar Odom	L.A. Lakers	4.0	82	2639	0.249	13.7
Rajon Rondo	Boston	1.0	68	2527	0.258	13.6
Landry Fields*	New York	2.5	82	2541	0.249	13.2
Tim Duncan*	San Antonio	4.5	76	2156	0.293	13.2
Jason Kidd	Dallas	1.0	80	2653	0.234	12.9
Andre Iguodala	Philadelphia	2.9	67	2469	0.240	12.3
Tyson Chandler	Dallas	5.0	74	2059	0.284	12.2
Derrick Rose	Chicago	1.0	81	3026	0.190	12.0
Manu Ginobili*	San Antonio	2.5	80	2426	0.234	11.8
Kobe Bryant	L.A. Lakers	2.0	82	2779	0.203	11.7
Russell Westbrook	Oklahoma City	1.0	82	2847	0.195	11.5
Ray Allen	Boston	2.0	80	2890	0.181	10.9

*Players that qualified in multiple positions

Table 2: Players who were more than 5.0 Wins Worse than Average at Position

Name	Team	Pos	G	MP	WP48	WP
Andrea Bargnani	Toronto	4.6	66	2353	-0.115	-5.7
Darko Milicic	Minnesota	5.0	69	1686	-0.082	-2.9
Jeff Green	Oklahoma City	3.9	75	2427	-0.038	-1.9
Brook Lopez	New Jersey	5.0	82	2889	-0.031	-1.9
Dante Cunningham	Charlotte	4.0	78	1637	-0.052	-1.8
Glen Davis*	Boston	4.5	78	2298	-0.033	-1.6
Travis Outlaw	New Jersey	3.2	82	2358	-0.030	-1.5
Carl Landry	New Orleans	4.0	76	2008	-0.031	-1.3
Michael Beasley	Minnesota	3.2	73	2361	-0.021	-1.1
Derek Fisher	L.A. Lakers	1.0	82	2297	-0.018	-0.9
Nick Young*	Washington	2.5	64	2034	-0.019	-0.8
Gilbert Arenas	Orlando	1.6	70	1796	-0.021	-0.8
Wesley Johnson	Minnesota	3.0	79	2069	-0.014	-0.6
Nenad Krstic	Boston	5.0	71	1571	-0.013	-0.4
Willie Green	New Orleans	2.1	77	1674	-0.003	-0.1
Mo Williams	L.A. Clippers	1.0	58	1788	0.002	0.1
Jamal Crawford*	Atlanta	1.4	76	2297	0.006	0.3
Charlie Villanueva	Detroit	4.0	76	1666	0.008	0.3
DeMar DeRozan*	Toronto	2.5	82	2851	0.006	0.4
Ryan Gomes	L.A. Clippers	3.1	76	2095	0.010	0.4
C.J. Miles	Utah	2.8	78	1969	0.013	0.5
Steve Blake	L.A. Lakers	1.0	79	1581	0.017	0.6
Antawn Jamison	Cleveland	4.0	56	1842	0.020	0.8
De Marcus Cousin*	Sacramento	4.5	81	2309	0.019	0.9
Darrell Arthur	Memphis	4.0	80	1609	0.029	1.0
Andray Blatche	Washington	4.8	64	2172	0.023	1.0
Channing Frye*	Phoenix	4.5	77	2541	0.020	1.1
Spencer Hawes	Philadelphia	5.0	81	1718	0.038	1.3
Tyler Hansbrough	Indiana	4.0	70	1535	0.045	1.4

*Players that qualified in multiple positions.

