Free Agency Ratings (So Far)

Little math problem. I'll fix it soon.
EDIT: I have now switched these to being based on a much more accurate player rating, RAPM via http://stats-for-the-nba.appspot.com

I've made Free Agency ratings for each signing and team. These ratings are based on a few things:

First, Production ($). This refers to the estimated value of a player's Wins Above Replacement, which is based off my limited, but useful SPR rating. The basic math (which is somewhat based on the CBA) is roughly: $1.5 million x WARP + $1 million = Production $.

 Some issues with this are:

1) A player's WARP will be diminished if they are injured
2) SPR ratings are not great at measuring defense

The latter I don't have a quick fix for. The former, I made a quick adjustment to. A player's initial value is multiplied up to 68*** games (i.e. if a player's production was $1 million and they played 34 games, their injury-adjusted production would be $2 million). If they played more than 68 games, they got full credit for that # of games played.

Here are the best deals so far, followed by each team's gained/lost value (measured by the "Difference" column in the first table).


*Please note that this does not include any player whose terms are not listed on Basketball Reference's free agency tracker (I know Manu, for example, isn't on here)*

Player	OTm	NTm	2012 Injury-Adjusted Production ($)	Free Agency Signed $ / Year	Diff
Paul Millsap	UTA	ATL	21533840.13	9500000	12033840.13
Andre Iguodala	DEN	GSW	21350126.84	12000000	9350126.84
Jose Calderon	DET	DAL	16254169.95	7250000	9004169.954
Al-Farouq Aminu	NOP	NOP	11022611.33	3700000	7322611.329
Devin Harris	ATL	DAL	8802482.295	3000000	5802482.295
Nikola Pekovic	MIN	MIN	11672940.33	6046500	5626440.333
Chris Paul	LAC	LAC	26762960.65	21400000	5362960.654
Matt Barnes	LAC	LAC	9069688.566	3833333.333	5236355.233
David West	IND	IND	17096725.7	12000000	5096725.699
Tiago Splitter	SAS	SAS	13889325.24	9000000	4889325.242
J.R. Smith	NYK	NYK	10850257.13	6175000	4675257.135
Tony Allen	MEM	MEM	9387290.204	5000000	4387290.204
Mike Dunleavy	MIL	CHI	7280329.761	3000000	4280329.761
Josh Smith	ATL	DET	17765109.74	13500000	4265109.742
Mario Chalmers	MIA	MIA	8088888.511	4000000	4088888.511
Kyle Korver	ATL	ATL	9485217.163	6000000	3485217.163
Pablo Prigioni	NYK	NYK	5281693.116	2000000	3281693.116
Josh McRoberts	CHA	CHA	5925759.649	2750000	3175759.649
Dorell Wright	PHI	POR	6119130.344	3000000	3119130.344
Carlos Delfino	HOU	MIL	6214626.451	3250000	2964626.451
Darren Collison	DAL	LAC	4815418.725	1900000	2915418.725
Francisco Garcia	HOU	HOU	3729013.579	1300000	2429013.579
Dwight Howard	LAL	HOU	24287664.47	22000000	2287664.472
Omri Casspi	CLE	HOU	2915467.178	1300000	1615467.178
Jodie Meeks	LAL	LAL	2975483.078	1550000	1425483.078
Chase Budinger	MIN	MIN	6581692.313	5333333.333	1248358.98
Gerald Henderson	CHA	CHA	5384280.989	4200000	1184280.989
Greg Stiemsma	MIN	NOP	3816887.416	2700000	1116887.416
Dante Cunningham	MIN	MIN	3228831.038	2180000	1048831.038
Rashard Lewis	MIA	MIA	2397628.53	1400000	997628.5303
C.J. Watson	BRK	IND	2890695.155	2000000	890695.1553
Kevin Martin	OKC	MIN	8032773.588	7250000	782773.5881
Wayne Ellington	CLE	DAL	3254898.303	2500000	754898.3028
Jeff Teague	ATL	MIL	8603022.747	8000000	603022.7467
Chris Kaman	DAL	LAL	3606845.656	3200000	406845.6565
Ray Allen	MIA	MIA	3583235.199	3200000	383235.1986
Zaza Pachulia	ATL	MIL	5522598.858	5333333.333	189265.5244
O.J. Mayo	DAL	MIL	8158844.751	8000000	158844.7507
Tyler Hansbrough	IND	IND	4238255.5	4150000	88255.5003
Jarrett Jack	GSW	CLE	6290126.604	6250000	40126.60363
Patrick Mills	SAS	SAS	1076270.931	1133950	-57679.06913
Earl Watson	UTA	POR	1271447.862	1400000	-128552.1381
Boris Diaw	SAS	SAS	4422152.922	4702500	-280347.0777
J.J. Hickson	POR	DEN	4525962.224	5000000	-474037.776
Jerryd Bayless	MEM	MEM	2207495.722	3100000	-892504.278
Chris Copeland	NYK	IND	1847691.034	3050000	-1202308.966
Eric Maynor	POR	WAS	709401.2011	2000000	-1290598.799
Aaron Gray	TOR	TOR	1264898.481	2690875	-1425976.519
Al Jefferson	UTA	CHA	11830947.23	13500000	-1669052.773
Ronnie Brewer	OKC	MIN	3319730.452	5000000	-1680269.548
Trevor Ariza	WAS	WAS	6011169.571	7700000	-1688830.429
J.J. Redick	MIL	LAC	4901608.901	6750000	-1848391.099
Randy Foye	UTA	DEN	721589.5014	3000000	-2278410.499
Carl Landry	GSW	SAC	3529099.084	6500000	-2970900.916
Marco Belinelli	CHI	SAS	-596789.6931	3000000	-3596789.693
Shawn Marion	DAL	DAL	5505117.797	9316796	-3811678.203
Marvin Williams	UTA	UTA	3674119.951	7500000	-3825880.049
Tyreke Evans	SAC	NOP	6861293.132	11000000	-4138706.868
Emeka Okafor	WAS	WAS	9848117.628	14487500	-4639382.372
Earl Clark	LAL	CLE	-797022.1262	4500000	-5297022.126
Charlie Villanueva	DET	DET	2911016.137	8580000	-5668983.863
Richard Jefferson	GSW	UTA	1526167.7	11046000	-9519832.3
Ben Gordon	CHA	CHA	-4652922.605	13200000	-17852922.6

