For all your fancy-pants statistical needs.

Praise for The Basketball Distribution:

"...confusing." - CBS
"...quite the pun master." - ESPN

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).



PlayerPosTmTS%SA%Pts/48TS% - Avg
Tony ParkerPGSAS54.0%30.5%23.40.5%
LeBron JamesPFMIA62.5%28.1%22.39.0%
Tim DuncanCSAS50.3%27.1%19.4-3.2%
Manu GinobiliSGSAS51.2%24.8%18.1-2.2%
Jerryd BaylessPGMEM50.3%24.3%17.1-3.2%
Zach RandolphPFMEM56.0%24.2%19.02.6%
Paul GeorgeSFIND51.5%23.3%16.1-1.9%
Mike ConleyPGMEM53.2%22.8%16.9-0.2%
Dwyane WadeSGMIA47.4%22.6%13.6-6.1%
David WestPFIND54.3%21.9%16.00.8%
Ray AllenSGMIA65.4%21.8%18.211.9%
Marc GasolCMEM57.0%21.5%17.13.6%
George HillPGIND55.5%21.3%15.82.0%
Chris BoshCMIA56.8%20.6%14.93.3%



Also, check out Miami...

PlayerPosTmTS%SA%Pts/48TS% - Avg
LeBron JamesPFMIA62.5%28.1%22.39.0%
Chris AndersenCMIA78.0%18.8%18.724.5%
Ray AllenSGMIA65.4%21.8%18.211.9%
Norris ColePGMIA77.3%15.2%15.023.9%
Chris BoshCMIA56.8%20.6%14.93.3%
Dwyane WadeSGMIA47.4%22.6%13.6-6.1%
Udonis HaslemPFMIA59.7%16.0%12.26.3%
Mario ChalmersPGMIA52.4%14.5%9.7-1.0%
Shane BattierSFMIA43.2%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%               

regsds16e8f4title gameChampexp. Wins
E1Indiana90%69%55%36%23%3.74
S3Florida78%65%44%26%16%3.28
W1Gonzaga78%63%41%25%14%3.20
MW1Louisville67%52%34%20%10%2.83
W2Ohio St.73%51%28%15%7%2.74
S4Michigan69%42%22%11%6%2.50
MW2Duke64%41%22%11%5%2.43
E2Miami FL70%46%16%7%3%2.42
W6Arizona82%33%13%5%1%2.34
MW3Michigan St.68%31%14%6%2%2.21
E4Syracuse76%24%13%5%2%2.21
S7San Diego St.82%21%7%2%1%2.12
S1Kansas58%27%12%5%2%2.05
MW4St. Louis65%20%9%3%1%1.98
E3Marquette58%25%7%2%1%1.92
W12Mississippi63%18%7%2%1%1.92
MW8Colorado St.33%20%10%4%2%1.69
S8North Carolina42%17%6%2%1%1.68
MW7Creighton36%19%8%3%1%1.68
E6Butler42%15%3%1%0%1.62
S5Virginia Commonwealth31%13%4%1%0%1.51
E7Illinois30%13%3%1%0%1.47
W10Iowa St.27%14%4%1%0%1.47
W13La Salle37%7%2%0%0%1.46
MW12Oregon35%7%2%0%0%1.45
MW6Memphis32%9%2%1%0%1.43
S11Minnesota22%13%5%1%0%1.42
W9Wichita St.22%12%4%1%0%1.40
E12California24%3%1%0%0%1.28
W14Harvard18%3%0%0%0%1.21
S15Florida Gulf Coast18%1%0%0%0%1.19
E9Temple10%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.



