Skip to main content
Menu
How Our RAPTOR Metric Works

RAPTOR, which stands for Robust Algorithm (using) Player Tracking (and) On/Off Ratings, is FiveThirtyEight’s new NBA statistic. We’re pretty excited about it. In addition to being a statistic that we bake in house, RAPTOR fulfills two long-standing goals of ours:

  • First, we wanted to create a publicly available statistic that takes advantage of modern NBA data, specifically player tracking and play-by-play data that isn’t available in traditional box scores.
  • Second, and relatedly, we wanted a statistic that better reflects how modern NBA teams actually evaluate players. NBA teams highly value floor spacing, defense and shot creation, and they place relatively little value on traditional big-man skills. RAPTOR likewise values these things — not because we made any deliberate attempt to design the system that way but because the importance of those skills emerges naturally from the data. RAPTOR thinks ball-dominant players such as James Harden and Steph Curry are phenomenally good. It highly values two-way wings such as Kawhi Leonard and Paul George. It can have a love-hate relationship with centers, who are sometimes overvalued in other statistical systems. But it appreciates modern centers such as Nikola Jokić and Joel Embiid, as well as defensive stalwarts like Rudy Gobert.

Before we get into more detail about RAPTOR, a few “getting to know you” basics about it:

  • Like Box Plus/Minus (BPM) and Real Plus Minus (RPM), RAPTOR is a plus-minus statistic that measures the number of points a player contributes to his team’s offense and defense per 100 possessions, relative to a league-average player. For instance, a player with an offensive RAPTOR rating of +2.1 boosts his team’s performance by 2.1 points per 100 offensive possessions while he is on the floor. Likewise, a player with a defensive RAPTOR of +3.4 would improve his team’s defensive performance1 by 3.4 points per 100 possessions while he’s on the court.
  • Plus-minus statistics have certain inherent limitations, and RAPTOR is subject to those, too. Namely, these statistics assume that player performance is largely linear and additive, that is, that you can roughly add up the ratings from individual players to project team performance. In other words, RAPTOR does not account for coaching, systems or synergies between teammates.
  • RAPTOR consists of two major components that are blended together to rate players: a “box” (as in “box score”) component, which uses individual statistics (including statistics derived from player tracking and play-by-play data), and an “on-off” component, which evaluates a team’s performance when the player and various combinations of his teammates are on or off the floor.
  • When applied to past data — for instance, in evaluating who the best players were in the 2018-19 season — RAPTOR is a descriptive statistic. Descriptive RAPTOR is based solely on a player’s on-court performance and the performance of the player’s teammates, as described above. It does not use priors based on a player’s height, weight, age or any other factor.
  • However, RAPTOR can also be used to make team and player predictions, and indeed our NBA predictions are now fueled by RAPTOR. (We are retiring the CARMELO brand name from our previous projection system, although much of the code for RAPTOR projections is borrowed from CARMELO.) RAPTOR-driven predictions do use qualities such as height, age and draft position, and even whether a player recently appeared on an All-NBA team — that data improves the performance of the predictive measure. Predictions also weight variables slightly differently than descriptive RAPTOR does, as certain statistics are more subject to luck than others. We refer to this predictive version of RAPTOR as PREDATOR (PREDictive rApTOR).
  • RAPTOR is based exclusively on publicly available data. There are other player-tracking statistics we believe could be highly helpful to RAPTOR, especially more detailed measures of on-ball defense, so we hope to be able to revisit RAPTOR as additional data becomes available.
  • RAPTOR’s name (in addition to being a whimsical backronym in the tradition of CARMELO and DRAYMOND) honors the 2018-19 Toronto Raptors, which FiveThirtyEight’s previous projection system correctly predicted had an edge over the Golden State Warriors (even though we didn’t fully believe the projection ourselves at the time).
  • The full-fledged version of RAPTOR is available for the 2013-14 season onward, as that’s when the NBA’s player-tracking data came on line. We also have a historical version of RAPTOR called Approximate RAPTOR dating back to 1976-1977, the first season after the ABA-NBA merger, but that uses a far more limited range of data.

RAPTOR ratings for players with at least 1,000 minutes played2 in a season since 2013-14 can be found in the table below. As you can see, RAPTOR generally loves perimeter players and wings, such as Curry, Harden, Leonard and Chris Paul, although some frontcourt players like Jokic, Anthony Davis and Draymond Green are also rated highly by the system. For more detail on past RAPTORs, including the breakdown of box and on-off components, you can download files that list the regular season and playoffs separately, or a version that combines a player’s appearances over the course of the entire season3 into one file.

RAPTOR ❤️s Steph, Harden, CP3 and Kawhi

RAPTOR ratings for players with at least 1,000 minutes played, regular season and playoffs combined

RAPTOR
Name
Season
Min. played
Off.
Def.
Total
WAR
Stephen Curry 2016 3,314 +10.4 +2.1 +12.5 26.7
Chris Paul 2014 2,643 +7.7 +3.7 +11.4 19.3
Stephen Curry 2015 3,439 +8.6 +2.4 +11.0 25.1
James Harden 2019 3,291 +9.6 +1.1 +10.7 22.8
Chris Paul 2015 3,302 +8.6 +2.1 +10.7 22.6
James Harden 2018 3,172 +8.8 +1.3 +10.1 20.9
Kawhi Leonard 2016 2,719 +5.1 +4.7 +9.9 17.5
Paul George 2019 3,045 +5.3 +4.2 +9.5 19.4
Draymond Green 2016 3,687 +3.9 +5.4 +9.4 23.5
Chris Paul 2016 2,545 +7.7 +1.6 +9.3 15.7
Kawhi Leonard 2017 2,903 +7.3 +2.0 +9.3 17.9
Stephen Curry 2017 3,239 +9.3 -0.1 +9.2 20.7
Chris Paul 2017 2,181 +7.9 +1.2 +9.1 13.2
Nikola Jokic 2019 3,061 +6.1 +2.7 +8.7 18.2
Chris Paul 2018 2,364 +7.0 +1.6 +8.6 13.7
Anthony Davis 2015 2,627 +3.8 +4.7 +8.5 15.2
Stephen Curry 2014 3,142 +7.8 +0.5 +8.3 18.1
Kawhi Leonard 2015 2,283 +3.4 +4.8 +8.2 12.9
Nikola Jokic 2016 1,733 +3.6 +4.5 +8.2 9.7
LeBron James 2016 3,531 +6.0 +2.2 +8.2 19.9
Jimmy Butler 2018 2,334 +5.7 +2.4 +8.1 12.7
LeBron James 2017 3,538 +6.9 +0.9 +7.8 19.2
Stephen Curry 2019 3,177 +7.5 +0.3 +7.8 17.6
Draymond Green 2017 3,064 +1.4 +6.4 +7.8 16.8
Stephen Curry 2018 2,186 +8.1 -0.5 +7.6 11.8
Victor Oladipo 2018 2,813 +3.4 +4.1 +7.5 15.1
Joel Embiid 2019 2,488 +2.7 +4.8 +7.5 13.3
James Harden 2015 3,617 +7.7 -0.2 +7.5 19.3
Anthony Davis 2019 1,850 +4.1 +3.3 +7.4 9.6
Draymond Green 2015 3,274 +1.9 +5.5 +7.3 17.3
Nikola Jokic 2017 2,038 +6.4 +0.9 +7.3 10.6
Jusuf Nurkic 2019 1,974 +2.1 +5.2 +7.2 10.1
James Harden 2017 3,354 +7.4 -0.3 +7.1 17.3
Kevin Durant 2017 2,603 +5.9 +1.1 +7.1 13.3
Russell Westbrook 2017 2,996 +7.8 -0.9 +6.8 15.3
Giannis Antetokounmpo 2019 2,872 +3.9 +2.9 +6.8 14.3
Jimmy Butler 2017 3,048 +4.6 +2.2 +6.8 14.8
Kevin Durant 2014 3,937 +7.1 -0.3 +6.8 19.7
Kawhi Leonard 2019 2,979 +5.7 +0.9 +6.6 14.5
Russell Westbrook 2016 3,424 +6.6 -0.0 +6.6 16.8
Kawhi Leonard 2014 2,659 +1.7 +4.9 +6.6 12.8
Kevin Love 2014 2,797 +5.7 +0.9 +6.6 13.6
Rudy Gobert 2017 2,990 +1.0 +5.6 +6.5 14.1
James Harden 2014 3,040 +6.5 -0.1 +6.4 14.4
Mike Conley 2019 2,342 +4.6 +1.7 +6.3 10.8
Mike Conley 2017 2,516 +5.5 +0.7 +6.2 11.6
Danny Green 2015 2,516 +3.0 +3.2 +6.2 11.5
Blake Griffin 2017 2,175 +4.6 +1.6 +6.2 10.0
Paul George 2016 3,094 +3.5 +2.6 +6.2 14.6
Damian Lillard 2018 2,832 +6.2 -0.1 +6.0 12.8
Paul George 2014 3,679 +3.0 +3.0 +6.0 16.7
Kemba Walker 2018 2,736 +5.4 +0.6 +6.0 12.2
Kyle Lowry 2017 2,544 +6.3 -0.4 +5.9 11.3
Manu Ginobili 2014 2,136 +4.1 +1.7 +5.9 9.7
LeBron James 2018 3,948 +7.5 -1.7 +5.8 17.4
Kyle Lowry 2016 3,617 +5.3 +0.4 +5.8 15.8
Kemba Walker 2019 2,863 +5.0 +0.8 +5.7 12.3
Joakim Noah 2014 3,030 +1.2 +4.5 +5.7 13.0
Kyrie Irving 2019 2,544 +5.1 +0.6 +5.7 11.1
George Hill 2015 1,267 +3.9 +1.7 +5.6 5.4
Jimmy Butler 2019 2,606 +3.6 +2.0 +5.6 11.1
Russell Westbrook 2015 2,302 +6.1 -0.5 +5.6 10.1
Kyle Lowry 2019 3,114 +3.7 +1.9 +5.6 13.5
Damian Lillard 2019 3,488 +6.4 -0.8 +5.6 15.0
LeBron James 2019 1,937 +5.4 +0.2 +5.6 8.3
Kyle Lowry 2014 3,133 +4.3 +1.2 +5.6 13.5
Jrue Holiday 2019 2,402 +4.1 +1.5 +5.6 10.3
Giannis Antetokounmpo 2018 3,036 +3.3 +2.2 +5.5 12.9
Manu Ginobili 2016 1,326 +2.2 +3.3 +5.5 5.7