Team	Value Change by Not Resigning	Value Change By FA Signing/Resigning	Total
GSW	$12,450,606.61	$9,350,127	$21,800,733.45
LAC	$-	$11,666,344	$11,666,343.51
NYK	$1,202,308.97	$7,956,950	$9,159,259.22
DAL	$(3,481,109.13)	$11,749,872	$8,268,763.22
CHI	$3,596,789.69	$4,280,330	$7,877,119.45
MIN	$(1,116,887.42)	$7,026,134	$5,909,246.97
MIA	$-	$5,469,752	$5,469,752.24
IND	$-	$4,873,367	$4,873,367.39
LAL	$3,009,357.65	$1,832,329	$4,841,686.39
POR	$1,764,636.57	$2,990,578	$4,755,214.78
ATL	$(10,859,880.31)	$15,519,057	$4,659,176.98
NOP	$-	$4,300,792	$4,300,791.88
MEM	$-	$3,494,786	$3,494,785.93
HOU	$(2,964,626.45)	$6,332,145	$3,367,518.78
MIL	$(2,431,938.66)	$3,915,759	$1,483,820.81
SAC	$4,138,706.87	-$2,970,901	$1,167,805.95
SAS	$-	$954,509	$954,509.40
TOR	$-	-$1,425,977	$(1,425,976.52)
WAS	$-	-$7,618,812	$(7,618,811.60)
CLE	$(2,370,365.48)	-$5,256,896	$(7,627,261.00)
DET	$(9,004,169.95)	-$1,403,874	$(10,408,044.07)
DEN	$(9,350,126.84)	-$2,752,448	$(12,102,575.11)
CHA	$-	-$15,161,935	$(15,161,934.74)
UTA	$(7,957,824.72)	-$13,345,712	$(21,303,537.07)