Here’s a rundown, position by position:

Point Guard

Total Players: 43
Average Performance: 2299 Minutes Played, 0.128 WP48, 6.1 Wins Produced
Players with Performances 5.0+ Wins Produced Better than Average: 6
Players with Performances 5.0- Wins Produced Worse than Average: 4

Shooting Guard

Total Players: 46
Average Performance: 2199 Minutes Played, 0.108 WP48, 5.0 Wins Produced
Players with Performances 5.0+ Wins Produced Better than Average: 5
Players with Performances 5.0- Wins Produced Worse than Average: 3

Small Forward

Total Players: 45
Average Performance: 2369 Minutes Played, 0.115 WP48, 5.7 Wins Produced
Players with Performances 5.0+ Wins Produced Better than Average: 6
Players with Performances 5.0- Wins Produced Worse than Average: 7

Power Forward

Total Players: 43
Average Performances: 2323 Minutes Played, 0.139 WP48, 6.7 Wins Produced
Players with Performances 5.0+ Wins Produced Better than Average: 8
Players with Performances 5.0- Wins Produced Worse than Average: 10

Center

Total Players: 41
Average Performances: 2885 Minutes Played, 0.150 WP48, 7.1 Wins Produced
Players with Performances 5.0+ Wins Produced Better than Average: 7
Players with Performances 5.0- Wins Produced Worse than Average: 9

Why Parity Exists in the NBA

Good Players on the same team win.

Of our 181 players, most of them fall within a range of around 10.0 wins. This means when it comes to swapping out our players it can really just be Shuffling Deck Chairs. It might matter if you swap out an average player for for a great player (e.g. Quinten Richardson for LeBron James) or a terrible player for an average player (e.g. Jeff Green/Nenad Krstic for Kendrick Perkins).

The problem with both of these scenarios is the rarity of players at either end of the distrubition. In terms of player much better than their peers, there were only 26 players this last season. That isn’t even enough for one player a team. Not only that, certain teams have hogged several of these players. It doesn’t matter if we let teams try and upgrade their mediocre talent. There simply aren’t enough good players to replace them.

The same holds true with terrible players. Only 29 are really much worse than their peers. Again, that’s not even enough for one per team. Certain teams have more than one terrible players (Minnesota and Toronto for instance). Most teams, though, just don’t have an awful enough player such that a slight upgrade will magically fix everything.

Summing Up the Pay Problem in the NBA

But. . . we're paid like stars!

In the NBA many teams are perfectly willing to pay for a star player. The problem is there just aren’t enough of them to go around. A select group of players keep the really good teams good and the really bad teams bad. Even when a team manages to get a star it comes at the cost of another team (Miami and Cleveland anyone?). No pay provisions or clauses will fix this.

The issue comes back to a short supply of tall people. There will not be any provisions in the new CBA that are going to magically produce more elite talents. And that means competitive imbalance is probably going to continue (as it has continued for much of NBA history).

-Dre

Quick Takes: Pacific Division Draft Grades

Posted on July 30, 2011 by Devin Dignam

Devin Dignam (of NBeh? “fame”) is the Toronto Raptors writer for the Wages of Wins Network. He’s also an avid enthusiast of the draft (helped by being a Raptors fan). This post continues his comprehensive review of the 2011 draft.

Reviewing the 2011 NBA Draft

Today I’ll be reviewing the Pacific Division and how its teams fared in the draft. Here’s a reminder of my previous draft work:

The metric I’ll be using for my evaluation is Position Adjusted Win Score per 40 minutes (PAWS40). The ranks used are for all listed draft prospects not just those drafted. For those who are forgetful (thanks for the suggestion, mmotherwell), here are the average positional values for PAWS40:

Point Guard: 7.4
Shooting Guard: 8.4
Small Forward: 9.95
Power Forward: 12.59
Center: 12.32
All players: 10.17

On to the grades!

Los Angeles Lakers Draft Grade: B

"Meh"

The Lakers had several late second round picks: #41, #46, #56, and #58. The 56th pick was traded to the Nuggets for a future second rounder. The 58th pick was used to select former NCAA player Ater Majok (2.68 PAWS40 in 2009-2010). Those decisions don’t look so hot, but did LA hit it big with its remaining two choices? With the 41st pick, the team selected guard Darius Morris (8.57 PAWS40, 46th). With the 46th pick, they selected point guard Andrew Goudelock (9.47 PAWS40, 36th). It’s not surprising that the Lake show went for a point guard, given that the team has been getting nothing from that position for a number of years. Of the two prospects, Goudelock has a better chance of panning out – although both players are still below average. But with such late picks, I can’t fault LA for picking only one nearly average player.

