ambchang
12-29-2006, 02:08 PM
The verdict is in, the zebras, at least in last year’s playoffs, are not biased, and I hope that this can put the conspiracy theories to death.
I ran a model (similar to the model I ran earlier for the regular season) to predict the number of FTAs a player should get based on the number of perimeter shots, shots in the paint, dunks, tips and 3pters. After the model was run, I decided to take out 3pters and tips, because statistically, these two factors do not show that they are significant.
What I found was a little surprising, to say the least.
The teams that “suffer” most from a lack of calls are Phoenix, Cleveland, and LA Clippers. Phoenix could be easily explained by their style of play, but I was surprised by Cleveland as the team that suffered the 2nd most out of all 16 playoff teams, with about 6 less FTs attempted than expected per game, given their style of play, and the presence of one LeBron James.
Chicago being the top beneficiary of the calls was just as surprising, perhaps it was due to the physical nature of the Miami series, where calls are a frequent occurrence.
All the teams that faced Phoenix saw their expected FTAs in the negatives, which is not surprising given the no foul policy by Mike D’Antoni, as well as the higher than expected number of layups and dunks from fastbreaks.
Team GP Dif Total Dif / Game
CHI 6 34.69343 5.782238378
WAS 7 38.57245 5.510349997
MIA 23 116.1622 5.050528628
SAS 20 56.14845 2.807422328
DET 23 57.50887 2.500385631
IND 13 29.37893 2.259917562
MEM 23 18.21389 0.791908243
SAC 22 6.738917 0.306314406
NJN 22 -0.6626 -0.030118141
DEN 23 -23.4917 -1.021376141
LAL 23 -26.5326 -1.153591394
DAL 23 -34.552 -1.50226194
MIL 20 -44.6722 -2.233608036
LAC 17 -53.5584 -3.150496763
CLE 8 -49.2999 -6.162481683
PHO 13 -124.648 -9.588288725
From an individual standpoint, I took the players that have less than 5 FTAs, and ranked them according to the difference between actual and predicted FTs, and projected it to 48 minutes. Shockingly, none of the first seven players are what you would qualify as superstars. Dirk Nowitzki, the player often cited as the player that got an unreasonable amount of FTs by Spurs fans, ranked 16th out 126 players, Manu Ginobili, the player who was accused by non-Spurs fan as a flopper, ranked 15th out of the bunch. At the same time, NBA-darling Dwayne Wade ranked a lowly 24th of the bunch, while LeBron James couldn’t even get into the top 40. Remember, players such as Jannero Pargo, David Harrison, and Reggie Evans all finished higher than these superstars, and I doubt that the league wants Chicago, Indiana or Seattle to win the championship, nor can these players bring in significant revenue from their jersey sales.