***I used the Excel solver and asked it what standard # of games most accurately reflects money earned in the NBA. This was done by running the following math on each player-season:

2012 Raw Production $
-
(x / Games Played) * 2012 Raw Production $
=
Difference

Solver minimized this difference, and came up with about 68 games. 

Fourteen Scorers Remain (Sort of)

Assuming that the final four teams in the NBA playoffs are Miami, Indiana, San Antonio, and Memphis, (a big assumption) there are only 14 players with at least 100 minutes played who are taking at least 20% of their team's true-shooting attempts.

Sorted by points per 48 in the playoffs (LeBron has probably been hurt here by slower play, Parker vice versa).

Player	Pos	Tm	TS%	SA%	Pts/48	TS% - Avg
Tony Parker	PG	SAS	54.0%	30.5%	23.4	0.5%
LeBron James	PF	MIA	62.5%	28.1%	22.3	9.0%
Tim Duncan	C	SAS	50.3%	27.1%	19.4	-3.2%
Manu Ginobili	SG	SAS	51.2%	24.8%	18.1	-2.2%
Jerryd Bayless	PG	MEM	50.3%	24.3%	17.1	-3.2%
Zach Randolph	PF	MEM	56.0%	24.2%	19.0	2.6%
Paul George	SF	IND	51.5%	23.3%	16.1	-1.9%
Mike Conley	PG	MEM	53.2%	22.8%	16.9	-0.2%
Dwyane Wade	SG	MIA	47.4%	22.6%	13.6	-6.1%
David West	PF	IND	54.3%	21.9%	16.0	0.8%
Ray Allen	SG	MIA	65.4%	21.8%	18.2	11.9%
Marc Gasol	C	MEM	57.0%	21.5%	17.1	3.6%
George Hill	PG	IND	55.5%	21.3%	15.8	2.0%
Chris Bosh	C	MIA	56.8%	20.6%	14.9	3.3%

Also, check out Miami...

Player	Pos	Tm	TS%	SA%	Pts/48	TS% - Avg
LeBron James	PF	MIA	62.5%	28.1%	22.3	9.0%
Chris Andersen	C	MIA	78.0%	18.8%	18.7	24.5%
Ray Allen	SG	MIA	65.4%	21.8%	18.2	11.9%
Norris Cole	PG	MIA	77.3%	15.2%	15.0	23.9%
Chris Bosh	C	MIA	56.8%	20.6%	14.9	3.3%
Dwyane Wade	SG	MIA	47.4%	22.6%	13.6	-6.1%
Udonis Haslem	PF	MIA	59.7%	16.0%	12.2	6.3%
Mario Chalmers	PG	MIA	52.4%	14.5%	9.7	-1.0%
Shane Battier	SF	MIA	43.2%	14.9%	8.2	-10.2%

The Sweet 16 and Beyond

Here are the results of my latest 10,000 simulations of the tournament.

Notable Notes:

Expected number of double-digit seeds in the Sweet 16:   2.5

Odds of all four 1-seeds making it to the Sweet 16:   27%

Odds of La Salle making it to the Sweet 16:   37%               

reg	sd		s16	e8	f4	title game	Champ	exp. Wins
E	1	Indiana	90%	69%	55%	36%	23%	3.74
S	3	Florida	78%	65%	44%	26%	16%	3.28
W	1	Gonzaga	78%	63%	41%	25%	14%	3.20
MW	1	Louisville	67%	52%	34%	20%	10%	2.83
W	2	Ohio St.	73%	51%	28%	15%	7%	2.74
S	4	Michigan	69%	42%	22%	11%	6%	2.50
MW	2	Duke	64%	41%	22%	11%	5%	2.43
E	2	Miami FL	70%	46%	16%	7%	3%	2.42
W	6	Arizona	82%	33%	13%	5%	1%	2.34
MW	3	Michigan St.	68%	31%	14%	6%	2%	2.21
E	4	Syracuse	76%	24%	13%	5%	2%	2.21
S	7	San Diego St.	82%	21%	7%	2%	1%	2.12
S	1	Kansas	58%	27%	12%	5%	2%	2.05
MW	4	St. Louis	65%	20%	9%	3%	1%	1.98
E	3	Marquette	58%	25%	7%	2%	1%	1.92
W	12	Mississippi	63%	18%	7%	2%	1%	1.92
MW	8	Colorado St.	33%	20%	10%	4%	2%	1.69
S	8	North Carolina	42%	17%	6%	2%	1%	1.68
MW	7	Creighton	36%	19%	8%	3%	1%	1.68
E	6	Butler	42%	15%	3%	1%	0%	1.62
S	5	Virginia Commonwealth	31%	13%	4%	1%	0%	1.51
E	7	Illinois	30%	13%	3%	1%	0%	1.47
W	10	Iowa St.	27%	14%	4%	1%	0%	1.47
W	13	La Salle	37%	7%	2%	0%	0%	1.46
MW	12	Oregon	35%	7%	2%	0%	0%	1.45
MW	6	Memphis	32%	9%	2%	1%	0%	1.43
S	11	Minnesota	22%	13%	5%	1%	0%	1.42
W	9	Wichita St.	22%	12%	4%	1%	0%	1.40
E	12	California	24%	3%	1%	0%	0%	1.28
W	14	Harvard	18%	3%	0%	0%	0%	1.21
S	15	Florida Gulf Coast	18%	1%	0%	0%	0%	1.19
E	9	Temple	10%	3%	1%	0%	0%	1.15

Simulated Tournament, Luck-Adjusted Style

Alright...so I did another 10,000 simulations, but I used a combination of my luck-adjustments and Ken Pomeroy's strength of schedule to come up with some decent results. Notably, turnovers (offensive and defensive) are far more important here.