Nikola Jokic 2018 2,443 +5.2 +0.3 +5.5 10.3
Steven Adams 2016 2,567 +1.3 +4.2 +5.5 10.7
Kevin Durant 2016 3,304 +5.5 -0.0 +5.4 14.1
Rudy Gobert 2019 2,729 +0.7 +4.7 +5.4 11.4
DeMarcus Cousins 2015 2,013 +0.9 +4.4 +5.4 8.5
Kyle Lowry 2018 2,871 +4.9 +0.4 +5.3 12.0
Eric Bledsoe 2019 2,695 +2.9 +2.4 +5.3 11.2
Patty Mills 2014 1,878 +3.8 +1.5 +5.3 7.7
Anthony Davis 2018 3,085 +1.3 +4.0 +5.3 12.8
Giannis Antetokounmpo 2017 3,088 +2.8 +2.5 +5.2 12.6
LeBron James 2014 3,665 +6.0 -0.9 +5.2 15.1
Kevin Durant 2018 3,132 +5.9 -0.7 +5.2 13.0
DeMarcus Cousins 2017 2,465 +3.4 +1.7 +5.1 10.0
Danny Green 2014 2,180 +1.2 +3.9 +5.1 8.9
Bradley Beal 2017 3,189 +4.9 +0.1 +5.1 12.9
Kevin Durant 2019 3,144 +5.2 -0.2 +5.1 12.8
Kemba Walker 2017 2,739 +5.0 +0.1 +5.0 10.8
Anthony Davis 2017 2,708 +0.6 +4.4 +5.0 10.8
Goran Dragic 2014 2,668 +4.8 +0.2 +5.0 10.6
LeBron James 2015 3,337 +4.8 +0.2 +5.0 13.3
DeMarcus Cousins 2014 2,298 +1.7 +3.3 +5.0 9.2
James Harden 2016 3,318 +5.6 -0.7 +4.9 13.1
Kyrie Irving 2018 1,931 +6.0 -1.2 +4.8 7.5
Nikola Vucevic 2019 2,657 +1.4 +3.4 +4.8 10.2
Tim Duncan 2016 1,754 -0.5 +5.2 +4.8 6.7
Kevin Love 2017 2,463 +2.8 +1.9 +4.7 9.5
Chris Paul 2019 2,254 +3.2 +1.4 +4.6 8.6
Russell Westbrook 2014 2,147 +4.3 +0.3 +4.6 8.4
Klay Thompson 2015 3,216 +4.0 +0.5 +4.5 12.1
Blake Griffin 2019 2,680 +4.1 +0.4 +4.5 10.0
Draymond Green 2019 2,916 +0.6 +3.8 +4.4 11.1
Russell Westbrook 2018 3,149 +4.3 +0.1 +4.4 11.8
Eric Bledsoe 2018 2,547 +2.6 +1.8 +4.4 9.5
DeAndre Jordan 2015 3,302 +3.1 +1.3 +4.4 12.0
Robert Covington 2018 2,813 +1.1 +3.3 +4.4 10.4
Tony Allen 2015 1,927 -0.4 +4.8 +4.4 7.1
Jrue Holiday 2018 3,275 +2.4 +2.0 +4.4 12.1
Otto Porter Jr. 2018 2,590 +2.9 +1.5 +4.4 9.4
Danilo Gallinari 2019 2,260 +4.3 +0.1 +4.4 8.2
DeMarcus Cousins 2016 2,246 +0.3 +4.1 +4.4 8.3
Joel Embiid 2018 2,190 +0.4 +3.9 +4.3 8.0
Draymond Green 2018 3,106 +1.0 +3.3 +4.3 11.6
Marc Gasol 2015 3,103 +1.4 +3.0 +4.3 11.2
Eric Bledsoe 2016 1,059 +2.3 +1.9 +4.2 3.8
Kyle Korver 2015 2,944 +4.0 +0.3 +4.2 10.6
Mario Chalmers 2016 1,373 +1.7 +2.5 +4.2 4.9
Draymond Green 2014 2,025 -0.8 +5.0 +4.2 7.3
Isaiah Thomas 2017 3,090 +7.5 -3.3 +4.2 11.1
Dirk Nowitzki 2014 2,891 +3.9 +0.3 +4.2 10.2
JJ Redick 2016 2,263 +2.8 +1.3 +4.1 8.0
Rudy Gobert 2015 2,158 -0.7 +4.8 +4.1 7.5
Kyrie Irving 2015 3,194 +5.3 -1.2 +4.1 11.3
Kevin Love 2016 3,037 +2.8 +1.3 +4.1 10.7
Khris Middleton 2015 2,610 +1.3 +2.8 +4.1 9.1
Al Horford 2018 2,956 +0.9 +3.2 +4.1 10.3
Anderson Varejao 2014 1,800 +0.5 +3.6 +4.1 6.2
Danny Green 2019 2,900 +2.6 +1.4 +4.1 10.1
Fred VanVleet 2018 1,634 +2.3 +1.7 +4.1 5.6
Darren Collison 2015 1,565 +1.7 +2.3 +4.0 5.4
Tiago Splitter 2015 1,153 +0.5 +3.5 +4.0 4.0
Kemba Walker 2016 3,145 +3.4 +0.7 +4.0 10.7
Jimmy Butler 2015 3,019 +3.6 +0.4 +4.0 10.4
Ricky Rubio 2016 2,323 +1.3 +2.7 +4.0 8.0
LaMarcus Aldridge 2018 2,686 +2.6 +1.4 +4.0 9.1
LaMarcus Aldridge 2015 2,720 +2.3 +1.6 +3.9 9.2
Tiago Splitter 2014 1,787 -0.5 +4.4 +3.9 6.2
Isaiah Thomas 2014 2,497 +3.5 +0.4 +3.9 8.5
Tyreke Evans 2018 1,607 +4.4 -0.6 +3.9 5.4
Paul Millsap 2019 2,364 +1.1 +2.8 +3.9 8.0
Derrick Favors 2019 1,869 +0.0 +3.8 +3.9 6.4
JJ Redick 2014 1,338 +2.7 +1.2 +3.9 4.6
Karl-Anthony Towns 2018 3,088 +4.1 -0.2 +3.8 10.3
Carmelo Anthony 2014 2,982 +4.2 -0.4 +3.8 9.9
Al Horford 2019 2,283 +1.6 +2.2 +3.8 7.6
Darren Collison 2018 2,232 +2.3 +1.4 +3.8 7.4
LaMarcus Aldridge 2014 2,939 +1.4 +2.3 +3.8 9.7
Malcolm Brogdon 2019 2,030 +2.6 +1.1 +3.8 6.8
Tim Duncan 2015 2,477 +0.4 +3.4 +3.8 8.2
Victor Oladipo 2019 1,147 +1.3 +2.5 +3.8 3.8
Kemba Walker 2014 2,767 +1.5 +2.3 +3.7 9.1
Hassan Whiteside 2015 1,142 +1.1 +2.6 +3.7 3.8
Derrick White 2019 1,919 +0.7 +3.0 +3.7 6.4
Deron Williams 2014 2,487 +2.6 +1.1 +3.7 8.3
Ricky Rubio 2014 2,638 +1.9 +1.8 +3.7 8.8
Rudy Gay 2017 1,013 +1.1 +2.6 +3.7 3.4
Eric Bledsoe 2014 1,416 +1.5 +2.2 +3.7 4.7
Derrick Favors 2016 1,983 +0.6 +3.1 +3.7 6.5
Clint Capela 2018 2,554 +0.4 +3.3 +3.7 8.4
Gordon Hayward 2017 2,927 +2.9 +0.8 +3.7 9.6
Lou Williams 2017 2,266 +5.7 -2.0 +3.7 7.6
Paul Millsap 2015 2,956 +1.3 +2.3 +3.7 9.8
Jimmy Butler 2016 2,474 +2.5 +1.2 +3.7 8.0
Delon Wright 2018 1,648 +1.4 +2.2 +3.6 5.4
Kyle Lowry 2015 2,545 +3.1 +0.6 +3.6 8.3
Rudy Gobert 2018 2,199 -0.6 +4.2 +3.6 7.2
Manu Ginobili 2017 1,575 +1.1 +2.5 +3.6 5.2
Wesley Matthews 2015 2,024 +2.3 +1.3 +3.6 6.6
Danny Green 2016 2,329 +0.6 +3.0 +3.6 7.6
Patrick Beverley 2017 2,383 +1.3 +2.3 +3.6 7.7
Paul Millsap 2014 2,749 +0.4 +3.1 +3.6 9.0
Andre Drummond 2019 2,774 +0.7 +2.8 +3.5 8.9
Jrue Holiday 2016 1,831 +3.3 +0.2 +3.5 5.9
Nikola Mirotic 2015 1,818 +1.6 +1.9 +3.5 5.8
Anthony Davis 2014 2,358 +1.2 +2.3 +3.5 7.5
Karl-Anthony Towns 2019 2,545 +3.5 +0.0 +3.5 8.1
Patrick Beverley 2014 1,953 +1.8 +1.7 +3.5 6.1
Gordon Hayward 2015 2,618 +3.2 +0.2 +3.4 8.3
Manu Ginobili 2015 1,718 +1.9 +1.5 +3.4 5.5
Kevin Love 2015 2,639 +1.9 +1.6 +3.4 8.3
Tristan Thompson 2016 2,891 +0.9 +2.5 +3.4 9.1
Jonas Jerebko 2015 1,298 +0.6 +2.8 +3.4 4.1
Kevon Looney 2018 1,297 -1.0 +4.4 +3.4 4.1
Dwight Powell 2018 1,672 +0.5 +2.9 +3.4 5.2
Blake Griffin 2014 3,341 +3.0 +0.4 +3.4 10.5
Kevon Looney 2019 1,913 +0.6 +2.8 +3.4 6.0
Damian Lillard 2017 2,845 +5.8 -2.4 +3.4 9.0
Bradley Beal 2019 3,028 +4.3 -0.9 +3.4 9.6
Mike Conley 2014 2,713 +3.2 +0.2 +3.4 8.4
Jimmy Butler 2014 2,809 +0.4 +2.9 +3.3 8.7
Vince Carter 2014 2,163 +2.5 +0.8 +3.3 6.8
Jeremy Lamb 2016 1,239 +1.0 +2.3 +3.3 3.8
Otto Porter Jr. 2017 3,033 +2.1 +1.2 +3.3 9.5
Kristaps Porzingis 2016 2,047 +0.1 +3.3 +3.3 6.4
Davis Bertans 2019 1,711 +2.2 +1.1 +3.3 5.3
Patrick Beverley 2016 2,170 +1.5 +1.8 +3.3 6.7
Nikola Pekovic 2014 1,663 +1.1 +2.2 +3.3 5.1
Paul George 2018 3,142 +1.7 +1.5 +3.3 9.8
Andre Iguodala 2014 2,288 +0.9 +2.3 +3.3 7.0
Brandon Jennings 2015 1,173 +3.1 +0.1 +3.2 3.5
Paul Millsap 2017 2,562 +0.7 +2.5 +3.2 7.9
CJ McCollum 2019 3,010 +3.3 -0.1 +3.2 9.2
CJ McCollum 2016 3,222 +2.4 +0.7 +3.1 9.7
Amir Johnson 2017 1,750 -0.3 +3.4 +3.1 5.2
Jae Crowder 2014 1,335 +0.1 +3.1 +3.1 4.0
Isaiah Thomas 2016 2,864 +4.1 -1.0 +3.1 8.7
Nikola Mirotic 2018 1,814 +2.5 +0.6 +3.1 5.5
Ersan Ilyasova 2019 1,503 -0.1 +3.2 +3.1 4.6
Mario Chalmers 2014 2,713 +1.4 +1.7 +3.1 8.1
Mike Conley 2015 2,468 +2.5 +0.6 +3.1 7.4
Hassan Whiteside 2019 1,674 -0.6 +3.8 +3.1 5.0
DeAndre Jordan 2016 2,796 +0.8 +2.3 +3.1 8.3
John Wall 2017 3,343 +4.6 -1.5 +3.1 10.1
Pau Gasol 2016 2,291 +0.7 +2.4 +3.1 6.8
Andrew Bogut 2014 1,769 -1.4 +4.4 +3.1 5.3
Kris Humphries 2014 1,376 +0.0 +3.0 +3.0 4.0
Al-Farouq Aminu 2015 1,516 +0.1 +2.9 +3.0 4.5
Blake Griffin 2015 2,913 +3.3 -0.3 +3.0 8.7
Danilo Gallinari 2015 1,426 +2.8 +0.2 +3.0 4.2
Marcin Gortat 2015 2,760 -0.2 +3.2 +3.0 8.1
Paul Millsap 2016 3,012 +0.4 +2.5 +3.0 8.9
David West 2017 1,075 -1.6 +4.5 +2.9 3.1
Pau Gasol 2017 1,992 +1.4 +1.6 +2.9 5.8
Ty Lawson 2014 2,222 +3.2 -0.3 +2.9 6.5
Joe Ingles 2017 2,306 +0.8 +2.1 +2.9 6.7
Eric Bledsoe 2015 2,800 +1.7 +1.2 +2.9 8.1
Tony Allen 2014 1,508 +0.6 +2.3 +2.9 4.4
Kelly Olynyk 2015 1,476 +0.8 +2.1 +2.8 4.3
Marc Gasol 2019 3,171 -0.8 +3.6 +2.8 9.0
DeAndre Jordan 2017 2,834 +1.3 +1.5 +2.8 8.0
Bradley Beal 2018 3,193 +2.3 +0.5 +2.8 9.1
DeMarre Carroll 2014 2,587 +0.7 +2.1 +2.8 7.3
Andrew Bogut 2015 2,023 -1.3 +4.1 +2.8 5.7
George Hill 2017 1,825 +2.9 -0.1 +2.8 5.1
Marvin Williams 2016 2,566 +2.2 +0.6 +2.8 7.2
Hassan Whiteside 2016 2,416 +0.4 +2.4 +2.8 6.8
Joe Ingles 2018 2,960 +2.0 +0.8 +2.8 8.4
James Johnson 2017 2,085 +0.4 +2.4 +2.8 5.9
David West 2016 1,580 +0.2 +2.5 +2.8 4.5
Chris Andersen 2014 1,713 +0.5 +2.3 +2.8 4.8
Damian Lillard 2014 3,403 +4.2 -1.4 +2.8 9.7
Robert Covington 2019 1,203 -0.6 +3.3 +2.8 3.4
Kristaps Porzingis 2018 1,553 +0.8 +2.0 +2.8 4.4
Jonas Valanciunas 2018 1,971 +1.1 +1.7 +2.7 5.6
Anthony Morrow 2015 1,806 +2.7 +0.1 +2.7 5.1
Lou Williams 2015 2,118 +4.8 -2.1 +2.7 6.0
John Collins 2019 1,829 +3.2 -0.5 +2.7 5.1
Clint Capela 2019 2,580 +0.8 +1.9 +2.7 7.2
Damian Lillard 2016 3,113 +4.9 -2.2 +2.7 8.8
Kyle Anderson 2018 2,051 -0.3 +3.0 +2.7 5.7
DeMarre Carroll 2015 2,747 +2.1 +0.6 +2.7 7.7
Zaza Pachulia 2015 1,859 -0.6 +3.3 +2.7 5.2
Jeff Teague 2015 2,757 +2.4 +0.3 +2.7 7.8
Klay Thompson 2016 3,515 +3.1 -0.5 +2.7 9.9
Jeremy Lamb 2019 2,250 +1.5 +1.1 +2.7 6.2
Jonas Valanciunas 2016 1,878 +2.2 +0.4 +2.6 5.2
Aron Baynes 2017 1,163 -1.9 +4.5 +2.6 3.2
Khris Middleton 2019 2,908 +2.2 +0.4 +2.6 8.0
Steven Adams 2018 2,687 +1.5 +1.1 +2.6 7.3
Serge Ibaka 2015 2,116 -0.4 +3.0 +2.6 5.7
LaMarcus Aldridge 2016 2,598 +1.0 +1.6 +2.6 7.1
Andre Roberson 2018 1,037 -1.4 +4.0 +2.6 2.8
Anthony Davis 2016 2,164 +0.3 +2.3 +2.6 5.9
Terry Rozier 2018 2,764 +1.1 +1.5 +2.6 7.5
Paul George 2017 2,861 +2.4 +0.2 +2.6 7.9
Kyrie Irving 2017 3,178 +6.1 -3.5 +2.6 8.7
Jrue Holiday 2015 1,358 +3.3 -0.7 +2.6 3.7
Otto Porter Jr. 2019 1,683 +1.3 +1.3 +2.6 4.6