Phoenix Suns Draft Grade: B+

Draft Picks have worked out for Phoenix before. . .

The Suns had the 13th pick, and with it they selected power forward Markieff Morris (13.68 PAWS40, 3rd). While Kenneth Faried would have been a better choice, the better Morris twin was the next best option. Hopefully the Suns will start Morris next to Marcin Gortat next year, which would keep Channing Frye and Robin Lopez on the bench where they belong. A rotation of Nash, Dudley, Hill, Morris, Gortat, and Childress and Warrick off the bench just might be enough to get the Nashty back into the playoffs. Notice I didn’t mention Frye, Lopez, Vince Carter or Aaron Brooks.

Golden State Warriors Draft Grade: B+

"Trade?!?!? Moi?!?!?"

The Warriors had the 11th and 44th pick, and bought the 39th pick away from the Bobcats as well. The 11th pick was used on guard-forward Klay Thompson(9.10 PAWS40, 41st). The 39th pick was used on Jeremy Tyler ( I don’t have any official stats for him), a well-traveled young forward-center who has been playing overseas since his senior year of high school. With the 44th pick, Golden State selected guard Charles Jenkins (12.17 PAWS40, 11th). Jenkins is an outright steal for the 44th pick and should become a good NBA player. Tyler is another mystery box – I suspect that he’s a project that will not pan out, but he’s taken a very unorthodox route to the NBA, so you never know. Thompson is roughly average and could go either way. By taking Thompson and Jenkins in the same draft, it seems like the Warriors might be preparing to trade away Monta Ellis, which wouldn’t necessarily be a bad thing.

Los Angeles Clippers Draft Grade: B+

Yes...Kyrie Irving should have been a Clipper!

The Clippers had two picks: with the 37th pick the Clippers selected power forward Trey Thompkins(7.38 PAWS40,62nd). With the 47th pick the team took shooting guard Travis Leslie (12.37 PAWS40,10th). Thompkins was not a very good pick, but the Clippers made up for it by lucking into the player with the 10th highest PAWS amongst all draftees. If he gets playing time, Leslie could be an above average NBA player this year. Does it make up for trading away the #1 pick in the draft in order to get rid of Baron Davis’ massive contract? Not quite, but luckily for the Clippers I’m not grading them on that.

Sacramento Kings Draft Grade: C+

Reddick 2.0?

Coming into the draft, the Kings had the 7th, 35th, and 60th picks, but the team traded the 7th pick and Beno Udrih for the 10th pick and John Salmons. Let’s focus on the two veteran players first.

John Salmons (3 year contract): 14.4 Expected Wins, $24.4 Million Value, $24.2 Million Salary
Beno Udrih (2 year contract): 13.3 Expected Wins, $22.6 Million value, $15.0 Million Salary

Salmons is being paid just about what he should be making, whereas Udrih was actually somewhat underpaid. Based on Salmons and Udrih’s past performances the Kings lost about $7.3 million in value with this switch. When we factor in the value lost by swapping the 7th pick into the 10th pick, Sacramento lost a total of $10.5 million in value in the trade.

The Kings then used the 10th pick on BYU point guard Jimmer Fredette (10.77 PAWS40, 20th). While Fredette did post an above average PAWS40, by my measures he is also the 4th most overrated draft prospect this year, only behind Jon Leuer, Gary Flowers and Troy Gillenwater. Flowers and Gillenwater went undrafted. Kings’ fans are probably going to be disappointed when Fredette turns out to be J.J. Redick 2.0. He’s not a terrible pick, but there were certainly plenty of better options available. Tyler Honeycutt (8.32 PAWS40, 49th) and Isaiah Thomas (9.77 PAWS40, 32nd) were selected 35th and 60th, respectively. Honeycutt probably won’t amount to much, but Thomas is just a hair under average and should surprise a lot of people if he gets the court time.

- Devin

Notes

Ranking all players by PAWS gives us a good idea of how well a player performed in their various leagues. A word of warning, though: NCAA PAWS40 does not correlate perfectly to NBA success, and Euroleague PAWS40 is even worse. For the most part, though, players with a PAWS of 12 or higher usually end up being good NBA players, and players with a PAWS of under 7.3 end up being below average players.