		ro32	s16	e8	f4	title game	Champ	exp. Wins
1	Indiana	100%	85%	68%	58%	38%	26%	3.74
2	Florida	99%	81%	64%	43%	24%	15%	3.26
3	Louisville	100%	71%	59%	39%	23%	12%	3.03
4	Gonzaga	100%	67%	49%	33%	21%	11%	2.81
5	Ohio St.	97%	70%	49%	25%	13%	6%	2.60
6	Michigan	92%	73%	48%	25%	13%	7%	2.58
7	Duke	99%	69%	46%	24%	12%	5%	2.55
8	Miami FL	95%	67%	47%	15%	6%	2%	2.32
9	Syracuse	96%	72%	21%	13%	5%	2%	2.09
10	Kansas	99%	62%	29%	11%	4%	2%	2.07
11	Georgetown	97%	63%	19%	8%	3%	1%	1.90
12	Michigan St.	84%	56%	26%	11%	5%	2%	1.83
13	Wisconsin	73%	56%	24%	13%	7%	3%	1.76
14	New Mexico	88%	51%	19%	6%	2%	1%	1.67
15	Marquette	71%	46%	21%	5%	1%	0%	1.44
16	Arizona	73%	39%	15%	5%	2%	0%	1.34
17	Pittsburgh	73%	28%	17%	10%	5%	2%	1.34
18	St. Louis	75%	43%	11%	4%	1%	0%	1.34
19	North Carolina	75%	33%	12%	4%	1%	1%	1.26
20	Creighton	65%	23%	12%	5%	2%	1%	1.08
21	Oklahoma St.	61%	32%	7%	3%	1%	0%	1.04
22	North Carolina St.	74%	13%	7%	4%	1%	0%	0.99
23	Colorado St.	57%	18%	13%	7%	3%	1%	0.99
24	Virginia Commonwealth	67%	19%	8%	2%	1%	0%	0.97
25	Butler	56%	25%	9%	1%	0%	0%	0.91
26	San Diego St.	57%	23%	5%	1%	0%	0%	0.87
27	Kansas St.	60%	20%	4%	1%	0%	0%	0.86
28	Notre Dame	54%	17%	9%	3%	1%	0%	0.83
29	Nevada Las Vegas	59%	18%	3%	1%	0%	0%	0.81
30	Minnesota	58%	12%	6%	2%	1%	0%	0.79
31	Colorado	51%	16%	8%	1%	0%	0%	0.77
32	St. Mary's	44%	21%	8%	3%	1%	0%	0.76
33	Illinois	49%	15%	7%	1%	0%	0%	0.73
34	Iowa St.	46%	12%	6%	2%	1%	0%	0.67
35	Bucknell	44%	17%	5%	1%	0%	0%	0.67
36	Missouri	43%	11%	6%	3%	1%	0%	0.64
37	Memphis	42%	15%	4%	1%	0%	0%	0.62
38	Oklahoma	43%	14%	2%	1%	0%	0%	0.60
39	Oregon	39%	17%	3%	1%	0%	0%	0.59
40	UCLA	42%	7%	3%	1%	0%	0%	0.54
41	California	41%	10%	1%	0%	0%	0%	0.51
42	Cincinnati	35%	8%	3%	1%	0%	0%	0.46
43	Mississippi	27%	15%	3%	1%	0%	0%	0.46
44	Davidson	29%	13%	3%	0%	0%	0%	0.46
45	Akron	33%	6%	1%	0%	0%	0%	0.41
46	Belmont	27%	8%	2%	0%	0%	0%	0.37
47	Wichita St.	27%	5%	2%	1%	0%	0%	0.35
48	New Mexico St.	25%	8%	1%	0%	0%	0%	0.34
49	Villanova	25%	5%	1%	0%	0%	0%	0.32
50	Boise St.	23%	6%	1%	0%	0%	0%	0.31
51	Temple	26%	2%	0%	0%	0%	0%	0.29
52	Valparaiso	16%	5%	1%	0%	0%	0%	0.22
53	La Salle	16%	3%	0%	0%	0%	0%	0.20
54	Middle Tennessee	14%	4%	1%	0%	0%	0%	0.19
55	Harvard	12%	2%	0%	0%	0%	0%	0.14
56	South Dakota St.	8%	2%	0%	0%	0%	0%	0.10
57	Pacific	5%	1%	0%	0%	0%	0%	0.06
58	Montana	4%	1%	0%	0%	0%	0%	0.04
59	Florida Gulf Coast	3%	1%	0%	0%	0%	0%	0.04
60	Iona	3%	0%	0%	0%	0%	0%	0.04
61	Northwestern St.	1%	0%	0%	0%	0%	0%	0.01
62	Western Kentucky	1%	0%	0%	0%	0%	0%	0.01
63	Albany	1%	0%	0%	0%	0%	0%	0.01
64	Southern	0%	0%	0%	0%	0%	0%	0.00
65	Long Island	0%	0%	0%	0%	0%	0%	0.00
66	North Carolina A&T	0%	0%	0%	0%	0%	0%	0.00
67	Liberty	0%	0%	0%	0%	0%	0%	0.00

Simulated Tournament, LRMC Style

I simulated the NCAA tournament 10,000 times based on the LRMC ratings. Just a pure-point-margin version of Ken Pomeroy's table. Use responsibly!