Pascal Siakam 2019 3,439 +1.3 +1.2 +2.6 9.3
Thaddeus Young 2019 2,619 +0.7 +1.9 +2.6 7.1
Kentavious Caldwell-Pope 2016 2,950 +0.8 +1.7 +2.5 8.0
Larry Nance Jr. 2018 1,728 -0.2 +2.8 +2.5 4.7
Klay Thompson 2014 3,125 +1.9 +0.7 +2.5 8.5
Patrick Beverley 2019 2,332 +1.2 +1.4 +2.5 6.3
Serge Ibaka 2014 3,247 -0.1 +2.6 +2.5 8.8
Amir Johnson 2018 1,265 -0.6 +3.1 +2.5 3.4
Davis Bertans 2018 1,168 +0.8 +1.7 +2.5 3.2
Spencer Dinwiddie 2018 2,306 +3.2 -0.7 +2.5 6.1
DeMarcus Cousins 2018 1,737 +0.3 +2.2 +2.5 4.7
Delon Wright 2019 1,699 +0.5 +2.0 +2.5 4.5
Caris LeVert 2019 1,207 +1.0 +1.5 +2.5 3.2
Jakob Poeltl 2018 1,664 +0.1 +2.4 +2.5 4.4
Dwight Howard 2015 1,797 -0.7 +3.2 +2.5 4.8
JJ Redick 2015 2,949 +2.0 +0.4 +2.5 8.0
Shabazz Napier 2019 1,011 +1.7 +0.7 +2.4 2.7
Shane Battier 2014 1,670 +0.3 +2.2 +2.4 4.4
Rudy Gay 2015 2,408 +3.5 -1.1 +2.4 6.4
Joe Ingles 2019 2,719 +1.2 +1.2 +2.4 7.2
Jae Crowder 2017 2,931 +1.6 +0.8 +2.4 7.8
Channing Frye 2014 2,312 +2.0 +0.4 +2.4 6.1
Brook Lopez 2016 2,457 -0.1 +2.5 +2.4 6.4
Andre Roberson 2017 2,561 -1.9 +4.3 +2.4 6.7
George Hill 2014 3,121 +0.1 +2.3 +2.4 8.1
Jared Dudley 2015 1,827 +0.2 +2.2 +2.4 4.8
John Wall 2018 1,644 +2.2 +0.2 +2.4 4.4
Rudy Gobert 2016 1,932 -1.1 +3.5 +2.4 5.0
Dion Waiters 2017 1,384 +1.2 +1.2 +2.4 3.6
Kemba Walker 2015 2,119 +1.2 +1.2 +2.4 5.4
Al Horford 2015 2,840 +0.3 +2.1 +2.4 7.4
Marc Gasol 2017 2,771 +1.0 +1.4 +2.4 7.2
Marcus Smart 2019 2,232 +0.1 +2.3 +2.4 5.9
David West 2014 3,159 +0.9 +1.4 +2.4 8.3
Blake Griffin 2018 1,970 +2.2 +0.2 +2.4 5.2
CJ McCollum 2015 1,139 +1.3 +1.0 +2.4 3.0
Damian Lillard 2015 3,126 +3.7 -1.4 +2.4 8.1
Channing Frye 2016 1,437 +1.4 +0.9 +2.3 3.8
Marcin Gortat 2016 2,256 -0.9 +3.3 +2.3 5.8
Tyson Chandler 2015 2,446 -0.1 +2.4 +2.3 6.3
David Lee 2017 1,722 +0.6 +1.7 +2.3 4.5
Marcin Gortat 2014 3,037 -0.3 +2.6 +2.3 7.9
Victor Oladipo 2016 2,379 +1.2 +1.1 +2.3 6.2
Enes Kanter 2016 2,044 +2.5 -0.2 +2.3 5.2
Khris Middleton 2016 2,852 +2.6 -0.4 +2.3 7.4
Ryan Anderson 2016 2,008 +2.0 +0.3 +2.3 5.2
Klay Thompson 2017 3,245 +1.5 +0.8 +2.3 8.3
Tim Duncan 2014 2,910 -0.5 +2.7 +2.3 7.5
Derrick Favors 2015 2,280 +0.1 +2.1 +2.3 5.8
Devin Harris 2015 1,759 +1.8 +0.4 +2.2 4.5
Andre Roberson 2015 1,286 -1.1 +3.4 +2.2 3.3
Larry Nance Jr. 2019 1,795 +0.0 +2.2 +2.2 4.5
Wesley Matthews 2014 3,206 +2.3 -0.1 +2.2 8.2
Luka Doncic 2019 2,318 +3.1 -0.9 +2.2 5.9
Nemanja Bjelica 2019 1,788 +1.2 +1.0 +2.2 4.5
Rudy Gay 2019 2,021 +1.0 +1.2 +2.2 5.1
Iman Shumpert 2015 2,240 +0.5 +1.7 +2.2 5.7
Timofey Mozgov 2015 2,574 -1.1 +3.3 +2.2 6.6
Patty Mills 2016 1,829 +1.8 +0.4 +2.2 4.6
Jrue Holiday 2014 1,143 +2.2 -0.1 +2.2 2.9
CJ McCollum 2017 2,936 +3.2 -1.0 +2.2 7.4
Matt Barnes 2015 2,680 +1.0 +1.1 +2.2 6.8
Trevor Ariza 2014 3,130 +1.2 +0.9 +2.1 8.0
Josh Richardson 2018 2,819 -0.5 +2.7 +2.1 7.0
Nicolas Batum 2014 3,415 +1.8 +0.3 +2.1 8.7
Jared Dudley 2016 2,098 +1.3 +0.9 +2.1 5.2
Danilo Gallinari 2017 2,134 +2.6 -0.5 +2.1 5.3
Luc Mbah a Moute 2017 2,011 -1.3 +3.5 +2.1 5.0
Zach Randolph 2015 2,686 +1.1 +1.0 +2.1 6.6
Robin Lopez 2014 2,970 +0.8 +1.4 +2.1 7.3
J.J. Barea 2015 1,516 +2.1 -0.0 +2.1 3.7
Tyus Jones 2018 1,522 +0.8 +1.2 +2.1 3.7
Solomon Hill 2016 1,064 +1.1 +1.0 +2.1 2.7
Robert Covington 2017 2,119 -1.7 +3.8 +2.1 5.3
Ben Simmons 2018 3,101 +1.1 +1.0 +2.1 7.6
DeMarre Carroll 2016 1,382 -0.1 +2.2 +2.1 3.4
Jakob Poeltl 2019 1,450 +1.3 +0.8 +2.1 3.6
Gary Harris 2018 2,304 +1.4 +0.6 +2.1 5.7
Darren Collison 2014 2,318 +0.8 +1.3 +2.1 5.7
Dewayne Dedmon 2017 1,427 -1.7 +3.8 +2.1 3.5
Donovan Mitchell 2018 3,049 +1.4 +0.7 +2.1 7.6
Danilo Gallinari 2016 1,839 +3.0 -0.9 +2.1 4.5
LaMarcus Aldridge 2019 2,931 +0.6 +1.4 +2.1 7.1
Ty Lawson 2015 2,665 +3.8 -1.8 +2.1 6.6
Devin Harris 2017 1,087 +1.6 +0.4 +2.1 2.7
John Wall 2015 3,110 +2.0 +0.0 +2.1 7.8
Rudy Gay 2018 1,391 +0.7 +1.3 +2.1 3.4
Jae Crowder 2015 1,747 +1.8 +0.3 +2.1 4.3
Ersan Ilyasova 2017 2,232 -0.1 +2.1 +2.1 5.5
Kyle Korver 2018 2,079 +1.7 +0.3 +2.0 5.1
Jared Dudley 2019 1,302 -0.6 +2.6 +2.0 3.2
Derrick Rose 2015 1,984 +0.7 +1.3 +2.0 5.0
Cody Zeller 2015 1,487 -0.1 +2.1 +2.0 3.6
Jeremy Lamb 2018 1,967 +2.2 -0.2 +2.0 4.7
Joakim Noah 2015 2,444 -0.5 +2.5 +2.0 5.9
Tim Hardaway Jr. 2018 1,885 +2.0 -0.0 +2.0 4.6
Marc Gasol 2014 2,269 -1.0 +3.0 +2.0 5.4
Michael Kidd-Gilchrist 2015 1,587 -1.0 +3.0 +2.0 3.8
Michael Kidd-Gilchrist 2017 2,349 -1.4 +3.4 +2.0 5.6
Ersan Ilyasova 2015 1,461 +1.7 +0.2 +2.0 3.5
Dwight Howard 2014 2,627 -0.3 +2.2 +2.0 6.3
Shabazz Napier 2018 1,570 -0.6 +2.5 +1.9 3.7
John Wall 2016 2,784 +1.9 +0.0 +1.9 6.7
Andrew Bogut 2016 1,816 -1.7 +3.6 +1.9 4.4
Ed Davis 2016 1,889 +0.7 +1.2 +1.9 4.5
George Hill 2019 1,697 +0.8 +1.1 +1.9 4.0
Trey Burke 2019 1,125 +2.0 -0.1 +1.9 2.6
Derrick Favors 2018 2,439 +0.1 +1.8 +1.9 5.7
Lou Williams 2018 2,589 +5.2 -3.3 +1.9 6.3
Monte Morris 2019 2,194 +1.0 +0.9 +1.9 5.1
Patrick Patterson 2017 1,784 +0.2 +1.7 +1.9 4.2
Ricky Rubio 2017 2,469 +1.5 +0.3 +1.9 5.8
Dwight Powell 2019 1,662 +2.2 -0.4 +1.9 3.9
Tyler Johnson 2017 2,178 +0.1 +1.8 +1.9 5.1
JJ Redick 2018 2,458 +3.3 -1.4 +1.8 5.9
Nene 2017 1,359 -1.7 +3.6 +1.8 3.3
Kyle Anderson 2017 1,215 -0.7 +2.5 +1.8 2.9
Tobias Harris 2017 2,567 +1.0 +0.8 +1.8 6.0
Maxi Kleber 2019 1,502 -1.1 +2.9 +1.8 3.5
Serge Ibaka 2016 3,102 +0.2 +1.6 +1.8 7.3
Dirk Nowitzki 2016 2,534 +1.9 -0.1 +1.8 5.9
Marcus Smart 2016 1,860 -0.2 +2.0 +1.8 4.4
Steven Adams 2019 2,828 -0.1 +1.9 +1.8 6.6
Anthony Tolliver 2018 1,757 +1.7 +0.1 +1.8 4.1
Khris Middleton 2018 3,257 +2.8 -1.0 +1.8 7.6
Josh Richardson 2019 2,539 +0.9 +0.9 +1.8 5.8
Paul Pierce 2014 2,466 +0.0 +1.8 +1.8 5.8
Rashard Lewis 2014 1,290 -0.3 +2.1 +1.8 3.0
Jaylen Brown 2018 2,735 +0.6 +1.2 +1.8 6.4
Nikola Mirotic 2019 1,543 +1.1 +0.7 +1.8 3.6
Seth Curry 2017 2,029 +1.1 +0.6 +1.8 4.6
Bradley Beal 2015 2,525 +1.1 +0.7 +1.8 5.8
James Johnson 2015 1,382 +0.6 +1.2 +1.8 3.2
Channing Frye 2017 1,552 +0.9 +0.9 +1.8 3.6
Khris Middleton 2017 1,120 +0.8 +0.9 +1.8 2.6
Karl-Anthony Towns 2017 3,030 +3.8 -2.1 +1.7 7.0
Derrick Jones Jr. 2019 1,153 -0.4 +2.2 +1.7 2.6
De’Aaron Fox 2019 2,546 +1.9 -0.1 +1.7 6.0
Isaiah Thomas 2015 1,845 +4.4 -2.7 +1.7 4.3
Chandler Parsons 2014 3,033 +2.5 -0.8 +1.7 6.9
PJ Tucker 2014 2,490 +0.8 +0.9 +1.7 5.7
Aaron Gordon 2018 1,909 +0.1 +1.6 +1.7 4.4
Jamal Murray 2019 2,955 +2.1 -0.4 +1.7 6.7
Montrezl Harrell 2019 2,316 +0.9 +0.8 +1.7 5.3
Luol Deng 2015 2,421 +1.8 -0.1 +1.7 5.5
Marcus Smart 2015 1,898 +0.2 +1.4 +1.7 4.3
Jeff Teague 2017 2,799 +2.4 -0.8 +1.7 6.4
Montrezl Harrell 2018 1,293 +1.7 -0.1 +1.7 2.9
Brandan Wright 2015 1,449 +0.3 +1.3 +1.7 3.2
Michael Kidd-Gilchrist 2014 1,593 -2.4 +4.1 +1.7 3.5
J.J. Barea 2018 1,603 +3.4 -1.7 +1.7 3.6
DeAndre Jordan 2014 3,312 +0.6 +1.1 +1.7 7.4
Ersan Ilyasova 2018 1,962 -0.7 +2.4 +1.6 4.4
Al Horford 2016 2,958 -0.5 +2.1 +1.6 6.7
Patrick Patterson 2015 2,262 +2.3 -0.7 +1.6 5.1
Pablo Prigioni 2014 1,283 +1.7 -0.0 +1.6 2.8
Jason Terry 2017 1,433 +0.5 +1.2 +1.6 3.2
Greg Monroe 2017 1,964 +1.2 +0.4 +1.6 4.4
Trevor Ariza 2015 3,585 +0.2 +1.4 +1.6 8.0
Danny Green 2017 2,243 -0.3 +2.0 +1.6 5.0
Jonas Valanciunas 2019 1,091 +0.6 +1.0 +1.6 2.4
CJ Miles 2015 1,841 +1.4 +0.2 +1.6 4.1
Marcus Smart 2018 2,063 -0.8 +2.4 +1.6 4.7
Goran Dragic 2016 2,835 +0.8 +0.8 +1.6 6.3
Andre Iguodala 2015 2,704 +0.2 +1.4 +1.6 6.0
Nikola Mirotic 2017 1,841 +0.7 +0.9 +1.6 4.1
John Wall 2014 3,400 +1.7 -0.1 +1.6 7.7
Ed Davis 2015 1,840 +1.2 +0.4 +1.6 4.0
JR Smith 2016 3,092 +3.1 -1.5 +1.6 6.9
Thaddeus Young 2018 2,844 -0.3 +1.9 +1.6 6.2
Clint Capela 2016 1,514 -0.4 +2.0 +1.6 3.3
David West 2018 1,174 -1.4 +3.0 +1.6 2.6
Monta Ellis 2015 2,896 +1.1 +0.5 +1.6 6.5
Malcolm Brogdon 2017 2,165 +1.1 +0.4 +1.6 4.7
Tyler Zeller 2014 1,049 -1.0 +2.5 +1.5 2.3
Andre Drummond 2014 2,619 +1.3 +0.2 +1.5 5.7
Bogdan Bogdanovic 2019 1,947 +1.7 -0.2 +1.5 4.2
Chandler Parsons 2015 2,223 +2.3 -0.8 +1.5 4.9
Danny Green 2018 1,894 -1.1 +2.7 +1.5 4.1
Reggie Jackson 2016 2,571 +3.2 -1.6 +1.5 5.6
Jared Sullinger 2014 2,041 +0.5 +1.1 +1.5 4.5
Matthew Dellavedova 2014 1,271 +0.9 +0.6 +1.5 2.8
Tony Allen 2017 1,914 -0.7 +2.2 +1.5 4.1
Derrick Rose 2019 1,392 +2.7 -1.2 +1.5 3.0
Terrence Ross 2017 1,955 +1.4 +0.0 +1.5 4.3
Jared Dudley 2017 1,362 -0.8 +2.3 +1.5 3.0
Al-Farouq Aminu 2018 2,203 -0.6 +2.1 +1.5 4.8
D’Angelo Russell 2019 2,596 +2.4 -0.9 +1.5 5.7
Andre Iguodala 2019 2,207 +0.2 +1.3 +1.5 4.8
Gary Harris 2017 1,782 +3.2 -1.7 +1.5 3.8
Domantas Sabonis 2019 1,934 +0.9 +0.5 +1.5 4.2
Victor Oladipo 2017 2,403 -0.0 +1.5 +1.5 5.2
Bradley Beal 2014 2,988 +0.7 +0.8 +1.5 6.5
Klay Thompson 2018 3,300 +1.4 +0.0 +1.4 7.1
Kyle Korver 2016 2,717 +0.5 +1.0 +1.4 5.9
Boris Diaw 2014 2,578 +1.1 +0.4 +1.4 5.6
Russell Westbrook 2019 2,827 +2.5 -1.1 +1.4 6.1
JR Smith 2015 2,640 +2.3 -0.8 +1.4 5.6
Courtney Lee 2014 2,197 +0.7 +0.7 +1.4 4.7