In order to come up with team grades, my method is as follows: I have a spreadsheet with all the draft prospects, all the draftees, their PAWS40, and (thanks to Arturo) the expected values of each pick. I also recorded the change in salary and wins obtained through draft day trades involving veteran players. Based on these numbers, I came up with the value that each team stands to gain if PAWS40 can perfectly predict NBA productivity. Of course, PAWS40 can’t predict NBA productivity perfectly, so the values I came up with aren’t infallible; I had to offer some subjective alterations to the raw scores. I won’t pretend that my evaluations are perfect, but nevertheless, I much prefer my methods to the vast majority of draft evaluations, which rely almost exclusively on subjective elements.

Killing their Team

Posted on July 28, 2011 by Arturo

Arturo Galletti is the Co-editor and Director of Analytics for the Wages of Wins Network. He is an Electrical Engineer with General Electric in the lovely isle of Puerto Rico, where he keeps his production lines running by day and night (and weekends) and works on sport analysis with his free time.

“Ever notice that ‘what the hell’ is always the right decision?”-Marylin Monroe

My fellow editor Dre wrote a lovely little trivia post today, where he asked:

Since 1978 only 8 players have managed to “earn” -15.0 Wins Produced or fewer and play 10,000 minutes or more. Can you name them?

Adam, you wanna take this one?

I had a great deal of fun thinking about the question but I refrained from answering it (because really that would be cheating). It did however distract me from a series I’ve been working on long enough to produce some very cool infographics.

What the question actually inspired for me was to think of the bizarro version of an old post from my own blog. That post focused on the Wins Produced All-NBA Teams by Year for every year since 1978. The rules were simple, the Wins Produced All NBA Teams is composed of the best player at each position for each season based on ADJP48 (who played more than 2000 minutes for that season). It produced an awesome visualization

(Editor Dre’s Note: Follow the link down the Rabbit Hole to see the cool visualization)

All-NBA Teams Season by Season Awesome Infographic

It looked great and I proceeded to have some great fun with it.

Dre’s post inspired a similar brainstorm but in reverse. Doing the worst seasons is easy. (Editor Dre’s Note: Thanks for calling my trivia easy Arturo!)

Table 1: Worst 25 Player Seasons (1978-2011)

The Worst Seasons
Rank	Name	Year	Pos	MP	WP48	WP
1	Adam Morrison	2007	PF	2326	-0.190	-9.2
2	Mahmoud Abdul-Rauf	1991	PG	1505	-0.251	-7.9
3	Clifford Robinson	2004	PF	2846	-0.129	-6.8
4	Dennis Scott	1991	PF	2336	-0.140	-6.7
5	Jeff Turner	1992	PF	1591	-0.201	-6.6
6	Rex Chapman	1989	SG	2219	-0.143	-6.6
7	John Amaechi	2001	C	1710	-0.185	-6.3
8	Jason Collins	2007	C	1844	-0.164	-6.3
9	Clifford Robinson	1990	C	1565	-0.193	-6.1
10	James Worthy	1994	PF	1597	-0.182	-6.0
11	Andrea Bargnani	2011	C	2353	-0.123	-5.6
12	Brad Sellers	1988	C	2212	-0.122	-5.6
13	Nikoloz Tskitishvili	2003	PF	1320	-0.203	-5.5
14	Charlie Scott	1980	SG	1860	-0.141	-5.4
15	Robert Reid	1989	SF	2152	-0.121	-5.2
16	Allan Houston	1994	SG	1519	-0.164	-5.1
17	Pete Maravich	1979	SG	1824	-0.135	-5.1
18	James Edwards	1992	C	1437	-0.170	-5.1
19	Lamond Murray	1995	PF	2556	-0.094	-5.0
20	Antoine Carr	1996	C	1532	-0.156	-5.0
21	Willie Green	2007	SG	1842	-0.126	-4.8
22	Orlando Woolridge	1992	PF	2113	-0.109	-4.8
23	Jeff Turner	1985	PF	1429	-0.161	-4.8
24	Mark Macon	1992	SG	2304	-0.099	-4.8
25	Jamal Mashburn	1994	SF	2896	-0.079	-4.8

Taking it a little further though is the key. What if we ranked the Anti Wins Produced All-NBA Team? The rules again are fairly simple. Grab the worst player by position using Wins Produced as the standard, with the caveat that the player must play at least >1200 minutes for the season in question. I then added a dollop of craziness and trickeration and stirred well. Interested?