ro32s16e8f4title gameChampexp. Wins
1Indiana100%85%68%58%38%26%3.74
2Florida99%81%64%43%24%15%3.26
3Louisville100%71%59%39%23%12%3.03
4Gonzaga100%67%49%33%21%11%2.81
5Ohio St.97%70%49%25%13%6%2.60
6Michigan92%73%48%25%13%7%2.58
7Duke99%69%46%24%12%5%2.55
8Miami FL95%67%47%15%6%2%2.32
9Syracuse96%72%21%13%5%2%2.09
10Kansas99%62%29%11%4%2%2.07
11Georgetown97%63%19%8%3%1%1.90
12Michigan St.84%56%26%11%5%2%1.83
13Wisconsin73%56%24%13%7%3%1.76
14New Mexico88%51%19%6%2%1%1.67
15Marquette71%46%21%5%1%0%1.44
16Arizona73%39%15%5%2%0%1.34
17Pittsburgh73%28%17%10%5%2%1.34
18St. Louis75%43%11%4%1%0%1.34
19North Carolina75%33%12%4%1%1%1.26
20Creighton65%23%12%5%2%1%1.08
21Oklahoma St.61%32%7%3%1%0%1.04
22North Carolina St.74%13%7%4%1%0%0.99
23Colorado St.57%18%13%7%3%1%0.99
24Virginia Commonwealth67%19%8%2%1%0%0.97
25Butler56%25%9%1%0%0%0.91
26San Diego St.57%23%5%1%0%0%0.87
27Kansas St.60%20%4%1%0%0%0.86
28Notre Dame54%17%9%3%1%0%0.83
29Nevada Las Vegas59%18%3%1%0%0%0.81
30Minnesota58%12%6%2%1%0%0.79
31Colorado51%16%8%1%0%0%0.77
32St. Mary's44%21%8%3%1%0%0.76
33Illinois49%15%7%1%0%0%0.73
34Iowa St.46%12%6%2%1%0%0.67
35Bucknell44%17%5%1%0%0%0.67
36Missouri43%11%6%3%1%0%0.64
37Memphis42%15%4%1%0%0%0.62
38Oklahoma43%14%2%1%0%0%0.60
39Oregon39%17%3%1%0%0%0.59
40UCLA42%7%3%1%0%0%0.54
41California41%10%1%0%0%0%0.51
42Cincinnati35%8%3%1%0%0%0.46
43Mississippi27%15%3%1%0%0%0.46
44Davidson29%13%3%0%0%0%0.46
45Akron33%6%1%0%0%0%0.41
46Belmont27%8%2%0%0%0%0.37
47Wichita St.27%5%2%1%0%0%0.35
48New Mexico St.25%8%1%0%0%0%0.34
49Villanova25%5%1%0%0%0%0.32
50Boise St.23%6%1%0%0%0%0.31
51Temple26%2%0%0%0%0%0.29
52Valparaiso16%5%1%0%0%0%0.22
53La Salle16%3%0%0%0%0%0.20
54Middle Tennessee14%4%1%0%0%0%0.19
55Harvard12%2%0%0%0%0%0.14
56South Dakota St.8%2%0%0%0%0%0.10
57Pacific5%1%0%0%0%0%0.06
58Montana4%1%0%0%0%0%0.04
59Florida Gulf Coast3%1%0%0%0%0%0.04
60Iona3%0%0%0%0%0%0.04
61Northwestern St.1%0%0%0%0%0%0.01
62Western Kentucky1%0%0%0%0%0%0.01
63Albany1%0%0%0%0%0%0.01
64Southern0%0%0%0%0%0%0.00
65Long Island0%0%0%0%0%0%0.00
66North Carolina A&T0%0%0%0%0%0%0.00
67Liberty0%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!



ro32s16e8f4title gamechampExp. Wins
1Indiana100%87%70%55%31%19%3.62
2Florida96%85%72%52%34%22%3.61
3Gonzaga100%78%63%48%31%18%3.37
4Louisville100%77%63%41%23%11%3.16
5Kansas99%83%53%24%12%6%2.77
6Miami (FL)95%73%54%21%8%3%2.55
7Ohio St.94%71%48%21%11%4%2.50
8Duke96%57%39%21%10%4%2.28
9Michigan87%60%30%11%5%2%1.95
10Syracuse90%62%19%10%3%1%1.85
11Georgetown90%56%14%5%2%1%1.67
12Creighton77%37%23%11%5%2%1.55
13Michigan St.79%45%18%7%3%1%1.52
14Wisconsin68%49%16%9%4%1%1.46
15New Mexico81%41%17%5%2%0%1.45
16Saint Louis73%38%10%3%1%0%1.26
17Oklahoma St.64%38%11%4%1%0%1.18
18Marquette56%33%13%3%1%0%1.05
19VCU65%27%9%3%1%0%1.05
20UNLV67%27%5%2%1%0%1.02
21Arizona53%30%12%3%1%0%1.01
22Bucknell58%26%9%2%0%0%0.95
23Kansas St.64%24%4%2%1%0%0.95
24Pittsburgh59%15%8%4%2%1%0.89
25San Diego St.57%25%5%1%0%0%0.88
26Iowa St.58%18%9%2%1%0%0.87
27N.C. State68%11%5%2%1%0%0.86
28Belmont47%25%9%2%1%0%0.84
29North Carolina64%13%4%1%0%0%0.81
30Davidson44%24%8%2%0%0%0.78
31Minnesota61%10%5%1%0%0%0.78
32Colorado53%15%7%1%0%0%0.76
33Colorado St.52%12%7%3%1%0%0.75
34Middle Tenn. St.35%20%8%3%1%0%0.68
35Missouri48%10%6%2%1%0%0.67
36Memphis40%17%5%1%0%0%0.64
37Butler42%16%4%1%0%0%0.64
38Illinois47%11%5%1%0%0%0.63
39Oklahoma43%16%2%1%0%0%0.62
40Notre Dame42%10%4%1%0%0%0.56
41Oregon36%16%3%1%0%0%0.55
42Wichita St.41%7%4%2%1%0%0.55
43Mississippi32%17%3%1%0%0%0.54
44Akron35%10%2%0%0%0%0.48
45UCLA39%4%2%0%0%0%0.46
46St. Mary's25%12%4%1%0%0%0.43
47California33%9%1%0%0%0%0.43
48Villanova36%4%1%0%0%0%0.42
49New Mexico St.27%8%1%0%0%0%0.36
50Temple32%2%1%0%0%0%0.35
51Cincinnati23%5%2%0%0%0%0.31
52Boise St.21%6%1%0%0%0%0.28
53Valparaiso21%6%1%0%0%0%0.28
54Harvard19%4%0%0%0%0%0.23
55La Salle15%4%0%0%0%0%0.19
56South Dakota St.13%3%0%0%0%0%0.17
57Fla Gulf Coast10%3%0%0%0%0%0.13
58Montana10%2%0%0%0%0%0.13
59Iona6%2%0%0%0%0%0.08
60Pacific5%1%0%0%0%0%0.06
61Northwestern St.4%1%0%0%0%0%0.05
62Albany4%1%0%0%0%0%0.04
63West. Kentucky1%0%0%0%0%0%0.01
64Southern0%0%0%0%0%0%0.00
65LIU Brooklyn0%0%0%0%0%0%0.00
66Liberty0%0%0%0%0%0%0.00
67N.C. A&T0%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