Josh Hart 2018 1,461 +1.0 +0.5 +1.4 3.1
Amir Johnson 2016 1,934 +0.3 +1.1 +1.4 4.1
Cory Joseph 2019 2,148 -0.9 +2.3 +1.4 4.5
Kyle Korver 2014 2,658 +2.0 -0.6 +1.4 5.7
George Hill 2016 2,759 +0.6 +0.7 +1.4 5.9
Greg Monroe 2016 2,314 +1.5 -0.1 +1.4 4.9
Michael Kidd-Gilchrist 2018 1,850 -1.5 +2.9 +1.4 3.9
Nemanja Bjelica 2018 1,418 +0.1 +1.3 +1.4 3.0
Kevin Love 2018 2,311 +1.7 -0.3 +1.4 4.9
Dennis Schroder 2016 1,812 +0.3 +1.0 +1.4 3.8
Myles Turner 2017 2,674 -0.9 +2.2 +1.4 5.7
Karl-Anthony Towns 2016 2,627 +1.2 +0.2 +1.4 5.6
Ricky Rubio 2019 2,067 +0.4 +0.9 +1.4 4.4
Josh McRoberts 2014 2,514 +2.1 -0.8 +1.4 5.2
Mike Conley 2016 1,761 +2.2 -0.9 +1.4 3.6
Buddy Hield 2018 2,024 +1.1 +0.3 +1.4 4.2
Buddy Hield 2019 2,615 +2.2 -0.8 +1.4 5.5
Kelly Olynyk 2018 1,925 +2.2 -0.8 +1.4 4.0
Jeremy Lin 2015 1,907 +0.9 +0.4 +1.4 4.0
Tyler Hansbrough 2015 1,106 +0.7 +0.7 +1.3 2.3
Jeremy Lin 2016 2,237 -1.1 +2.4 +1.3 4.7
Jeremy Evans 2014 1,209 +0.2 +1.1 +1.3 2.5
DeMar DeRozan 2018 3,065 +3.4 -2.1 +1.3 6.3
Derek Fisher 2014 1,727 -0.1 +1.4 +1.3 3.6
Nick Collison 2014 1,536 -0.0 +1.3 +1.3 3.2
Carmelo Anthony 2015 1,428 +3.8 -2.5 +1.3 2.9
Kelly Olynyk 2016 1,427 -0.5 +1.8 +1.3 2.9
Tarik Black 2017 1,091 -1.1 +2.4 +1.3 2.2
Ish Smith 2018 2,043 +0.3 +1.0 +1.3 4.1
JJ Redick 2017 2,404 +1.5 -0.2 +1.3 4.8
Trevor Ariza 2017 3,186 +0.9 +0.4 +1.3 6.5
Reggie Jackson 2015 2,268 +2.0 -0.8 +1.3 4.6
C.J. Watson 2015 1,422 +0.1 +1.1 +1.3 2.9
Garrett Temple 2017 1,728 -0.7 +1.9 +1.3 3.5
Al Jefferson 2014 2,659 -0.6 +1.9 +1.3 5.4
Tobias Harris 2018 2,668 +1.9 -0.6 +1.2 5.4
Manu Ginobili 2018 1,406 +0.7 +0.5 +1.2 2.9
Lavoy Allen 2015 1,070 -0.4 +1.6 +1.2 2.2
Wesley Matthews 2016 2,817 +1.3 -0.1 +1.2 5.7
Robert Covington 2016 1,903 -0.7 +1.9 +1.2 3.9
Brook Lopez 2015 2,334 +0.4 +0.8 +1.2 4.7
Al-Farouq Aminu 2017 1,886 -2.2 +3.4 +1.2 3.8
Goran Dragic 2018 2,534 +1.4 -0.2 +1.2 5.1
Royce O’Neale 2018 1,409 -1.2 +2.4 +1.2 2.8
Alan Anderson 2015 1,886 -0.3 +1.5 +1.2 3.8
Andre Roberson 2016 2,024 -0.4 +1.6 +1.2 4.1
Jared Sullinger 2015 1,646 +0.7 +0.5 +1.2 3.3
Jayson Tatum 2018 3,121 +0.5 +0.7 +1.2 6.3
Maurice Harkless 2019 1,803 -0.1 +1.3 +1.2 3.6
Patrick Beverley 2015 1,727 +0.2 +1.0 +1.2 3.5
Thaddeus Young 2017 2,377 -1.1 +2.3 +1.2 4.8
Luol Deng 2016 2,889 +0.3 +0.9 +1.2 5.9
Tobias Harris 2016 2,669 +0.5 +0.6 +1.2 5.4
Wayne Ellington 2017 1,500 +1.7 -0.5 +1.2 3.0
Ricky Rubio 2018 2,435 -0.1 +1.3 +1.2 4.9
Nate Wolters 2014 1,309 -0.2 +1.3 +1.2 2.6
Jae Crowder 2016 2,505 +0.7 +0.4 +1.2 5.0
Roy Hibbert 2014 2,951 -1.9 +3.1 +1.2 5.8
Dwight Howard 2017 2,356 -1.6 +2.7 +1.2 4.7
Kyrie Irving 2014 2,496 +2.3 -1.2 +1.2 5.0
DeMarre Carroll 2017 2,037 -0.6 +1.7 +1.1 4.0
Allen Crabbe 2018 2,197 +1.0 +0.2 +1.1 4.4
David Lee 2014 2,505 +0.2 +1.0 +1.1 5.0
Mike Dunleavy 2015 2,227 +1.4 -0.3 +1.1 4.5
Deron Williams 2015 2,306 +1.1 -0.0 +1.1 4.6
Brook Lopez 2019 2,760 -0.5 +1.6 +1.1 5.6
Jeremy Lin 2014 2,231 -0.4 +1.5 +1.1 4.5
Dejounte Murray 2018 1,839 -2.1 +3.2 +1.1 3.6
Spencer Dinwiddie 2019 2,045 +1.9 -0.8 +1.1 4.0
Thabo Sefolosha 2016 1,961 -0.9 +2.0 +1.1 3.9
Nick Calathes 2014 1,173 -2.4 +3.5 +1.1 2.3
Nemanja Bjelica 2017 1,190 -0.8 +1.9 +1.1 2.3
JJ Redick 2019 2,755 +1.7 -0.6 +1.1 5.4
Reggie Jackson 2014 2,808 +0.6 +0.5 +1.1 5.5
Rodney Hood 2016 2,541 +2.1 -1.0 +1.1 4.9
Lou Williams 2019 2,169 +5.0 -3.9 +1.1 4.3
Pau Gasol 2015 2,998 +0.3 +0.8 +1.1 5.9
Tomas Satoransky 2018 1,703 +1.1 -0.0 +1.0 3.3
Marc Gasol 2016 1,791 -1.5 +2.6 +1.0 3.4
CJ McCollum 2018 3,078 +2.5 -1.5 +1.0 6.0
Shelvin Mack 2014 1,608 +1.3 -0.3 +1.0 3.1
Cody Zeller 2019 1,243 +0.5 +0.6 +1.0 2.4
Jusuf Nurkic 2015 1,103 -2.7 +3.8 +1.0 2.1
Kyle O’Quinn 2018 1,387 +0.5 +0.5 +1.0 2.7
Jared Sullinger 2016 1,996 -0.6 +1.6 +1.0 3.8
Lou Williams 2016 1,907 +3.2 -2.2 +1.0 3.7
Drew Gooden 2015 1,042 +0.0 +1.0 +1.0 2.0
Al Horford 2017 2,803 +1.0 -0.0 +1.0 5.4
Robert Covington 2015 1,956 +1.2 -0.2 +1.0 3.8
Michael Carter-Williams 2016 1,649 -1.4 +2.3 +1.0 3.2
Clint Capela 2017 1,837 -0.1 +1.1 +1.0 3.5
Wilson Chandler 2017 2,197 +0.5 +0.5 +1.0 4.2
Corey Brewer 2014 2,609 +0.3 +0.7 +1.0 5.0
Chris Bosh 2014 3,217 +0.1 +0.8 +1.0 6.1
Jayson Tatum 2019 2,750 +0.4 +0.6 +1.0 5.2
Hassan Whiteside 2017 2,513 -0.8 +1.7 +1.0 4.7
Kyrie Irving 2016 2,441 +3.8 -2.9 +1.0 4.7
Aaron Gordon 2016 1,863 +0.9 +0.0 +0.9 3.5
Blake Griffin 2016 1,297 +0.6 +0.3 +0.9 2.5
Al-Farouq Aminu 2019 2,691 +0.3 +0.6 +0.9 5.0
Lucas Nogueira 2017 1,095 -1.5 +2.4 +0.9 2.1
Nene 2014 1,885 -2.5 +3.4 +0.9 3.5
Tristan Thompson 2015 2,921 +0.3 +0.6 +0.9 5.5
Paul Pierce 2015 2,212 +1.4 -0.4 +0.9 4.2
Patrick Patterson 2016 2,603 +0.7 +0.2 +0.9 4.8
Michael Kidd-Gilchrist 2019 1,179 -1.1 +2.0 +0.9 2.2
Jrue Holiday 2017 2,190 +0.6 +0.2 +0.9 4.1
Nene 2016 1,094 -2.3 +3.2 +0.9 2.1
Jerami Grant 2019 2,788 -0.3 +1.2 +0.9 5.2
Vince Carter 2017 1,994 +1.0 -0.1 +0.9 3.6
Luol Deng 2014 2,213 +0.3 +0.6 +0.9 4.1
Nick Young 2014 1,810 +2.4 -1.5 +0.9 3.4
Elfrid Payton 2017 2,412 +1.8 -0.9 +0.9 4.5
Devin Harris 2018 1,340 +1.6 -0.7 +0.9 2.5
Josh Hart 2019 1,715 -2.1 +3.0 +0.9 3.2
Chris Bosh 2016 1,778 +0.7 +0.2 +0.9 3.3
Will Barton 2018 2,683 +1.3 -0.4 +0.9 4.9
Andray Blatche 2014 1,790 -0.7 +1.6 +0.9 3.3
Aaron Gordon 2017 2,298 +1.1 -0.3 +0.9 4.2
Reggie Jackson 2018 1,201 +1.5 -0.7 +0.9 2.2
Cory Joseph 2015 1,466 +0.6 +0.2 +0.9 2.7
Dirk Nowitzki 2015 2,463 +2.1 -1.3 +0.9 4.5
Thaddeus Young 2015 2,624 +0.3 +0.6 +0.8 4.8
Tyreke Evans 2015 2,815 +2.4 -1.6 +0.8 5.1
Eric Bledsoe 2017 2,176 +3.2 -2.4 +0.8 4.0
Joe Johnson 2014 3,044 +3.1 -2.2 +0.8 5.6
Enes Kanter 2017 1,578 +1.7 -0.9 +0.8 2.9
Chandler Parsons 2016 1,799 +0.9 -0.1 +0.8 3.3
Trey Lyles 2018 1,391 +0.7 +0.1 +0.8 2.5
Al-Farouq Aminu 2016 2,713 -0.4 +1.2 +0.8 5.0
Matthew Dellavedova 2016 2,108 +0.4 +0.4 +0.8 3.8
Bam Adebayo 2019 1,913 -1.9 +2.7 +0.8 3.5
PJ Tucker 2015 2,383 -0.5 +1.3 +0.8 4.3
Rondae Hollis-Jefferson 2018 1,920 -0.3 +1.1 +0.8 3.5
Marcus Smart 2017 2,937 -1.1 +1.9 +0.8 5.4
PJ Tucker 2019 3,228 -1.2 +2.0 +0.8 5.9
Omri Casspi 2014 1,283 -0.5 +1.3 +0.8 2.3
Taj Gibson 2018 2,849 +0.1 +0.7 +0.8 5.1
Nerlens Noel 2017 1,047 -1.3 +2.0 +0.8 1.9
Darren Collison 2019 2,260 +0.7 +0.1 +0.8 4.0
Jose Calderon 2018 1,018 -0.2 +1.0 +0.8 1.8
Andre Drummond 2016 2,797 -0.9 +1.7 +0.8 5.0
Andre Iguodala 2018 2,023 -0.9 +1.7 +0.8 3.7
Yogi Ferrell 2019 1,067 +0.8 -0.1 +0.8 1.9
Gorgui Dieng 2017 2,653 -0.8 +1.6 +0.8 4.7
Elfrid Payton 2015 2,489 +0.5 +0.2 +0.8 4.5
Mario Chalmers 2015 2,368 -0.8 +1.5 +0.8 4.2
Kelly Olynyk 2019 1,812 +0.1 +0.7 +0.8 3.2
Nikola Vucevic 2016 2,037 +0.3 +0.5 +0.8 3.6
Ed Davis 2018 1,542 -0.6 +1.3 +0.8 2.7
Jonas Valanciunas 2015 2,202 -0.1 +0.9 +0.7 3.9
Kent Bazemore 2016 2,408 -0.3 +1.1 +0.7 4.3
Jeremy Lamb 2014 1,638 +0.5 +0.2 +0.7 2.9
Zaza Pachulia 2017 1,480 -0.8 +1.6 +0.7 2.7
Patty Mills 2017 2,170 +1.6 -0.8 +0.7 3.9
Amir Johnson 2014 2,405 -0.4 +1.1 +0.7 4.3
Ed Davis 2019 1,487 -0.7 +1.5 +0.7 2.6
OG Anunoby 2018 1,719 -0.7 +1.4 +0.7 3.1
Eric Gordon 2018 2,703 +2.2 -1.5 +0.7 4.8
Andre Iguodala 2017 2,417 -0.2 +0.9 +0.7 4.2
Gordon Hayward 2016 2,893 +1.6 -0.9 +0.7 5.1
Tony Allen 2016 1,714 -1.0 +1.7 +0.7 3.0
Tristan Thompson 2019 1,198 -0.2 +1.0 +0.7 2.1
Carmelo Anthony 2016 2,530 +3.5 -2.7 +0.7 4.5
Avery Bradley 2016 2,569 +1.3 -0.6 +0.7 4.6
Trevor Booker 2016 1,632 -0.9 +1.6 +0.7 2.9
Luis Scola 2015 1,659 +0.1 +0.6 +0.7 2.9
Wesley Matthews 2017 2,495 -0.3 +0.9 +0.7 4.4
Trevor Booker 2015 1,564 -0.2 +0.9 +0.7 2.7
Langston Galloway 2016 2,033 -0.8 +1.5 +0.7 3.6
Randy Foye 2014 2,485 +2.1 -1.4 +0.7 4.4
Goran Dragic 2017 2,459 +2.5 -1.8 +0.7 4.3
PJ Tucker 2017 2,487 -1.1 +1.7 +0.7 4.4
Iman Shumpert 2014 1,962 -0.4 +1.0 +0.7 3.4
Langston Galloway 2015 1,457 -0.7 +1.3 +0.7 2.5
Andrew Wiggins 2017 3,048 +1.4 -0.8 +0.7 5.4
Jamal Murray 2018 2,565 +2.3 -1.7 +0.7 4.5
Kyle O’Quinn 2017 1,229 +0.4 +0.3 +0.7 2.1
Greivis Vasquez 2014 1,969 +0.4 +0.2 +0.7 3.4
Tim Hardaway Jr. 2017 2,354 +1.8 -1.1 +0.7 4.1
Terrence Ross 2019 2,296 +1.0 -0.3 +0.7 4.0
C.J. Watson 2014 1,535 -1.5 +2.1 +0.7 2.6
Amar’e Stoudemire 2015 1,320 +0.7 -0.0 +0.7 2.3
Bismack Biyombo 2016 2,314 -2.1 +2.8 +0.7 4.1
Kenneth Faried 2017 1,296 +1.1 -0.4 +0.6 2.2
Donovan Mitchell 2019 2,791 +1.7 -1.1 +0.6 4.8
Garrett Temple 2016 1,951 -1.3 +2.0 +0.6 3.4
Gordon Hayward 2014 2,800 +0.7 -0.1 +0.6 4.9
Dario Saric 2018 2,639 +1.1 -0.5 +0.6 4.6
George Hill 2018 2,369 +0.4 +0.2 +0.6 4.0
Nikola Mirotic 2016 1,646 +0.7 -0.1 +0.6 2.8
Nene 2015 1,950 -2.4 +3.0 +0.6 3.4
Terrence Ross 2016 2,082 +0.5 +0.1 +0.6 3.5
Rudy Gay 2014 2,531 +1.1 -0.5 +0.6 4.3
Eric Gordon 2017 2,681 +1.7 -1.1 +0.6 4.7
Devin Booker 2019 2,242 +3.6 -3.0 +0.6 3.9
Yogi Ferrell 2018 2,282 -0.6 +1.2 +0.6 3.8
Kent Bazemore 2018 1,789 -0.1 +0.7 +0.6 3.1
Tristan Thompson 2017 2,898 -1.0 +1.6 +0.6 4.9