		ro32	s16	e8	f4	title game	champ	Exp. Wins
1	Indiana	100%	87%	70%	55%	31%	19%	3.62
2	Florida	96%	85%	72%	52%	34%	22%	3.61
3	Gonzaga	100%	78%	63%	48%	31%	18%	3.37
4	Louisville	100%	77%	63%	41%	23%	11%	3.16
5	Kansas	99%	83%	53%	24%	12%	6%	2.77
6	Miami (FL)	95%	73%	54%	21%	8%	3%	2.55
7	Ohio St.	94%	71%	48%	21%	11%	4%	2.50
8	Duke	96%	57%	39%	21%	10%	4%	2.28
9	Michigan	87%	60%	30%	11%	5%	2%	1.95
10	Syracuse	90%	62%	19%	10%	3%	1%	1.85
11	Georgetown	90%	56%	14%	5%	2%	1%	1.67
12	Creighton	77%	37%	23%	11%	5%	2%	1.55
13	Michigan St.	79%	45%	18%	7%	3%	1%	1.52
14	Wisconsin	68%	49%	16%	9%	4%	1%	1.46
15	New Mexico	81%	41%	17%	5%	2%	0%	1.45
16	Saint Louis	73%	38%	10%	3%	1%	0%	1.26
17	Oklahoma St.	64%	38%	11%	4%	1%	0%	1.18
18	Marquette	56%	33%	13%	3%	1%	0%	1.05
19	VCU	65%	27%	9%	3%	1%	0%	1.05
20	UNLV	67%	27%	5%	2%	1%	0%	1.02
21	Arizona	53%	30%	12%	3%	1%	0%	1.01
22	Bucknell	58%	26%	9%	2%	0%	0%	0.95
23	Kansas St.	64%	24%	4%	2%	1%	0%	0.95
24	Pittsburgh	59%	15%	8%	4%	2%	1%	0.89
25	San Diego St.	57%	25%	5%	1%	0%	0%	0.88
26	Iowa St.	58%	18%	9%	2%	1%	0%	0.87
27	N.C. State	68%	11%	5%	2%	1%	0%	0.86
28	Belmont	47%	25%	9%	2%	1%	0%	0.84
29	North Carolina	64%	13%	4%	1%	0%	0%	0.81
30	Davidson	44%	24%	8%	2%	0%	0%	0.78
31	Minnesota	61%	10%	5%	1%	0%	0%	0.78
32	Colorado	53%	15%	7%	1%	0%	0%	0.76
33	Colorado St.	52%	12%	7%	3%	1%	0%	0.75
34	Middle Tenn. St.	35%	20%	8%	3%	1%	0%	0.68
35	Missouri	48%	10%	6%	2%	1%	0%	0.67
36	Memphis	40%	17%	5%	1%	0%	0%	0.64
37	Butler	42%	16%	4%	1%	0%	0%	0.64
38	Illinois	47%	11%	5%	1%	0%	0%	0.63
39	Oklahoma	43%	16%	2%	1%	0%	0%	0.62
40	Notre Dame	42%	10%	4%	1%	0%	0%	0.56
41	Oregon	36%	16%	3%	1%	0%	0%	0.55
42	Wichita St.	41%	7%	4%	2%	1%	0%	0.55
43	Mississippi	32%	17%	3%	1%	0%	0%	0.54
44	Akron	35%	10%	2%	0%	0%	0%	0.48
45	UCLA	39%	4%	2%	0%	0%	0%	0.46
46	St. Mary's	25%	12%	4%	1%	0%	0%	0.43
47	California	33%	9%	1%	0%	0%	0%	0.43
48	Villanova	36%	4%	1%	0%	0%	0%	0.42
49	New Mexico St.	27%	8%	1%	0%	0%	0%	0.36
50	Temple	32%	2%	1%	0%	0%	0%	0.35
51	Cincinnati	23%	5%	2%	0%	0%	0%	0.31
52	Boise St.	21%	6%	1%	0%	0%	0%	0.28
53	Valparaiso	21%	6%	1%	0%	0%	0%	0.28
54	Harvard	19%	4%	0%	0%	0%	0%	0.23
55	La Salle	15%	4%	0%	0%	0%	0%	0.19
56	South Dakota St.	13%	3%	0%	0%	0%	0%	0.17
57	Fla Gulf Coast	10%	3%	0%	0%	0%	0%	0.13
58	Montana	10%	2%	0%	0%	0%	0%	0.13
59	Iona	6%	2%	0%	0%	0%	0%	0.08
60	Pacific	5%	1%	0%	0%	0%	0%	0.06
61	Northwestern St.	4%	1%	0%	0%	0%	0%	0.05
62	Albany	4%	1%	0%	0%	0%	0%	0.04
63	West. Kentucky	1%	0%	0%	0%	0%	0%	0.01
64	Southern	0%	0%	0%	0%	0%	0%	0.00
65	LIU Brooklyn	0%	0%	0%	0%	0%	0%	0.00
66	Liberty	0%	0%	0%	0%	0%	0%	0.00
67	N.C. A&T	0%	0%	0%	0%	0%	0%	0.00