PlayerSeasonOSPRDSPRTotal SPRSPR per Game
1Carmelo Anthony2012-1310.6-0.79.97.5
2LeBron James2012-136.91.38.16.5
3Blake Griffin2012-137.12.59.66.4
4Kevin Durant2012-136.20.46.65.4
5Chris Paul2012-136.32.18.45.4
6Kobe Bryant2012-136.4-0.55.95.0
7Andray Blatche2012-134.73.68.24.8
8Ryan Anderson2012-137.9-1.46.54.6
9Tony Parker2012-137.3-0.66.64.6
10Paul George2012-134.71.05.74.5
11Kemba Walker2012-136.4-0.16.34.4
12Chris Copeland2012-1312.71.213.94.3
13Russell Westbrook2012-134.90.85.84.2
15Stephen Curry2012-135.0-0.34.73.9
16Paul Millsap2012-134.11.35.43.7
17James Harden2012-134.00.54.53.7
18Tyson Chandler2012-133.71.35.03.5
19Andrei Kirilenko2012-131.13.54.63.5
21J.J. Hickson2012-135.41.06.43.4
20Matt Barnes2012-134.51.96.43.4
22Ed Davis2012-134.42.46.83.4
23Dwyane Wade2012-135.3-0.44.83.2
24David Lee2012-133.80.24.03.2
27Kyrie Irving2012-135.9-1.64.33.2
26Eric Bledsoe2012-133.64.68.23.2

The Bottom 26


PlayerSeasonOSPRDSPRTotal SPRSPR per Game
387Daniel Gibson2012-13-5.5-1.7-7.2-3.9
386Kyle Singler2012-13-4.1-1.8-5.9-3.8
388Doron Lamb2012-13-8.9-1.6-10.5-3.8
382Mickael Pietrus2012-13-4.6-1.1-5.7-3.5
383Andre Iguodala2012-13-5.30.7-4.6-3.4
379Chris Singleton2012-13-5.90.1-5.8-3.3
381J.R. Smith2012-13-3.6-1.5-5.1-3.3
378Andrea Bargnani2012-13-3.2-2.2-5.4-3.2
377Victor Claver2012-13-11.32.0-9.3-3.2
376Jeff Taylor2012-13-3.1-2.3-5.4-3.1
374Jerry Stackhouse2012-13-4.0-2.6-6.6-3.0
375Bismack Biyombo2012-13-5.00.5-4.5-3.0
372Alonzo Gee2012-13-3.3-0.8-4.1-3.0
373Gerald Green2012-13-4.7-1.9-6.7-2.9
370Willie Green2012-13-5.6-2.2-7.8-2.8
369Festus Ezeli2012-13-7.6-0.9-8.5-2.6
368Dahntay Jones2012-13-4.1-2.4-6.5-2.6
367Austin Rivers2012-13-2.6-1.7-4.3-2.6
365Keith Bogans2012-13-9.1-2.6-11.7-2.6
364Sebastian Telfair2012-13-3.2-2.4-5.6-2.4
363Aaron Brooks2012-13-2.7-1.6-4.3-2.4
361Martell Webster2012-13-2.8-1.0-3.8-2.4
362John Salmons2012-13-1.8-1.8-3.6-2.4
359Jason Maxiell2012-13-5.41.6-3.8-2.3
360Tony Allen2012-13-6.11.5-4.6-2.3
358Nolan Smith2012-13-6.5-2.8-9.3-2.3



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

-OSPR can be found here.