Brandan Wright 2014 1,167 +1.9 -1.3 +0.6 2.0
Lonzo Ball 2018 1,780 -0.9 +1.4 +0.6 3.0
Andre Iguodala 2016 2,499 +0.5 +0.1 +0.6 4.2
Thabo Sefolosha 2017 1,605 -1.7 +2.2 +0.6 2.7
Robin Lopez 2015 1,755 -0.9 +1.5 +0.5 2.9
Kosta Koufos 2015 1,475 -2.6 +3.1 +0.5 2.5
Maurice Harkless 2017 2,322 +0.2 +0.4 +0.5 3.9
Samuel Dalembert 2014 1,749 -1.9 +2.4 +0.5 2.9
Amir Johnson 2015 2,091 +0.1 +0.5 +0.5 3.5
Kosta Koufos 2014 1,394 -1.6 +2.1 +0.5 2.3
Giannis Antetokounmpo 2016 2,823 +0.8 -0.2 +0.5 4.7
Thaddeus Young 2016 2,407 +0.1 +0.5 +0.5 4.0
Josh Smith 2015 2,696 -1.7 +2.2 +0.5 4.5
Jonathan Isaac 2019 2,133 -1.0 +1.5 +0.5 3.5
Wilson Chandler 2014 1,927 +0.5 +0.0 +0.5 3.2
Courtney Lee 2016 2,591 -0.4 +0.9 +0.5 4.3
Tim Hardaway Jr. 2019 2,057 +1.2 -0.7 +0.5 3.4
Kenneth Faried 2015 2,086 +0.6 -0.1 +0.5 3.5
Kentavious Caldwell-Pope 2019 2,035 +0.8 -0.3 +0.5 3.4
Gordon Hayward 2019 2,130 +0.5 +0.0 +0.5 3.6
Nick Young 2017 1,556 +2.0 -1.5 +0.5 2.6
Pablo Prigioni 2015 1,490 -0.6 +1.1 +0.5 2.5
Patrick Patterson 2014 1,732 -0.2 +0.7 +0.5 2.9
Vince Carter 2018 1,026 -0.5 +1.0 +0.5 1.7
Shelvin Mack 2016 1,058 -0.4 +0.9 +0.5 1.8
Jeremy Lamb 2017 1,143 +2.1 -1.6 +0.5 1.9
Josh Richardson 2017 1,614 -1.6 +2.1 +0.5 2.6
Nikola Vucevic 2017 2,163 -1.5 +2.0 +0.5 3.6
Jae Crowder 2019 2,296 -0.1 +0.6 +0.5 3.8
Mirza Teletovic 2016 1,686 +2.2 -1.7 +0.5 2.8
Omer Asik 2015 2,061 -2.0 +2.5 +0.5 3.3
Pascal Siakam 2018 1,858 +0.2 +0.3 +0.4 3.0
Landry Shamet 2019 1,976 +1.0 -0.5 +0.4 3.2
Corey Brewer 2018 1,359 -1.1 +1.6 +0.4 2.2
Otto Porter Jr. 2016 2,276 +0.4 +0.0 +0.4 3.7
Marreese Speights 2017 1,384 +0.3 +0.1 +0.4 2.3
T.J. McConnell 2018 1,861 -1.2 +1.6 +0.4 3.1
Tyreke Evans 2014 2,028 +1.2 -0.8 +0.4 3.3
Dwyane Wade 2014 2,468 +1.1 -0.7 +0.4 4.0
Kirk Hinrich 2014 2,283 -1.6 +2.0 +0.4 3.7
Nicolas Batum 2015 2,589 +0.6 -0.2 +0.4 4.2
Marc Gasol 2018 2,408 -1.3 +1.7 +0.4 3.9
Marvin Williams 2018 2,006 +0.3 +0.1 +0.4 3.2
Anthony Morrow 2014 1,426 +1.3 -0.9 +0.4 2.3
Rondae Hollis-Jefferson 2019 1,296 -2.4 +2.8 +0.4 2.1
Nerlens Noel 2019 1,115 -2.8 +3.1 +0.4 1.8
Aaron Gordon 2019 2,797 +0.1 +0.3 +0.4 4.4
Omri Casspi 2016 1,880 +1.6 -1.2 +0.4 3.0
Reggie Bullock 2018 1,732 +0.6 -0.2 +0.4 2.8
Jerian Grant 2017 1,080 +0.5 -0.1 +0.4 1.7
Fred VanVleet 2019 2,352 +0.9 -0.6 +0.3 3.7
Mike Dunleavy 2014 2,747 +0.4 -0.1 +0.3 4.3
Kentavious Caldwell-Pope 2015 2,587 +0.8 -0.4 +0.3 4.1
Shaquille Harrison 2019 1,430 -1.4 +1.8 +0.3 2.2
Thabo Sefolosha 2014 1,820 -1.9 +2.2 +0.3 2.9
Jason Terry 2015 2,128 +0.6 -0.2 +0.3 3.4
Tyus Jones 2019 1,560 +0.2 +0.1 +0.3 2.4
Cody Zeller 2016 1,911 -1.0 +1.3 +0.3 3.0
Boris Diaw 2016 1,545 -0.1 +0.4 +0.3 2.4
Royce O’Neale 2019 1,808 -2.2 +2.5 +0.3 2.9
Rondae Hollis-Jefferson 2017 1,761 -1.8 +2.1 +0.3 2.8
DeMarre Carroll 2018 2,180 -0.1 +0.5 +0.3 3.4
Goran Dragic 2015 2,640 +1.9 -1.6 +0.3 4.2
PJ Tucker 2018 2,850 -0.4 +0.7 +0.3 4.5
Josh Okogie 2019 1,757 -1.3 +1.7 +0.3 2.8
Tyler Johnson 2018 2,133 +0.2 +0.1 +0.3 3.3
Rodney Stuckey 2015 1,874 +0.5 -0.2 +0.3 2.9
Kristaps Porzingis 2017 2,164 -1.3 +1.6 +0.3 3.4
Tobias Harris 2019 3,290 +0.9 -0.6 +0.3 5.1
Brandon Knight 2015 2,035 +0.5 -0.2 +0.3 3.2
Marvin Williams 2017 2,295 -0.3 +0.6 +0.3 3.5
Pat Connaughton 2019 1,585 -0.2 +0.5 +0.3 2.5
Zach Randolph 2017 1,977 -0.1 +0.4 +0.3 3.0
Luc Mbah a Moute 2016 1,352 -3.2 +3.5 +0.3 2.1
DeMar DeRozan 2014 3,299 +1.9 -1.6 +0.3 5.0
Raul Neto 2016 1,499 -1.2 +1.5 +0.3 2.3
Dewayne Dedmon 2019 1,609 -0.9 +1.1 +0.3 2.5
Ryan Anderson 2017 2,452 +0.7 -0.4 +0.2 3.7
Anthony Tolliver 2014 1,319 +0.6 -0.3 +0.2 2.0
Kentavious Caldwell-Pope 2018 2,458 +0.8 -0.5 +0.2 3.8
Dwight Powell 2016 1,056 -2.1 +2.4 +0.2 1.6
Mitchell Robinson 2019 1,360 -0.7 +0.9 +0.2 2.1
Alec Burks 2014 2,193 +0.9 -0.7 +0.2 3.3
Aron Baynes 2018 1,874 -3.0 +3.2 +0.2 2.8
Nicolas Batum 2017 2,617 +0.9 -0.7 +0.2 4.0
Ray Allen 2014 2,463 +1.8 -1.6 +0.2 3.8
Shelvin Mack 2018 1,365 +0.0 +0.2 +0.2 2.0
Dirk Nowitzki 2018 1,900 +0.6 -0.4 +0.2 2.9
Marcus Morris 2016 3,000 +0.9 -0.7 +0.2 4.5
Cory Joseph 2014 1,023 +0.6 -0.4 +0.2 1.5
Terrence Ross 2014 2,317 +0.2 -0.0 +0.2 3.5
Kyle Anderson 2019 1,281 -2.0 +2.2 +0.2 1.9
Seth Curry 2019 1,725 -0.4 +0.6 +0.2 2.6
DeMar DeRozan 2017 2,993 +2.1 -1.9 +0.2 4.5
Troy Daniels 2017 1,251 +1.3 -1.1 +0.2 1.9
Lauri Markkanen 2019 1,682 +1.0 -0.8 +0.2 2.5
DeMar DeRozan 2019 2,939 +1.3 -1.1 +0.2 4.4
Mikal Bridges 2019 2,417 -0.9 +1.1 +0.2 3.6
PJ Tucker 2016 2,540 -0.8 +0.9 +0.2 3.8
Jerian Grant 2018 1,686 +1.0 -0.9 +0.2 2.5
Dennis Schroder 2018 2,078 +1.6 -1.4 +0.2 3.1
Taj Gibson 2014 2,505 -1.0 +1.2 +0.2 3.8
Devin Harris 2016 1,401 +0.2 -0.1 +0.2 2.1
Patty Mills 2019 2,060 +1.1 -0.9 +0.2 3.1
Norman Powell 2017 1,595 +0.2 -0.0 +0.2 2.4
Hassan Whiteside 2018 1,441 -2.2 +2.4 +0.2 2.2
Joe Harris 2018 1,975 +1.3 -1.1 +0.2 2.9
Justin Holiday 2018 2,265 -0.9 +1.1 +0.2 3.4
James Johnson 2018 2,104 +0.2 -0.0 +0.2 3.1
Steven Adams 2017 2,546 -1.6 +1.8 +0.1 3.8
Gerald Green 2015 1,446 +2.2 -2.0 +0.1 2.2
Gerald Henderson 2015 2,315 -1.0 +1.1 +0.1 3.4
Shaun Livingston 2014 2,299 -0.0 +0.1 +0.1 3.3
CJ Miles 2017 1,858 +1.5 -1.4 +0.1 2.7
Nikola Vucevic 2014 1,812 -0.8 +0.9 +0.1 2.7
Greg Monroe 2015 2,137 -0.1 +0.2 +0.1 3.1
Jamal Crawford 2014 2,407 +2.8 -2.7 +0.1 3.6
Steven Adams 2015 1,771 -1.9 +2.0 +0.1 2.6
Kent Bazemore 2017 2,113 -1.4 +1.5 +0.1 3.1
Rajon Rondo 2018 2,007 +1.9 -1.8 +0.1 3.0
Gary Harris 2019 2,156 -0.4 +0.5 +0.1 3.2
Wesley Johnson 2016 1,743 -2.1 +2.2 +0.1 2.6
Ryan Anderson 2018 1,820 -0.1 +0.2 +0.1 2.7
Michael Carter-Williams 2014 2,414 -0.5 +0.6 +0.1 3.6
CJ Miles 2018 1,564 +1.1 -1.0 +0.1 2.3
Myles Turner 2019 2,245 -1.9 +2.0 +0.1 3.3
Jaren Jackson Jr. 2019 1,515 -1.7 +1.8 +0.1 2.2
Darren Collison 2016 2,219 +1.8 -1.7 +0.1 3.2
Marvin Williams 2015 2,035 -0.8 +0.9 +0.1 3.0
Andre Drummond 2018 2,625 -0.6 +0.7 +0.1 3.8
Ian Mahinmi 2016 1,988 -2.7 +2.8 +0.1 2.8
Jose Calderon 2016 2,024 +0.6 -0.5 +0.1 2.9
Brook Lopez 2017 2,222 -0.1 +0.2 +0.1 3.2
Gerald Green 2016 1,667 -0.7 +0.7 +0.1 2.4
Jusuf Nurkic 2018 2,182 -2.0 +2.1 +0.1 3.2
Donatas Motiejunas 2015 2,037 -0.7 +0.8 +0.1 2.9
Ryan Anderson 2015 1,770 +1.7 -1.7 +0.1 2.5
Mason Plumlee 2017 2,148 -0.1 +0.1 +0.0 3.1
Greg Monroe 2014 2,690 +0.3 -0.3 +0.0 3.8
Jerami Grant 2018 1,780 -0.9 +1.0 +0.0 2.5
Justise Winslow 2018 1,805 -1.7 +1.7 +0.0 2.6
Spencer Dinwiddie 2017 1,334 +0.7 -0.7 +0.0 1.9
Noah Vonleh 2019 1,722 -0.9 +0.9 +0.0 2.4
Cory Joseph 2016 2,498 -1.3 +1.3 +0.0 3.5
Serge Ibaka 2019 2,510 -1.2 +1.2 +0.0 3.6
Matt Barnes 2014 2,139 +0.7 -0.6 +0.0 3.1
Bojan Bogdanovic 2019 2,721 +0.6 -0.6 +0.0 3.8
Enes Kanter 2019 2,101 +0.7 -0.7 +0.0 3.0
Avery Bradley 2014 1,855 -0.9 +0.9 -0.0 2.6
Otto Porter Jr. 2015 1,763 -0.1 +0.1 -0.0 2.5
Joe Harris 2019 2,442 +0.7 -0.7 -0.0 3.4
Kris Humphries 2015 1,350 -1.4 +1.4 -0.0 1.9
Marco Belinelli 2014 2,372 +2.1 -2.1 -0.0 3.3
E’Twaun Moore 2014 1,506 -1.0 +1.0 -0.0 2.1
Nick Young 2015 1,000 +1.8 -1.8 -0.0 1.4
Dwyane Wade 2016 2,731 +1.9 -1.9 -0.0 3.8
Jeff Teague 2019 1,264 +1.0 -1.0 -0.0 1.8
Monta Ellis 2014 3,272 +0.8 -0.9 -0.0 4.6
Enes Kanter 2018 1,830 +2.1 -2.2 -0.0 2.5
Larry Nance Jr. 2016 1,266 -1.0 +1.0 -0.0 1.7
Jordan Clarkson 2019 2,214 +2.0 -2.1 -0.0 3.0
Zach Randolph 2014 2,939 +0.8 -0.9 -0.0 4.0
Jusuf Nurkic 2017 1,408 -2.7 +2.6 -0.0 2.0
Tony Snell 2015 1,552 -0.2 +0.2 -0.0 2.1
Josh Richardson 2016 1,494 -0.1 +0.1 -0.0 2.0
Tyler Zeller 2015 1,821 -0.5 +0.5 -0.1 2.5
Alex Len 2015 1,518 -2.6 +2.5 -0.1 2.1
Joe Johnson 2017 2,169 +1.0 -1.1 -0.1 2.9
Andre Miller 2014 1,090 +1.0 -1.0 -0.1 1.4
Kentavious Caldwell-Pope 2017 2,529 +0.7 -0.7 -0.1 3.5
Anthony Tolliver 2016 1,367 +0.0 -0.1 -0.1 1.9
Ben Simmons 2019 3,121 +0.8 -0.9 -0.1 4.4
E’Twaun Moore 2016 1,263 -0.3 +0.3 -0.1 1.7
Kyle O’Quinn 2014 1,188 -1.7 +1.6 -0.1 1.6
Pau Gasol 2018 1,902 -0.9 +0.9 -0.1 2.6
D.J. Augustin 2018 1,760 +0.4 -0.5 -0.1 2.4
Pero Antic 2015 1,236 -1.3 +1.3 -0.1 1.7
Justise Winslow 2019 1,959 -0.4 +0.3 -0.1 2.7
Dwyane Wade 2017 1,982 +0.2 -0.3 -0.1 2.7
Julius Randle 2018 2,190 +0.2 -0.3 -0.1 3.0
Torrey Craig 2019 1,833 -0.2 +0.1 -0.1 2.5
Gerald Green 2014 2,330 +1.3 -1.3 -0.1 3.2
Justin Holiday 2017 1,639 -0.7 +0.6 -0.1 2.2
Markieff Morris 2017 2,747 -1.7 +1.6 -0.1 3.8
T.J. McConnell 2016 1,606 -0.2 +0.1 -0.1 2.2
JaMychal Green 2017 2,219 -0.4 +0.3 -0.1 3.0
Kelly Oubre Jr. 2019 1,935 -0.6 +0.5 -0.1 2.6
Aron Baynes 2015 1,162 -1.8 +1.7 -0.1 1.6
Danuel House Jr. 2019 1,120 +0.6 -0.7 -0.1 1.5
Tony Parker 2014 2,716 +0.9 -1.0 -0.1 3.6
Mirza Teletovic 2014 1,616 +1.8 -1.9 -0.1 2.2
Lauri Markkanen 2018 2,020 +0.1 -0.2 -0.1 2.7
D.J. Augustin 2019 2,410 +2.3 -2.4 -0.1 3.2
Zaza Pachulia 2016 2,116 -1.6 +1.5 -0.1 2.8
Darrell Arthur 2016 1,516 -1.9 +1.8 -0.1 2.0
D.J. Augustin 2014 2,080 +2.0 -2.1 -0.1 2.7
Corey Brewer 2015 2,515 -0.5 +0.4 -0.1 3.4