Nothing interesting here

I did however promise infographs right? Here it comes:

(Click to enlarge.)

If I tabulate the results of this exercise we get 134 names with 31 repeat offenders.The list includes some surprising names. Stars like Kevin Durant and James Worthy make cameos either early or late in their respective careers.

However, this shouldn’t surprise longtime readers of this space as they are very familiar with the idea that too young or too old means less productive.

Been meaning to work this one in somehow.

As for those repeat offenders?

Table 2: Players with Multiple Appearances on All-Terrible Teams (1978-Present)

Player	Apperances
Mahmoud Abdul-Rauf	4
Maurice Taylor	3
Ron Mercer	3
Sebastian Telfair	3
Mark Blount	2
Charlie Scott	2
Robert Reid	2
Clifford Robinson	2
Kevin Duckworth	2
David Wesley	2
Nick Young	2
Desmond Mason	2
Rod Higgins	2
Jamal Mashburn	2
Johnny Newman	2
James Edwards	2
Calvin Murphy	2
James Robinson	2
Campy Russell	2
Jason Kapono	2
Rex Chapman	2
Jay Vincent	2
Rod Foster	2
Antoine Carr	2
Ron Boone	2
Terry Teagle	2
John Williamson	2
Jeff Turner	2
Tim Thomas	2
Joe Bryant	2
John Amaechi	2

Mahmoud Abdul-Rauf crowns himself the king of the Team Killers although Nick Young lurks in the weeds to possibly take his crown.

It's like matter and antimatter colliding on a basketball court!

If you’re nice, I just might do the team version of this tomorrow.

-Arturo

Afternoon Thoughts

Posted on July 28, 2011 by Andres Alvarez

Hey all,

It’s a lot of fun to do research and post numbers and analysis, but it turns out that many of us here at the Wages of Wins Network are sports fans. That means we have plenty of links and discussions in long e-mail chains or Tweets that never end up in a post. We’re going to experiment by posting some of these for your enjoyment.

The Lions are a Contender

It could happen.

Peter King has said “the Detroit Lions might (and he said might many times) be in the Super Bowl”. Here is a link to the video.
http://www.mlive.com/lions/index.ssf/2011/07/video_peter_king_offers_detroi.html

This has Dave super psyched. His blissful optimism as a Lion’s fan means he almost believes it too.

The All Injured Team

Hindsight is a cruel thing.

Without really crunching the numbers I thought it would be fun to build an All-Time team out of players that could have been great if injuries hadn’t stopped them. Here’s my starting five. Agree? Disagree?

PG: Anfernee Hardaway
SG: Brandon Roy
SF: Grant Hill
PF: Antonio McDyess
C: Yao Ming

Feel free to shoot along any links or thoughts you have. We love hearing them.

<-Dre

Trivia: Baddest of the Bad

Posted on July 28, 2011 by Andres Alvarez

Playing Poorly for the Long Haul

There's a big difference between a good big man and a bad one.

Last season Andrea Bargnani played terribly. It was the 10th worst performance of the turnover era (1978-present). The 9th spot on the list also goes to Bargnani for his 2008 performance. One or two bad seasons is nothing special. What is truly difficult is to make a career of it. Let’s just take a brief glimpse at some of Bargnani’s career accomplishments.

Andrea Bargnani

11095 Minutes Played -0.077 WP48 -17.8 Wins Produced
15.1 Points per Game with a 0.539 TS%
4.9 Rebounds per Game

It turns out Bargnani’s ability to play poorly and stay in the league is rare. That brings me to today’s trivia question.