An Apology for my Quietude: EZ Score

SORRY FOR THE DELAY. I have been hired by the Losangephoenix Spurockets to do basketballysis!


Just kidding.
I've actually been pretty busy doing other church-music related things. Not my bball-twitter-peeps kind of material, I know.

I've had ten or so blog posts in the works, none of which ever reached fruition.
Displeased with my blog production level ( < 20%), I decided to post what I think could probably have made me the most money (I don't know, a couple dollars?) had I decided to streamline and sell it.

Yes, my compassion and eagerness outweighs my entrepreneurial sense. And yes, I did have to spell-check "entrepreneurial."

With sincere apologies to Evan Zamir who owns a 51% market share on the term "EZ" in the basketball-stats world, I present "EZ Score." EZ Score is a game charting system that takes into account every possession (so it requires a bit of rewinding your recorded video), and every player on your team. It is pretty simple to describe, but a little bit open to interpretation. If anyone cares, I can post the Excel-specific nitty gritty on how to accomplish it, but here are the main basic details:


THE RULES OF EZ SCORE:

Introduction:
This is a system that imitates Dean Oliver's offensive and defensive rating system, although it is a little bit more intensive in that every possession (both offensive and defensive) must be charted. Credit is only given to whomever directly contributes to the possession result. This is pretty wide-open to interpretation, but generally I follow it like so:
Everything past #1 for each data point could be optional if you want, but it will give you less-refined results.

Each possession must be entered manually, simply by entering the player's jersey number like so:

A dream-team including MJ, Hansbrough, and Penny.


Where
P1=Most responsible / directly responsible for the possession result
P2=Less responsible than player #1
P3=Less responsible than player #1

i.e. 
If only one player truly deserves credit, only enter one player. My excel sheet distributes credit accordingly to the between 1 and 3 players(weights are noted at the end of this section).

THE SPECIFICS:

Offense:
Good possession (2+ points):
P1) Whoever scores
optional:
P2) Pass or screen or offensive rebound leading to score
P3) Pass or screen or offensive rebound leading to #2

Normative plays (1 point):
P1) Whoever scores. Optionally, the assister/etc can receive credit as P2 and/or P3, but this depends on your philosophy (is it the passer's "fault" that the player misses a free throw?, etc)

Bad plays (0 points):
P1) Turnover, missed field goal
optional:
P2) Not boxing out/missing easily available rebound


Defense:
Good possessions (0 points):
P1) Forced field-goal miss or defensive rebound (if more causal than #2), fouls, forced turnovers
optional:
P2) Forced field-goal miss or defensive rebound (if less causal than #1), fouls, forced turnovers, help defense
P3) Same as #2

Normative possessions (1 point):
P1) fouler gets 100% credit

Bad possessions (2+ points):
P1) Your man or your zone scores / fail to switch / etc
P2) If a man is wide open due to #1, whomever helps, etc receives #2.
P3) Same as #2


Now, the weighting. In excel, I weight every possession depending on the # of contributing players
If there is 1 player, they receive 100% of the score & possessions
p1=(100% * points, 1 possession)

If there are 2 players, the first receives 66.67% of the score and possession, the second receives 33.33%.
p1=(66% * points, 0.66 possessions), p2=(33% * points, 0.33 possessions)

If there are 3 players, the first receives 50%, and the second two receive 25% apiece.
p3=(50%*points, 0.5 poss), (25%*points, 0.25 poss)


So, there are many obvious small changes one could make. Many of these would increase the work of the charter and might not necessarily be necessary; it's a balancing act. The most obvious to me is the ability to choose in the two or three-player scenarios between ranked and equal weights for player 2 & 3 (i.e. the ability to say that a scorer-screener-assister are weighted something like 50-30-20 rather than 50-25-25) But I would love to hear your suggestions.


So..here are my results for USA v. France in the Olympics this year. This took maybe 30 minutes more than it would have, had it been a regular game-watching experience.


I'll try to do this for a few games this year as my free time permits. Use responsibly!

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About Me

I wish my heart were as often large as my hands.