Name FTA PFTA Dif Total Dif / 48 min
David Harrison 12 3.911056 8.088944448 12.52481721
Reggie Evans 18 2.12208 15.87791999 11.04550956
Hakim Warrick 14 6.892516 7.107483502 7.933935072
Ronny Turiaf 6 2.12208 3.877919993 7.445606386
Dahntay Jones 10 3.092019 6.907981312 7.208328326
Jannero Pargo 5 2.467067 2.532932876 6.398988319
Nazr Mohammed 18 6.335407 11.66459263 5.956387727
Gilbert Arenas 70 41.59818 28.40182008 4.80030762
Alonzo Mourning 42 20.77198 21.228023 4.528644906
Derek Anderson 8 2.032398 5.967601611 4.340073899
Brendan Haywood 25 11.40765 13.59235251 4.209244648
Chauncey Billups 116 59.19705 56.80294868 3.86195685
Tyson Chandler 10 1.637111 8.362889333 3.859795077
Corey Maggette 67 43.57032 23.42967883 3.851454054
Manu Ginobili 87 54.73124 32.26876177 3.635916819
Dirk Nowitzki 229 154.6723 74.32771153 3.633126429
Robert Horry 26 9.690812 16.30918826 3.479293496
Michael Redd 46 32.57024 13.42975719 3.465743791
Tim Duncan 131 96.6815 34.31850433 3.341355391
Jermaine O'Neal 53 38.08046 14.91954075 3.315453499
Kevin Martin 29 15.92708 13.07292416 3.185281013
Austin Croshere 18 6.468767 11.53123264 3.162852382
Maurice Evans 16 9.428389 6.571610883 3.123141806
Dwyane Wade 250 190.6534 59.34664581 2.970426485
Anderson Varejao 37 22.62316 14.37683749 2.899530249
Carmelo Anthony 52 41.4074 10.5925978 2.634428468
Sasha Vujacic 11 4.406944 6.593055515 2.453229959
Kirk Hinrich 42 30.23938 11.76062492 2.41243588
Ben Wallace 66 34.54372 31.45628083 2.34821381
Vladimir Radmanovic23 11.14572 11.85428024 2.313030291
Eddie Jones 15 9.328283 5.671717208 2.287751479
Lamar Odom 45 30.72054 14.27945805 2.18284709
Vince Carter 108 89.3234 18.6765987 1.992170528
James Posey 37 13.52076 23.47923926 1.856677899
Jason Collins 22 10.79411 11.2058896 1.775190431
Shaquille O'Neal 182 155.8887 26.11133997 1.651310038
Erick Dampier 44 28.59221 15.40778824 1.629017259
Sam Cassell 68 54.73173 13.26827395 1.576428588
Ben Gordon 37 29.08627 7.913729305 1.550444925
Andres Nocioni 35 27.75331 7.246691815 1.512353074
So there you have it, this is as scientific as I can get with the available data, and even though I am aware of the short comings of leaving out style of play in the analysis, this is as detailed as I can get. If anybody can supply me with the raw data of individual series (numbers such as FTA, 3pters taken, perimeter shots taken, paint shots taken, tips and dunks broken down by individual players), I am more than happy to run the analysis.
I ran a model (similar to the model I ran earlier for the regular season) to predict the number of FTAs a player should get based on the number of perimeter shots, shots in the paint, dunks, tips and 3pters. After the model was run, I decided to take out 3pters and tips, because statistically, these two factors do not show that they are significant.
What I found was a little surprising, to say the least.
The teams that “suffer” most from a lack of calls are Phoenix, Cleveland, and LA Clippers. Phoenix could be easily explained by their style of play, but I was surprised by Cleveland as the team that suffered the 2nd most out of all 16 playoff teams, with about 6 less FTs attempted than expected per game, given their style of play, and the presence of one LeBron James.
Chicago being the top beneficiary of the calls was just as surprising, perhaps it was due to the physical nature of the Miami series, where calls are a frequent occurrence.
All the teams that faced Phoenix saw their expected FTAs in the negatives, which is not surprising given the no foul policy by Mike D’Antoni, as well as the higher than expected number of layups and dunks from fastbreaks.
Team GP Dif Total Dif / Game
CHI 6 34.69343 5.782238378
WAS 7 38.57245 5.510349997
MIA 23 116.1622 5.050528628
SAS 20 56.14845 2.807422328
DET 23 57.50887 2.500385631
IND 13 29.37893 2.259917562
MEM 23 18.21389 0.791908243
SAC 22 6.738917 0.306314406
NJN 22 -0.6626 -0.030118141
DEN 23 -23.4917 -1.021376141
LAL 23 -26.5326 -1.153591394
DAL 23 -34.552 -1.50226194
MIL 20 -44.6722 -2.233608036
LAC 17 -53.5584 -3.150496763
CLE 8 -49.2999 -6.162481683
PHO 13 -124.648 -9.588288725
From an individual standpoint, I took the players that have less than 5 FTAs, and ranked them according to the difference between actual and predicted FTs, and projected it to 48 minutes. Shockingly, none of the first seven players are what you would qualify as superstars. Dirk Nowitzki, the player often cited as the player that got an unreasonable amount of FTs by Spurs fans, ranked 16th out 126 players, Manu Ginobili, the player who was accused by non-Spurs fan as a flopper, ranked 15th out of the bunch. At the same time, NBA-darling Dwayne Wade ranked a lowly 24th of the bunch, while LeBron James couldn’t even get into the top 40. Remember, players such as Jannero Pargo, David Harrison, and Reggie Evans all finished higher than these superstars, and I doubt that the league wants Chicago, Indiana or Seattle to win the championship, nor can these players bring in significant revenue from their jersey sales.