Jeff Teague 2014 2,784 +0.4 -0.5 -0.1 3.7
Marcus Morris 2015 2,045 +1.0 -1.2 -0.1 2.7
Chris Bosh 2015 1,556 -0.5 +0.4 -0.1 2.1
T.J. Warren 2017 2,048 +0.9 -1.1 -0.1 2.7
Jeff Teague 2016 2,534 +0.9 -1.0 -0.2 3.4
Evan Fournier 2017 2,234 +0.2 -0.4 -0.2 3.0
Wayne Ellington 2015 1,675 +0.3 -0.5 -0.2 2.2
Ersan Ilyasova 2016 1,881 +0.0 -0.2 -0.2 2.5
Rodney Hood 2019 2,266 +0.4 -0.5 -0.2 3.0
Spencer Hawes 2014 2,470 -0.7 +0.5 -0.2 3.3
Timofey Mozgov 2014 1,770 -1.3 +1.1 -0.2 2.3
Klay Thompson 2019 3,470 +0.7 -0.9 -0.2 4.5
Marcus Morris 2014 1,800 +0.2 -0.4 -0.2 2.4
Cody Zeller 2017 1,725 -1.6 +1.4 -0.2 2.2
CJ Miles 2016 1,556 +0.7 -0.9 -0.2 2.0
Evan Fournier 2019 2,728 +0.4 -0.6 -0.2 3.5
Derrick Rose 2017 2,082 +1.2 -1.4 -0.2 2.7
Tyreke Evans 2019 1,486 -0.6 +0.4 -0.2 1.9
Markieff Morris 2015 2,581 -1.1 +0.9 -0.2 3.4
Robin Lopez 2016 2,219 -0.1 -0.2 -0.2 2.8
Mo Williams 2015 1,980 +1.2 -1.4 -0.2 2.6
Dorell Wright 2014 1,072 -0.3 +0.0 -0.2 1.4
JR Smith 2017 1,674 +0.2 -0.4 -0.2 2.2
Andrew Wiggins 2016 2,845 +0.5 -0.8 -0.2 3.7
Evan Fournier 2016 2,566 +1.7 -1.9 -0.2 3.3
Ian Mahinmi 2014 1,489 -3.9 +3.6 -0.2 1.9
Tomas Satoransky 2019 2,164 +0.3 -0.6 -0.2 2.8
Harrison Barnes 2017 2,803 -1.3 +1.1 -0.2 3.6
Ben McLemore 2015 2,670 +0.2 -0.4 -0.2 3.4
Evan Fournier 2018 1,837 +1.8 -2.1 -0.3 2.4
Bojan Bogdanovic 2018 2,702 -0.2 -0.1 -0.3 3.5
Tyson Chandler 2014 1,662 -1.3 +1.1 -0.3 2.1
Ronnie Price 2016 1,211 -1.7 +1.5 -0.3 1.5
Garrett Temple 2018 1,615 -1.5 +1.2 -0.3 2.0
Jonas Jerebko 2018 1,213 +0.6 -0.9 -0.3 1.5
Allen Crabbe 2016 2,407 +0.8 -1.1 -0.3 3.1
Paul Millsap 2018 1,143 -0.5 +0.2 -0.3 1.4
Iman Shumpert 2016 1,683 -1.3 +1.0 -0.3 2.1
Luke Babbitt 2017 1,065 -0.5 +0.2 -0.3 1.3
Gorgui Dieng 2016 2,220 -0.7 +0.4 -0.3 2.7
T.J. Warren 2019 1,360 +0.9 -1.2 -0.3 1.7
Jordan Clarkson 2018 2,174 +0.4 -0.7 -0.3 2.6
Lonzo Ball 2019 1,423 -1.1 +0.8 -0.3 1.8
Mason Plumlee 2016 2,390 -0.1 -0.2 -0.3 3.0
Omer Asik 2014 1,131 -2.3 +2.0 -0.3 1.4
Bruce Brown 2019 1,506 -2.7 +2.4 -0.3 1.8
Ian Mahinmi 2015 1,146 -2.8 +2.4 -0.3 1.4
LaMarcus Aldridge 2017 2,872 -1.4 +1.1 -0.3 3.4
Andre Drummond 2015 2,502 -0.8 +0.4 -0.3 3.1
Kyle Singler 2014 2,337 -0.0 -0.3 -0.3 2.9
Will Barton 2016 2,353 +0.2 -0.6 -0.4 2.9
James Ennis III 2018 1,604 -1.2 +0.9 -0.4 2.0
T.J. Warren 2018 2,142 +0.1 -0.5 -0.4 2.6
Ish Smith 2014 1,006 -1.0 +0.7 -0.4 1.2
Jose Calderon 2014 2,659 +1.9 -2.2 -0.4 3.2
Iman Shumpert 2019 1,590 -1.3 +0.9 -0.4 1.9
Roy Hibbert 2015 1,926 -2.3 +2.0 -0.4 2.3
Rodney Stuckey 2016 1,400 -0.4 +0.0 -0.4 1.7
Malcolm Brogdon 2018 1,622 +0.6 -1.0 -0.4 1.9
Dorian Finney-Smith 2019 1,985 -2.1 +1.7 -0.4 2.4
Monta Ellis 2016 2,959 -0.5 +0.1 -0.4 3.5
Dewayne Dedmon 2018 1,542 -1.5 +1.1 -0.4 1.8
Brandon Bass 2016 1,342 -0.0 -0.4 -0.4 1.6
Pat Connaughton 2018 1,547 -0.5 +0.1 -0.4 1.8
Marcus Thornton 2014 1,865 +0.7 -1.1 -0.4 2.2
Trevor Ariza 2018 2,851 +0.2 -0.6 -0.4 3.4
Marcin Gortat 2018 2,235 -1.8 +1.3 -0.4 2.6
Rajon Rondo 2017 1,910 -0.5 +0.0 -0.4 2.3
Lance Stephenson 2014 3,457 +0.4 -0.8 -0.4 4.1
Nikola Vucevic 2018 1,683 -0.9 +0.4 -0.5 2.0
Rudy Gay 2016 2,379 -0.3 -0.2 -0.5 2.8
Taj Gibson 2016 1,936 -0.7 +0.2 -0.5 2.2
Vince Carter 2016 1,096 +1.5 -1.9 -0.5 1.3
Dwyane Wade 2015 1,971 +2.0 -2.5 -0.5 2.3
Harrison Barnes 2015 2,999 -0.6 +0.1 -0.5 3.5
Patty Mills 2018 2,272 +0.8 -1.3 -0.5 2.6
Ryan Arcidiacono 2019 1,961 -0.1 -0.4 -0.5 2.2
Sam Dekker 2017 1,450 -0.5 +0.0 -0.5 1.7
Marcus Morris 2017 2,565 -0.7 +0.2 -0.5 2.9
Rajon Rondo 2016 2,537 +1.0 -1.5 -0.5 2.9
Luke Kennard 2018 1,463 +0.2 -0.7 -0.5 1.7
Pero Antic 2014 1,095 -1.2 +0.7 -0.5 1.3
Derrick Favors 2014 2,201 -1.0 +0.4 -0.5 2.5
Jon Leuer 2016 1,255 -0.9 +0.3 -0.5 1.4
Gerald Wallace 2014 1,416 -2.1 +1.6 -0.5 1.6
Raymond Felton 2014 2,017 +0.0 -0.6 -0.5 2.3
Jared Dudley 2014 1,774 -0.6 +0.1 -0.5 2.0
John Collins 2018 1,785 -1.1 +0.5 -0.5 2.0
Montrezl Harrell 2017 1,085 +0.7 -1.3 -0.5 1.2
Ivica Zubac 2019 1,079 -2.4 +1.8 -0.5 1.2
Kenrich Williams 2019 1,079 -1.3 +0.7 -0.5 1.2
Wilson Chandler 2018 2,346 -0.7 +0.1 -0.6 2.6
Ty Lawson 2017 1,732 +0.2 -0.7 -0.6 1.9
Jodie Meeks 2014 2,556 +0.7 -1.3 -0.6 2.9
E’Twaun Moore 2017 1,820 +0.2 -0.8 -0.6 2.0
Brook Lopez 2018 1,735 -0.7 +0.1 -0.6 1.9
Maxi Kleber 2018 1,206 -2.1 +1.5 -0.6 1.3
Jalen Brunson 2019 1,591 +0.0 -0.6 -0.6 1.8
DeJuan Blair 2014 1,295 -1.1 +0.6 -0.6 1.5
Rodney Hood 2015 1,064 +0.6 -1.2 -0.6 1.2
Avery Bradley 2017 2,480 -0.2 -0.4 -0.6 2.7
Iman Shumpert 2017 2,212 -1.4 +0.8 -0.6 2.4
Maurice Harkless 2016 1,729 -0.4 -0.2 -0.6 1.9
Willie Cauley-Stein 2019 2,213 -2.1 +1.5 -0.6 2.4
Alex Abrines 2017 1,135 +0.5 -1.1 -0.6 1.2
Jonas Valanciunas 2017 2,292 +0.1 -0.7 -0.6 2.5
Justise Winslow 2016 2,562 -2.3 +1.7 -0.6 2.8
Devin Booker 2018 1,865 +2.5 -3.1 -0.6 2.1
Jamal Murray 2017 1,764 -0.2 -0.4 -0.6 1.9
Andrew Wiggins 2018 3,143 -0.8 +0.2 -0.6 3.4
Jeff Green 2018 2,351 -0.7 +0.1 -0.6 2.5
Vince Carter 2015 1,287 +0.0 -0.7 -0.6 1.4
Solomon Hill 2017 2,374 -1.8 +1.2 -0.6 2.6
Raymond Felton 2016 2,364 -0.4 -0.2 -0.6 2.6
Ian Mahinmi 2018 1,197 -2.2 +1.5 -0.6 1.3
Gorgui Dieng 2019 1,031 -1.3 +0.7 -0.6 1.1
Marcus Thornton 2016 1,109 +1.3 -2.0 -0.6 1.2
Wayne Ellington 2019 1,428 -0.2 -0.4 -0.6 1.6
Mario Hezonja 2018 1,657 -0.8 +0.2 -0.6 1.8
Spencer Hawes 2016 1,088 -2.7 +2.0 -0.6 1.2
Juancho Hernangomez 2019 1,373 -1.5 +0.8 -0.7 1.5
Markieff Morris 2014 2,153 -0.0 -0.6 -0.7 2.3
Greg Monroe 2018 1,145 -0.8 +0.1 -0.7 1.2
Kevin Garnett 2014 1,359 -3.7 +3.0 -0.7 1.4
Kentavious Caldwell-Pope 2014 1,583 -0.9 +0.2 -0.7 1.7
Sindarius Thornwell 2018 1,156 -2.5 +1.8 -0.7 1.2
Victor Oladipo 2015 2,573 +0.5 -1.1 -0.7 2.7
Brandon Jennings 2014 2,728 +2.2 -2.8 -0.7 2.9
Darren Collison 2017 2,063 +1.1 -1.7 -0.7 2.1
Nemanja Bjelica 2016 1,075 +0.2 -0.9 -0.7 1.1
Brian Roberts 2015 1,330 -0.4 -0.3 -0.7 1.4
Khris Middleton 2014 2,460 +0.2 -0.9 -0.7 2.6
Evan Turner 2016 2,485 -1.6 +0.9 -0.7 2.6
Mike Muscala 2017 1,318 -1.2 +0.5 -0.7 1.4
Jerryd Bayless 2016 1,505 +0.2 -0.9 -0.7 1.5
Joe Johnson 2016 3,195 +1.0 -1.7 -0.7 3.3
Wilson Chandler 2015 2,471 +0.8 -1.6 -0.7 2.5
Andrei Kirilenko 2014 1,001 -0.8 +0.1 -0.7 1.1
Victor Oladipo 2014 2,487 -3.2 +2.4 -0.7 2.6
Terrence Jones 2014 2,216 +0.8 -1.6 -0.7 2.3
Markieff Morris 2016 1,629 -2.8 +2.1 -0.7 1.7
Reggie Jackson 2019 2,397 +1.7 -2.4 -0.7 2.4
Trevor Ariza 2016 3,040 +0.2 -0.9 -0.7 3.1
Jeff Green 2019 2,097 +0.2 -0.9 -0.8 2.1
Wesley Johnson 2018 1,486 -2.9 +2.1 -0.8 1.5
Bradley Beal 2016 1,708 +0.7 -1.4 -0.8 1.7
Jodie Meeks 2015 1,462 -0.1 -0.6 -0.8 1.5
Aaron Brooks 2016 1,108 +0.2 -0.9 -0.8 1.1
Malik Beasley 2019 2,160 +0.4 -1.2 -0.8 2.2
Terry Rozier 2017 1,540 -1.3 +0.5 -0.8 1.6
Elton Brand 2014 1,495 -1.6 +0.8 -0.8 1.5
Jonas Jerebko 2016 1,338 -1.5 +0.7 -0.8 1.3
Marco Belinelli 2018 2,220 +1.2 -2.0 -0.8 2.2
Carmelo Anthony 2018 2,695 +1.0 -1.7 -0.8 2.7
Deron Williams 2016 2,155 -0.2 -0.6 -0.8 2.1
Dennis Schroder 2019 2,465 -0.2 -0.6 -0.8 2.5
E’Twaun Moore 2018 2,870 +0.3 -1.1 -0.8 2.9
T.J. McConnell 2017 2,133 -1.4 +0.6 -0.8 2.1
Ish Smith 2016 2,239 +0.3 -1.1 -0.8 2.2
Luc Mbah a Moute 2018 1,713 -2.8 +2.1 -0.8 1.7
JaVale McGee 2019 1,671 -1.4 +0.5 -0.8 1.7
Jordan Hill 2014 1,500 -0.5 -0.3 -0.8 1.5
Darius Miller 2018 2,106 +0.4 -1.2 -0.8 2.1
Will Barton 2017 1,705 +1.1 -1.9 -0.8 1.7
Rodney Hood 2017 1,870 -0.4 -0.5 -0.8 1.8
Kosta Koufos 2017 1,419 -2.5 +1.7 -0.8 1.4
Kevin Martin 2015 1,302 +1.7 -2.5 -0.8 1.3
Larry Nance Jr. 2017 1,442 -1.4 +0.6 -0.8 1.4
Shaun Livingston 2016 2,034 -0.1 -0.7 -0.8 2.0
Bobby Portis 2018 1,643 +1.1 -2.0 -0.8 1.6
Gerald Henderson 2016 1,665 -1.3 +0.5 -0.8 1.6
Langston Galloway 2017 1,495 -0.8 -0.1 -0.8 1.5
Trevor Booker 2017 1,754 -2.0 +1.2 -0.8 1.7
Nick Collison 2015 1,101 -0.8 -0.1 -0.9 1.1
Al-Farouq Aminu 2014 2,045 -1.3 +0.5 -0.9 2.0
Jeff Teague 2018 2,464 +1.2 -2.0 -0.9 2.4
Justin Holiday 2019 2,607 -2.0 +1.2 -0.9 2.5
Rasual Butler 2015 1,512 -0.2 -0.7 -0.9 1.4
Anthony Tolliver 2015 1,432 +0.7 -1.6 -0.9 1.4
Langston Galloway 2019 1,855 -0.1 -0.8 -0.9 1.8
Marvin Williams 2014 1,674 +0.8 -1.7 -0.9 1.6
Chris Douglas-Roberts 2014 1,086 +0.0 -0.9 -0.9 1.0
Jon Leuer 2017 1,944 -1.3 +0.5 -0.9 1.8
Wesley Matthews 2019 2,210 -0.6 -0.3 -0.9 2.1
Jonathon Simmons 2017 1,698 -1.7 +0.8 -0.9 1.6
Giannis Antetokounmpo 2014 1,897 -1.1 +0.2 -0.9 1.8
Caris LeVert 2018 1,864 -1.0 +0.1 -0.9 1.8
Dwyane Wade 2018 1,663 -1.6 +0.7 -0.9 1.6
Lance Thomas 2016 1,313 -0.9 +0.0 -0.9 1.2
John Henson 2018 2,044 -1.4 +0.4 -0.9 1.9
Richard Jefferson 2015 1,295 -0.9 -0.1 -0.9 1.2
Andrew Harrison 2018 1,326 -0.4 -0.5 -0.9 1.2
Tyson Chandler 2018 1,151 -1.9 +1.0 -0.9 1.1
Taj Gibson 2017 2,107 -1.7 +0.7 -0.9 2.0
Bogdan Bogdanovic 2018 2,175 +0.8 -1.7 -0.9 2.0
Jeremy Lin 2019 1,463 -1.9 +1.0 -0.9 1.4
Willy Hernangomez 2017 1,324 -1.2 +0.2 -0.9 1.2