Exactly How Good Is R. Kelly?

YOU SEE ME RUNNIN' THROUGH THAT OPEN DOOOOR.

Before I begin, I must honor the fact that I am a die-hard Carolina fan. I bleed Carolina blue and I hate Duke the instant I wake up each morning. But that cannot change the impact of the beardy white man, R. Kelly.

You might remember last season that I tweeted LeHigh's praises in terms of their ability to possibly beat Duke, *even before the brackets came out*...but my statistics pushed LeHigh's odds way up when we learned that Kelly wouldn't make the LeHigh game...because in my system, he was definitely their best player.

I've heard a lot of claims from all sorts of people on how good R. Kelly is...the boys over at 99.9 The Fan (Raleigh represent...) seem to think that he has made Duke's defense impeccably better. I'm not so sure...but only because Ken Pomeroy mentioned that in a blog post.


By my SPR measure that estimates per-100-possession impact, he is the best player in the ACC (same as Daniel Myers' ASPM. But I am more interested in how much worse their defense got with him out. Let us investigate.

I looked at Duke's expected efficiency differential based on kenpom.com efficiency stats (and home-court advantage), versus how they actually played, and here's the difference we see:

So despite Kelly's immense impact on offense, we can tell that at least Duke's defense looks better with him on the floor. Sixty-four places better.

All-Overrated and All-Underrated NBA Teams, 2013

All-Underrated Squad
Nate Robinson, PG
Andre Iguodala, SG
Thaddeus Young, SF
Nick Collison, PF
Kevin Garnett, C

All-Overrated Squad
Deron Williams, PG
JR Smith, SG
Klay Thompson, SF
Earl Clark, PF
Javale McGee, C

BOOM.

Players of the Month: December (so far)

Welcome, all! Here I will be grading players according to their estimated offensive and defensive impacts (using my per-100-possession stat, SimplePlayerRating) via Month-of-December-State. I'm rolling out my Defensive SPR here, finally. Formula at the bottom.

EDIT: Fixed the per-game numbers.

Surprises of the month go to: Andray Blatche (#6 #7), Paul George (#9 #10), Kemba Walker (#10 #11) and JJ Hickson (#17 #21!!!).

Without further ado, here are your top and bottom 26.