Name FTA PFTA Dif Total Dif / 48 min
David Harrison 12 3.911056 8.088944448 12.52481721
Reggie Evans 18 2.12208 15.87791999 11.04550956
Hakim Warrick 14 6.892516 7.107483502 7.933935072
Ronny Turiaf 6 2.12208 3.877919993 7.445606386
Dahntay Jones 10 3.092019 6.907981312 7.208328326
Jannero Pargo 5 2.467067 2.532932876 6.398988319
Nazr Mohammed 18 6.335407 11.66459263 5.956387727
Gilbert Arenas 70 41.59818 28.40182008 4.80030762
Alonzo Mourning 42 20.77198 21.228023 4.528644906
Derek Anderson 8 2.032398 5.967601611 4.340073899
Brendan Haywood 25 11.40765 13.59235251 4.209244648
Chauncey Billups 116 59.19705 56.80294868 3.86195685
Tyson Chandler 10 1.637111 8.362889333 3.859795077
Corey Maggette 67 43.57032 23.42967883 3.851454054
Manu Ginobili 87 54.73124 32.26876177 3.635916819
Dirk Nowitzki 229 154.6723 74.32771153 3.633126429
Robert Horry 26 9.690812 16.30918826 3.479293496
Michael Redd 46 32.57024 13.42975719 3.465743791
Tim Duncan 131 96.6815 34.31850433 3.341355391
Jermaine O'Neal 53 38.08046 14.91954075 3.315453499
Kevin Martin 29 15.92708 13.07292416 3.185281013
Austin Croshere 18 6.468767 11.53123264 3.162852382
Maurice Evans 16 9.428389 6.571610883 3.123141806
Dwyane Wade 250 190.6534 59.34664581 2.970426485
Anderson Varejao 37 22.62316 14.37683749 2.899530249
Carmelo Anthony 52 41.4074 10.5925978 2.634428468
Sasha Vujacic 11 4.406944 6.593055515 2.453229959
Kirk Hinrich 42 30.23938 11.76062492 2.41243588
Ben Wallace 66 34.54372 31.45628083 2.34821381
Vladimir Radmanovic23 11.14572 11.85428024 2.313030291
Eddie Jones 15 9.328283 5.671717208 2.287751479
Lamar Odom 45 30.72054 14.27945805 2.18284709
Vince Carter 108 89.3234 18.6765987 1.992170528
James Posey 37 13.52076 23.47923926 1.856677899
Jason Collins 22 10.79411 11.2058896 1.775190431
Shaquille O'Neal 182 155.8887 26.11133997 1.651310038
Erick Dampier 44 28.59221 15.40778824 1.629017259
Sam Cassell 68 54.73173 13.26827395 1.576428588
Ben Gordon 37 29.08627 7.913729305 1.550444925
Andres Nocioni 35 27.75331 7.246691815 1.512353074
So there you have it, this is as scientific as I can get with the available data, and even though I am aware of the short comings of leaving out style of play in the analysis, this is as detailed as I can get. If anybody can supply me with the raw data of individual series (numbers such as FTA, 3pters taken, perimeter shots taken, paint shots taken, tips and dunks broken down by individual players), I am more than happy to run the analysis.