Cory Joseph 2018 2,353 -0.9 -0.0 -0.9 2.2
Luc Mbah a Moute 2015 1,916 -3.2 +2.3 -1.0 1.7
O.J. Mayo 2016 1,090 -1.7 +0.8 -1.0 1.0
Zach Randolph 2016 2,136 +0.7 -1.7 -1.0 1.9
Jonas Valanciunas 2014 2,482 -0.8 -0.2 -1.0 2.2
Elfrid Payton 2016 2,145 -0.6 -0.4 -1.0 2.0
Beno Udrih 2015 1,669 -0.0 -0.9 -1.0 1.5
Robin Lopez 2017 2,433 -2.2 +1.2 -1.0 2.2
Marcin Gortat 2017 2,965 -1.2 +0.2 -1.0 2.7
Shai Gilgeous-Alexander 2019 2,347 -0.9 -0.1 -1.0 2.1
Tony Parker 2016 2,244 -0.4 -0.6 -1.0 2.0
Dillon Brooks 2018 2,350 -1.5 +0.6 -1.0 2.1
Alan Anderson 2014 2,034 -0.9 -0.1 -1.0 1.8
Wayne Ellington 2018 2,142 +1.2 -2.2 -1.0 1.9
Nicolas Batum 2018 1,981 +1.3 -2.3 -1.0 1.8
Phil Pressey 2014 1,132 -1.9 +0.9 -1.0 1.0
Tobias Harris 2015 2,369 -0.0 -1.0 -1.0 2.1
Frank Kaminsky 2016 1,898 -1.4 +0.4 -1.0 1.7
Serge Ibaka 2017 2,729 -1.1 +0.1 -1.0 2.4
Austin Rivers 2018 2,057 +1.0 -2.0 -1.0 1.8
Cristiano Felicio 2017 1,122 -1.2 +0.2 -1.0 1.0
Maurice Harkless 2014 1,950 -1.4 +0.4 -1.0 1.7
Zach LaVine 2019 2,171 +1.3 -2.3 -1.0 1.9
Evan Turner 2017 1,782 -2.3 +1.2 -1.0 1.5
Dante Exum 2017 1,312 -1.9 +0.8 -1.0 1.1
Devin Booker 2017 2,730 +1.0 -2.0 -1.1 2.4
Dirk Nowitzki 2017 1,424 -1.3 +0.3 -1.1 1.2
Mike Muscala 2019 1,306 -1.2 +0.1 -1.1 1.1
Ish Smith 2017 1,955 -0.1 -1.0 -1.1 1.6
Elfrid Payton 2019 1,250 +0.1 -1.1 -1.1 1.1
Mario Chalmers 2018 1,421 -2.1 +1.0 -1.1 1.2
Maurice Harkless 2018 1,317 -0.8 -0.3 -1.1 1.1
Marcus Morris 2019 2,345 +0.9 -2.0 -1.1 2.0
Josh Smith 2014 2,730 -1.9 +0.8 -1.1 2.3
Nicolas Batum 2019 2,354 -0.9 -0.2 -1.1 2.0
David West 2015 1,895 -1.4 +0.3 -1.1 1.6
Joe Ingles 2015 1,673 -1.2 +0.1 -1.1 1.4
Corey Brewer 2016 1,746 -1.9 +0.8 -1.1 1.5
Anthony Morrow 2016 1,002 +1.7 -2.8 -1.1 0.8
DeMarre Carroll 2019 1,822 -0.6 -0.5 -1.1 1.5
Jabari Parker 2017 1,728 +0.4 -1.5 -1.1 1.4
Toney Douglas 2016 1,262 +0.9 -2.1 -1.1 1.0
Nicolas Batum 2016 2,592 +1.1 -2.2 -1.1 2.1
Luol Deng 2017 1,486 -1.8 +0.7 -1.1 1.2
Jameer Nelson 2015 1,407 +0.1 -1.3 -1.2 1.1
Mike Muscala 2018 1,060 -1.2 +0.1 -1.2 0.9
Giannis Antetokounmpo 2015 2,742 -0.8 -0.4 -1.2 2.2
Serge Ibaka 2018 2,353 -1.0 -0.2 -1.2 1.9
Dion Waiters 2016 2,643 -0.6 -0.5 -1.2 2.2
Dante Cunningham 2017 1,649 -1.4 +0.2 -1.2 1.3
Alec Burks 2018 1,179 +0.2 -1.4 -1.2 0.9
Carmelo Anthony 2017 2,538 +1.9 -3.1 -1.2 2.0
Bam Adebayo 2018 1,445 -2.2 +1.0 -1.2 1.2
Amar’e Stoudemire 2014 1,466 -0.9 -0.2 -1.2 1.2
Taj Gibson 2019 1,686 +0.4 -1.5 -1.2 1.3
Alex Len 2019 1,544 -1.8 +0.6 -1.2 1.2
David Lee 2015 1,011 -0.6 -0.6 -1.2 0.8
T.J. Warren 2016 1,070 +0.5 -1.7 -1.2 0.8
Lavoy Allen 2016 1,650 -0.8 -0.4 -1.2 1.3
Kenneth Faried 2014 2,178 +1.2 -2.4 -1.2 1.7
Kosta Koufos 2018 1,391 -1.8 +0.6 -1.2 1.1
Kris Dunn 2018 1,525 -1.7 +0.5 -1.2 1.2
Austin Rivers 2014 1,339 -0.3 -0.9 -1.2 1.0
Caris LeVert 2017 1,237 -0.4 -0.8 -1.2 1.0
Kelly Olynyk 2014 1,400 -0.0 -1.2 -1.2 1.1
Zaza Pachulia 2014 1,325 -1.5 +0.3 -1.2 1.0
Joakim Noah 2017 1,015 -1.0 -0.2 -1.2 0.8
Enes Kanter 2015 2,135 +0.5 -1.7 -1.2 1.6
Dion Waiters 2019 1,138 -0.3 -0.9 -1.2 0.9
Jason Thompson 2014 2,007 -1.5 +0.3 -1.3 1.5
Norman Powell 2019 1,492 -0.7 -0.6 -1.3 1.2
JaMychal Green 2016 1,518 -1.3 +0.0 -1.3 1.1
Kyle Kuzma 2019 2,314 -0.6 -0.7 -1.3 1.7
James Ennis III 2015 1,051 -0.1 -1.2 -1.3 0.8
Malcolm Delaney 2018 1,014 -1.5 +0.2 -1.3 0.8
Harrison Barnes 2019 2,533 -0.9 -0.4 -1.3 1.9
Taj Gibson 2015 1,968 -1.5 +0.2 -1.3 1.4
Aaron Brooks 2014 1,557 +0.5 -1.8 -1.3 1.2
Dion Waiters 2014 2,072 -0.5 -0.8 -1.3 1.5
Ish Smith 2019 1,332 -0.2 -1.1 -1.3 1.0
Rodney McGruder 2019 1,550 -1.5 +0.2 -1.3 1.1
Dante Cunningham 2014 1,635 -1.5 +0.2 -1.3 1.2
Eric Gordon 2016 1,481 +0.5 -1.8 -1.3 1.1
Courtney Lee 2018 2,310 +0.2 -1.5 -1.3 1.7
Tyler Hansbrough 2014 1,007 -0.8 -0.5 -1.3 0.7
DeMar DeRozan 2016 3,550 +1.8 -3.1 -1.3 2.5
Kelly Olynyk 2017 1,884 -1.1 -0.2 -1.3 1.4
Jeff Green 2015 2,752 -0.6 -0.7 -1.3 2.0
Richaun Holmes 2019 1,184 -1.5 +0.2 -1.3 0.9
Brandon Knight 2014 2,400 +0.9 -2.3 -1.3 1.7
Steve Blake 2014 1,543 -0.8 -0.5 -1.3 1.1
Boris Diaw 2015 2,182 -0.5 -0.9 -1.3 1.6
Tony Snell 2016 1,301 -2.4 +1.0 -1.3 0.9
Isaiah Taylor 2018 1,167 -1.2 -0.2 -1.3 0.8
Tyler Johnson 2019 1,529 -1.4 +0.0 -1.3 1.1
Ryan Kelly 2014 1,312 +0.5 -1.9 -1.3 0.9
Kyle Korver 2019 1,364 -0.6 -0.8 -1.4 1.0
Michael Carter-Williams 2015 2,340 -3.2 +1.8 -1.4 1.7
Courtney Lee 2015 2,721 +0.3 -1.7 -1.4 1.9
Glenn Robinson III 2017 1,458 -1.5 +0.1 -1.4 1.0
Courtney Lee 2017 2,459 +0.1 -1.4 -1.4 1.7
Alex Len 2018 1,395 -1.1 -0.3 -1.4 1.0
DeMar DeRozan 2015 2,259 +0.1 -1.5 -1.4 1.6
J.J. Barea 2016 1,767 +0.9 -2.3 -1.4 1.2
Evan Fournier 2015 1,661 +0.2 -1.5 -1.4 1.2
JR Smith 2014 2,421 +1.8 -3.1 -1.4 1.7
Stanley Johnson 2018 1,894 -2.7 +1.3 -1.4 1.3
Timofey Mozgov 2016 1,402 -3.7 +2.3 -1.4 1.0
Mason Plumlee 2019 1,949 -0.9 -0.5 -1.4 1.3
Dwight Powell 2017 1,333 -0.8 -0.5 -1.4 0.9
Kevin Martin 2014 2,177 +0.7 -2.1 -1.4 1.5
Kosta Koufos 2016 1,482 -1.6 +0.2 -1.4 1.0
James Ennis III 2017 1,660 -1.7 +0.3 -1.4 1.1
Corey Brewer 2017 1,281 -1.9 +0.4 -1.4 0.9
Taurean Prince 2017 1,168 -3.1 +1.7 -1.4 0.8
Julius Randle 2019 2,232 +0.6 -2.0 -1.4 1.5
Vince Carter 2019 1,330 -1.2 -0.3 -1.4 0.9
Darius Miller 2019 1,757 -0.9 -0.5 -1.4 1.2
Jordan Clarkson 2015 1,476 +0.2 -1.6 -1.4 1.0
Domantas Sabonis 2018 1,976 -0.8 -0.7 -1.4 1.3
Terrence Ross 2015 2,199 +0.2 -1.7 -1.4 1.5
Gerald Green 2018 1,201 -0.1 -1.3 -1.4 0.8
Eric Gordon 2019 2,568 +0.7 -2.1 -1.4 1.7
Jonas Jerebko 2017 1,360 -0.7 -0.8 -1.5 0.9
Terry Rozier 2019 1,953 -1.7 +0.3 -1.5 1.3
Thomas Bryant 2019 1,496 +0.2 -1.7 -1.5 1.0
Gary Harris 2016 2,439 +0.4 -1.9 -1.5 1.6
Tyson Chandler 2017 1,298 -1.1 -0.3 -1.5 0.8
Cory Joseph 2017 2,215 -0.7 -0.8 -1.5 1.4
Jaylen Brown 2019 2,187 -1.7 +0.2 -1.5 1.4
Zach LaVine 2017 1,749 +0.9 -2.4 -1.5 1.1
Matthew Dellavedova 2015 1,877 -0.8 -0.7 -1.5 1.2
Trey Burke 2016 1,366 +0.6 -2.1 -1.5 0.9
Tony Snell 2019 1,332 -0.2 -1.3 -1.5 0.9
Evan Turner 2019 1,850 -1.8 +0.3 -1.5 1.2
Devin Harris 2019 1,071 -0.1 -1.4 -1.5 0.7
Miles Plumlee 2015 1,210 -1.9 +0.4 -1.5 0.7
Dario Saric 2019 2,023 -0.6 -1.0 -1.5 1.3
Harrison Barnes 2018 2,634 -1.4 -0.2 -1.5 1.6
Alex Abrines 2018 1,244 -0.0 -1.5 -1.5 0.8
Kyle Kuzma 2018 2,401 -0.7 -0.8 -1.5 1.5
Frank Ntilikina 2018 1,706 -4.0 +2.5 -1.5 1.1
Jeff Green 2016 2,412 -0.8 -0.7 -1.5 1.5
DeAndre Jordan 2019 2,047 -2.2 +0.7 -1.5 1.3
Kyle Anderson 2016 1,374 -1.9 +0.3 -1.5 0.8
O.J. Mayo 2015 1,853 -0.1 -1.5 -1.5 1.2
Brian Roberts 2014 1,667 -0.7 -0.8 -1.5 1.0
Evan Turner 2015 2,378 -1.8 +0.3 -1.6 1.5
Jordan Hamilton 2014 1,019 -1.0 -0.5 -1.6 0.6
Martell Webster 2014 2,352 +0.7 -2.3 -1.6 1.4
Raymond Felton 2018 1,444 -1.1 -0.4 -1.6 0.9
Mike Scott 2016 1,307 -0.5 -1.1 -1.6 0.8
Jerami Grant 2016 2,066 -2.5 +0.9 -1.6 1.2
Frank Kaminsky 2018 1,835 +0.7 -2.3 -1.6 1.1
Meyers Leonard 2016 1,333 -1.0 -0.6 -1.6 0.8
Tristan Thompson 2018 1,488 -0.8 -0.8 -1.6 0.9
Shawn Marion 2014 2,602 -1.4 -0.2 -1.6 1.5
Jarrett Jack 2016 1,027 +0.0 -1.6 -1.6 0.6
Nerlens Noel 2015 2,311 -4.3 +2.7 -1.6 1.3
Denzel Valentine 2018 2,095 -0.7 -1.0 -1.6 1.2
Rajon Rondo 2015 2,055 -1.7 +0.1 -1.6 1.2
Joe Johnson 2015 3,040 +1.6 -3.2 -1.6 1.7
Garrett Temple 2019 2,103 -2.4 +0.8 -1.6 1.2
Jordan Clarkson 2017 2,397 -0.5 -1.1 -1.7 1.3
Caron Butler 2015 1,623 -0.2 -1.5 -1.7 0.9
Kenneth Faried 2016 1,694 +0.9 -2.6 -1.7 0.9
Anthony Tolliver 2017 1,477 -0.5 -1.2 -1.7 0.8
Nikola Vucevic 2015 2,529 -0.7 -1.0 -1.7 1.4
Jarrett Jack 2015 2,394 -1.7 -0.0 -1.7 1.3
Marco Belinelli 2019 1,946 +0.5 -2.2 -1.7 1.1
Dwight Howard 2016 2,460 -1.8 +0.1 -1.7 1.3
Jake Layman 2019 1,347 -1.2 -0.4 -1.7 0.7
Harrison Barnes 2016 2,785 -1.0 -0.7 -1.7 1.5
Jordan Crawford 2014 1,916 +0.4 -2.1 -1.7 1.1
Mason Plumlee 2018 1,439 -2.0 +0.3 -1.7 0.8
Chris Andersen 2015 1,132 -1.6 -0.1 -1.7 0.6
Justin Jackson 2019 1,614 -0.7 -1.0 -1.7 0.9
T.J. McConnell 2019 1,545 -1.0 -0.7 -1.7 0.8
Solomon Hill 2015 2,381 -1.5 -0.2 -1.7 1.2
Trevor Booker 2018 1,222 -0.5 -1.2 -1.7 0.6
D.J. Augustin 2015 1,964 -0.2 -1.5 -1.7 1.0
Ersan Ilyasova 2014 1,478 -2.4 +0.7 -1.7 0.8
Darrell Arthur 2014 1,161 -3.6 +1.9 -1.7 0.6
Quincy Pondexter 2015 1,917 +0.3 -2.0 -1.7 1.0
Trey Burke 2014 2,262 +0.4 -2.2 -1.8 1.1
Tayshaun Prince 2015 1,397 -0.7 -1.0 -1.8 0.7
Eric Gordon 2015 2,161 +0.8 -2.5 -1.8 1.1
Milos Teodosic 2018 1,134 +0.0 -1.8 -1.8 0.6
Kris Dunn 2019 1,389 -1.1 -0.7 -1.8 0.7
Jordan Hill 2016 1,528 -1.3 -0.5 -1.8 0.8
Dennis Smith Jr. 2019 1,508 -2.9 +1.2 -1.8 0.8
Kevin Huerter 2019 2,048 +0.4 -2.2 -1.8 1.0
Bojan Bogdanovic 2015 2,060 -0.1 -1.7 -1.8 1.0
Rodney McGruder 2017 1,966 -0.4 -1.4 -1.8 1.0
Steven Adams 2014 1,528 -1.5 -0.3 -1.8 0.7
Dorian Finney-Smith 2017 1,642 -2.6 +0.8 -1.8 0.8
Arron Afflalo 2014 2,552 +1.2 -3.0 -1.8 1.2
Dennis Schroder 2017 2,696 +0.8 -2.6 -1.8 1.3