The Top 26

	Player	Season	OSPR	DSPR	Total SPR	SPR per Game
1	Carmelo Anthony	2012-13	10.6	-0.7	9.9	7.5
2	LeBron James	2012-13	6.9	1.3	8.1	6.5
3	Blake Griffin	2012-13	7.1	2.5	9.6	6.4
4	Kevin Durant	2012-13	6.2	0.4	6.6	5.4
5	Chris Paul	2012-13	6.3	2.1	8.4	5.4
6	Kobe Bryant	2012-13	6.4	-0.5	5.9	5.0
7	Andray Blatche	2012-13	4.7	3.6	8.2	4.8
8	Ryan Anderson	2012-13	7.9	-1.4	6.5	4.6
9	Tony Parker	2012-13	7.3	-0.6	6.6	4.6
10	Paul George	2012-13	4.7	1.0	5.7	4.5
11	Kemba Walker	2012-13	6.4	-0.1	6.3	4.4
12	Chris Copeland	2012-13	12.7	1.2	13.9	4.3
13	Russell Westbrook	2012-13	4.9	0.8	5.8	4.2
15	Stephen Curry	2012-13	5.0	-0.3	4.7	3.9
16	Paul Millsap	2012-13	4.1	1.3	5.4	3.7
17	James Harden	2012-13	4.0	0.5	4.5	3.7
18	Tyson Chandler	2012-13	3.7	1.3	5.0	3.5
19	Andrei Kirilenko	2012-13	1.1	3.5	4.6	3.5
21	J.J. Hickson	2012-13	5.4	1.0	6.4	3.4
20	Matt Barnes	2012-13	4.5	1.9	6.4	3.4
22	Ed Davis	2012-13	4.4	2.4	6.8	3.4
23	Dwyane Wade	2012-13	5.3	-0.4	4.8	3.2
24	David Lee	2012-13	3.8	0.2	4.0	3.2
27	Kyrie Irving	2012-13	5.9	-1.6	4.3	3.2
26	Eric Bledsoe	2012-13	3.6	4.6	8.2	3.2

The Bottom 26

	Player	Season	OSPR	DSPR	Total SPR	SPR per Game
387	Daniel Gibson	2012-13	-5.5	-1.7	-7.2	-3.9
386	Kyle Singler	2012-13	-4.1	-1.8	-5.9	-3.8
388	Doron Lamb	2012-13	-8.9	-1.6	-10.5	-3.8
382	Mickael Pietrus	2012-13	-4.6	-1.1	-5.7	-3.5
383	Andre Iguodala	2012-13	-5.3	0.7	-4.6	-3.4
379	Chris Singleton	2012-13	-5.9	0.1	-5.8	-3.3
381	J.R. Smith	2012-13	-3.6	-1.5	-5.1	-3.3
378	Andrea Bargnani	2012-13	-3.2	-2.2	-5.4	-3.2
377	Victor Claver	2012-13	-11.3	2.0	-9.3	-3.2
376	Jeff Taylor	2012-13	-3.1	-2.3	-5.4	-3.1
374	Jerry Stackhouse	2012-13	-4.0	-2.6	-6.6	-3.0
375	Bismack Biyombo	2012-13	-5.0	0.5	-4.5	-3.0
372	Alonzo Gee	2012-13	-3.3	-0.8	-4.1	-3.0
373	Gerald Green	2012-13	-4.7	-1.9	-6.7	-2.9
370	Willie Green	2012-13	-5.6	-2.2	-7.8	-2.8
369	Festus Ezeli	2012-13	-7.6	-0.9	-8.5	-2.6
368	Dahntay Jones	2012-13	-4.1	-2.4	-6.5	-2.6
367	Austin Rivers	2012-13	-2.6	-1.7	-4.3	-2.6
365	Keith Bogans	2012-13	-9.1	-2.6	-11.7	-2.6
364	Sebastian Telfair	2012-13	-3.2	-2.4	-5.6	-2.4
363	Aaron Brooks	2012-13	-2.7	-1.6	-4.3	-2.4
361	Martell Webster	2012-13	-2.8	-1.0	-3.8	-2.4
362	John Salmons	2012-13	-1.8	-1.8	-3.6	-2.4
359	Jason Maxiell	2012-13	-5.4	1.6	-3.8	-2.3
360	Tony Allen	2012-13	-6.1	1.5	-4.6	-2.3
358	Nolan Smith	2012-13	-6.5	-2.8	-9.3	-2.3

-The formula for DSPR is
DSPR = (1.3xSteals - 0.1xMissedFG + 0.2xDRB + 0.5xBLK)x100/Possessions Played - 3

-OSPR can be found here.