Randy Foye 2016 1,832 -1.8 -0.0 -1.8 0.9
DeAndre Jordan 2018 2,424 -0.9 -1.0 -1.8 1.2
Kelly Oubre Jr. 2018 2,379 -0.9 -0.9 -1.8 1.1
Miles Plumlee 2014 1,964 -3.4 +1.6 -1.8 0.9
Willie Cauley-Stein 2016 1,412 -1.1 -0.7 -1.8 0.7
Gerald Henderson 2014 2,580 -1.7 -0.2 -1.8 1.2
Josh Huestis 2018 1,001 -3.1 +1.3 -1.8 0.5
Francisco Garcia 2014 1,105 -0.4 -1.4 -1.8 0.5
Ramon Sessions 2014 2,214 +0.6 -2.4 -1.8 1.0
Joe Ingles 2016 1,241 -1.7 -0.1 -1.8 0.6
Tim Frazier 2017 1,525 -0.5 -1.3 -1.8 0.7
D.J. Augustin 2016 1,178 +1.1 -2.9 -1.9 0.5
David Nwaba 2018 1,646 -0.9 -0.9 -1.9 0.7
Avery Bradley 2019 1,905 -2.6 +0.7 -1.9 0.9
Willie Cauley-Stein 2018 2,044 -2.8 +0.9 -1.9 0.9
Dario Saric 2017 2,129 -2.1 +0.3 -1.9 1.0
Donald Sloan 2016 1,318 +0.4 -2.3 -1.9 0.6
Bryn Forbes 2019 2,505 +0.3 -2.2 -1.9 1.1
Tayshaun Prince 2014 2,061 -3.1 +1.2 -1.9 0.9
Tobias Harris 2014 1,850 -0.0 -1.9 -1.9 0.8
Gorgui Dieng 2015 2,193 -1.2 -0.7 -1.9 0.9
Evan Turner 2018 2,121 -2.4 +0.5 -1.9 0.9
Marco Belinelli 2015 1,504 +0.7 -2.6 -1.9 0.6
Marco Belinelli 2017 1,778 +0.1 -2.1 -1.9 0.7
Aaron Brooks 2015 2,017 +1.1 -3.1 -1.9 0.8
Alonzo Gee 2016 1,632 -3.1 +1.1 -1.9 0.7
Myles Turner 2018 2,032 -1.9 -0.1 -1.9 0.9
Jason Thompson 2015 1,991 -2.1 +0.2 -2.0 0.8
Shabazz Muhammad 2017 1,516 -0.3 -1.6 -2.0 0.6
Richard Jefferson 2014 2,213 -0.3 -1.6 -2.0 0.9
Aron Baynes 2016 1,277 -2.0 +0.0 -2.0 0.5
Cody Zeller 2014 1,469 -1.5 -0.5 -2.0 0.6
Andrew Wiggins 2019 2,543 -1.1 -0.9 -2.0 1.0
Brandon Ingram 2018 1,975 -1.2 -0.8 -2.0 0.8
Brandon Ingram 2019 1,760 -1.3 -0.7 -2.0 0.7
Trey Burke 2015 2,288 +0.0 -2.0 -2.0 0.9
Matt Barnes 2017 1,838 -1.0 -1.0 -2.0 0.7
Stanley Johnson 2017 1,371 -2.5 +0.5 -2.0 0.5
Wesley Johnson 2015 2,245 -0.6 -1.5 -2.0 0.8
Marvin Williams 2019 2,133 -1.2 -0.8 -2.0 0.8
Noah Vonleh 2017 1,365 -3.0 +1.0 -2.0 0.5
Shaun Livingston 2015 1,843 -1.7 -0.4 -2.0 0.7
Justin Anderson 2017 1,228 -1.2 -0.8 -2.0 0.5
Thaddeus Young 2014 2,718 -0.8 -1.2 -2.0 1.0
Allen Crabbe 2019 1,133 -2.6 +0.6 -2.0 0.4
Robin Lopez 2019 1,606 -1.9 -0.2 -2.0 0.6
Jonas Jerebko 2019 1,339 -0.5 -1.6 -2.0 0.5
Richard Jefferson 2017 1,793 -1.5 -0.5 -2.0 0.7
John Henson 2015 1,381 -2.7 +0.7 -2.0 0.5
E’Twaun Moore 2019 1,463 +0.2 -2.2 -2.0 0.5
Raymond Felton 2017 1,827 -2.2 +0.2 -2.1 0.7
Doug McDermott 2019 1,369 +0.3 -2.3 -2.1 0.5
Reggie Jackson 2017 1,424 +0.1 -2.1 -2.1 0.5
Monta Ellis 2017 2,074 -1.5 -0.5 -2.1 0.7
Shawne Williams 2015 1,087 +0.5 -2.6 -2.1 0.4
Jabari Parker 2019 1,724 -1.3 -0.8 -2.1 0.6
Luke Kennard 2019 1,570 +0.1 -2.1 -2.1 0.5
Al Jefferson 2015 1,992 -2.3 +0.3 -2.1 0.7
Treveon Graham 2018 1,050 -0.8 -1.3 -2.1 0.4
Jerryd Bayless 2015 1,837 -1.9 -0.2 -2.1 0.6
Steve Blake 2015 1,572 -0.8 -1.3 -2.1 0.5
Brandon Jennings 2017 1,980 -0.6 -1.5 -2.1 0.7
Nik Stauskas 2017 2,188 +0.0 -2.1 -2.1 0.7
DeAndre’ Bembry 2019 1,931 -3.2 +1.1 -2.1 0.7
Rajon Rondo 2019 1,369 -0.7 -1.4 -2.1 0.5
Michael Beasley 2018 1,653 -0.1 -2.0 -2.1 0.6
Wilson Chandler 2019 1,229 -1.5 -0.6 -2.1 0.4
John Henson 2017 1,135 -3.1 +1.0 -2.1 0.4
Tony Snell 2017 2,521 -0.4 -1.7 -2.1 0.8
Kyle Singler 2015 1,743 -1.2 -0.9 -2.1 0.6
Zach Collins 2019 1,631 -1.5 -0.6 -2.1 0.5
Trae Young 2019 2,503 +2.4 -4.5 -2.1 0.8
Ian Clark 2017 1,356 -0.6 -1.5 -2.1 0.4
John Wall 2019 1,104 -0.3 -1.9 -2.1 0.4
Leandro Barbosa 2015 1,211 +0.8 -2.9 -2.1 0.4
Jamal Crawford 2016 2,325 +0.5 -2.6 -2.1 0.7
Hollis Thompson 2015 1,776 -1.1 -1.1 -2.1 0.6
Dion Waiters 2015 2,208 -1.0 -1.2 -2.1 0.7
Richaun Holmes 2017 1,193 -0.9 -1.3 -2.1 0.4
Deron Williams 2017 1,919 -0.0 -2.1 -2.1 0.6
Dante Cunningham 2015 1,727 -2.3 +0.2 -2.1 0.5
Willie Reed 2017 1,031 -1.8 -0.4 -2.1 0.3
Elfrid Payton 2018 1,808 +0.5 -2.7 -2.1 0.6
Jae Crowder 2018 2,413 -1.8 -0.3 -2.2 0.7
Justin Hamilton 2017 1,177 -2.5 +0.3 -2.2 0.3
Dwyane Wade 2019 1,885 -0.1 -2.1 -2.2 0.6
Markieff Morris 2018 2,149 -1.5 -0.7 -2.2 0.6
Gerald Green 2019 1,570 -0.0 -2.2 -2.2 0.5
Wesley Matthews 2018 2,131 -0.6 -1.5 -2.2 0.6
Leandro Barbosa 2016 1,333 -0.1 -2.1 -2.2 0.4
Evan Fournier 2014 1,503 -1.4 -0.8 -2.2 0.4
Bismack Biyombo 2015 1,243 -2.5 +0.3 -2.2 0.4
Avery Bradley 2018 1,433 -2.5 +0.3 -2.2 0.4
Wes Iwundu 2019 1,293 -2.8 +0.6 -2.2 0.4
Trevor Ariza 2019 2,349 -0.2 -2.0 -2.2 0.7
Shaun Livingston 2019 1,289 -1.2 -1.0 -2.2 0.3
Bryn Forbes 2018 1,571 -1.0 -1.3 -2.2 0.4
Sean Kilpatrick 2017 1,754 -0.0 -2.2 -2.2 0.5
Timothe Luwawu-Cabarrot 2017 1,190 -1.9 -0.3 -2.2 0.3
Jamal Crawford 2015 2,082 +1.2 -3.5 -2.2 0.6
Reggie Bullock 2019 1,879 -1.1 -1.2 -2.2 0.5
Jordan Hill 2015 1,874 -2.5 +0.3 -2.2 0.5
C.J. Watson 2017 1,012 -1.9 -0.3 -2.3 0.3
Shaun Livingston 2018 1,491 -1.2 -1.1 -2.3 0.4
Channing Frye 2015 1,870 -1.0 -1.2 -2.3 0.5
Buddy Hield 2017 1,888 -0.9 -1.4 -2.3 0.5
Brandon Knight 2016 1,870 +0.3 -2.5 -2.3 0.5
Mike Scott 2018 1,532 -0.4 -1.9 -2.3 0.4
Terrence Jones 2017 1,270 -2.2 -0.1 -2.3 0.3
Richard Jefferson 2016 1,707 -1.8 -0.5 -2.3 0.5
Deandre Ayton 2019 2,183 -0.6 -1.7 -2.3 0.5
Kent Bazemore 2019 1,643 -2.9 +0.6 -2.3 0.4
Marcus Morris 2018 2,009 -0.9 -1.4 -2.3 0.4
Bismack Biyombo 2014 1,120 -3.5 +1.2 -2.3 0.3
Jerami Grant 2015 1,377 -2.6 +0.3 -2.3 0.3
Dwight Howard 2018 2,463 -2.2 -0.1 -2.3 0.5
Kobe Bryant 2015 1,207 +1.2 -3.5 -2.3 0.3
Mike Miller 2014 1,880 +0.5 -2.8 -2.3 0.4
Jodie Meeks 2018 1,119 -0.3 -2.1 -2.3 0.2
Andrea Bargnani 2014 1,257 -2.9 +0.6 -2.3 0.3
Miles Bridges 2019 1,696 -1.6 -0.7 -2.3 0.3
Anthony Tolliver 2019 1,079 -1.9 -0.5 -2.3 0.2
Jerami Grant 2017 1,642 -1.9 -0.4 -2.4 0.3
Avery Bradley 2015 2,561 -1.6 -0.7 -2.4 0.5
Norris Cole 2014 2,418 -1.8 -0.6 -2.4 0.5
Damyean Dotson 2019 2,004 -1.2 -1.2 -2.4 0.4
Tyson Chandler 2016 1,618 -2.7 +0.3 -2.4 0.3
Andre Drummond 2017 2,409 -2.5 +0.1 -2.4 0.5
Mario Hezonja 2019 1,206 -2.3 -0.1 -2.4 0.2
Jerryd Bayless 2014 1,686 +0.1 -2.4 -2.4 0.3
Jonathon Simmons 2018 2,029 -0.5 -1.9 -2.4 0.3
Andrew Wiggins 2015 2,969 -0.4 -2.1 -2.4 0.5
Jarrett Jack 2018 1,548 -0.8 -1.6 -2.4 0.3
Tim Frazier 2019 1,160 -0.1 -2.3 -2.4 0.2
Thon Maker 2019 1,041 -2.9 +0.4 -2.4 0.1
Pau Gasol 2014 1,884 -1.7 -0.8 -2.4 0.3
Jameer Nelson 2014 2,179 +1.2 -3.7 -2.4 0.3
Trevor Booker 2014 1,699 +0.3 -2.8 -2.4 0.3
Ben McLemore 2016 1,443 -1.7 -0.8 -2.5 0.2
Nick Young 2018 1,598 -1.1 -1.3 -2.5 0.2
Andre Miller 2015 1,253 +0.5 -2.9 -2.5 0.2
Jarrett Jack 2014 2,252 -1.7 -0.8 -2.5 0.3
Austin Rivers 2017 2,144 -0.9 -1.5 -2.5 0.3
Alec Burks 2019 1,375 -0.9 -1.6 -2.5 0.2
Tayshaun Prince 2016 1,462 -2.8 +0.3 -2.5 0.2
Kent Bazemore 2015 1,627 -2.8 +0.3 -2.5 0.2
Shane Larkin 2016 1,751 -1.9 -0.6 -2.5 0.2
J.J. Barea 2014 1,471 -0.9 -1.7 -2.5 0.2
Kendrick Perkins 2014 1,591 -4.3 +1.7 -2.5 0.2
Shane Larkin 2015 1,865 -2.3 -0.2 -2.5 0.2
Wes Iwundu 2018 1,020 -3.2 +0.6 -2.5 0.1
Derrick Favors 2017 1,411 -2.8 +0.3 -2.5 0.1
Alex Len 2017 1,560 -3.7 +1.1 -2.5 0.2
Alex Len 2016 1,821 -4.4 +1.8 -2.6 0.2
Austin Rivers 2019 2,243 -1.6 -0.9 -2.6 0.2
Luis Scola 2016 1,776 -1.5 -1.1 -2.6 0.2
Domantas Sabonis 2017 1,638 -3.8 +1.3 -2.6 0.2
Taurean Prince 2019 1,552 -0.6 -1.9 -2.6 0.1
Allen Crabbe 2017 2,346 -0.9 -1.7 -2.6 0.2
Jameer Nelson 2017 2,045 +0.4 -2.9 -2.6 0.2
Mason Plumlee 2015 1,792 -0.9 -1.7 -2.6 0.2
Chris Kaman 2015 1,435 -2.7 +0.1 -2.6 0.1
Tyler Ulis 2018 1,658 -1.6 -1.0 -2.6 0.1
Tony Parker 2015 2,163 +0.1 -2.7 -2.6 0.2
Matt Barnes 2016 2,329 -0.7 -1.9 -2.6 0.2
Ramon Sessions 2015 1,406 -1.7 -0.9 -2.6 0.1
Nerlens Noel 2016 1,965 -4.1 +1.5 -2.6 0.1
Taurean Prince 2018 2,464 -0.8 -1.8 -2.6 0.2
John Salmons 2014 1,803 -2.4 -0.3 -2.6 0.1
Jeff Ayres 2014 1,017 -1.6 -1.0 -2.6 0.1
Jordan Clarkson 2016 2,552 -0.4 -2.2 -2.6 0.1
Stanley Johnson 2019 1,208 -4.8 +2.2 -2.6 0.1
Julius Randle 2016 2,286 -2.3 -0.4 -2.6 0.1
Boris Diaw 2017 1,486 -2.6 -0.1 -2.6 0.1
Tarik Black 2015 1,196 -1.4 -1.2 -2.7 0.1
Arron Afflalo 2015 2,562 -1.0 -1.7 -2.7 0.1
Jason Smith 2017 1,225 -2.0 -0.6 -2.7 0.0
Isaiah Canaan 2016 1,966 -0.6 -2.1 -2.7 0.1
Jerian Grant 2016 1,265 -2.3 -0.4 -2.7 0.0
Travis Outlaw 2014 1,065 -1.4 -1.3 -2.7 0.0
Derrick Rose 2016 2,097 -1.3 -1.4 -2.7 0.0
Zach LaVine 2016 2,294 +0.6 -3.3 -2.7 0.1
Allonzo Trier 2019 1,459 -1.3 -1.5 -2.7 0.0
Jason Terry 2016 1,382 +0.2 -2.9 -2.7 0.0
Tony Parker 2017 1,798 -0.5 -2.2 -2.7 0.1
Wayne Ellington 2016 1,615 -1.9 -0.9 -2.7 0.0
Terrence Jones 2015 1,290 -1.5 -1.2 -2.7 0.0
Kelly Oubre Jr. 2017 1,789 -2.1 -0.6 -2.7 0.0
Austin Rivers 2016 1,608 -1.9 -0.9 -2.7 0.0
Myles Turner 2016 1,564 -3.9 +1.1 -2.7 0.0
Lance Stephenson 2016 1,467 +0.1 -2.9 -2.7 0.0
Kyle Korver 2017 2,079 +0.2 -3.0 -2.7 0.0
Yogi Ferrell 2017 1,197 -0.8 -1.9 -2.7 0.0
Chase Budinger 2015 1,286 -1.1 -1.7 -2.8 0.0
Ante Zizic 2019 1,082 -2.1 -0.7 -2.8 0.0
Trey Lyles 2016 1,382 -2.7 -0.1 -2.8 0.0
Doug McDermott 2018 1,768 -1.4 -1.3 -2.8 0.0
Omri Casspi 2015 1,416 +0.6 -3.4 -2.8 0.0
Ray McCallum 2015 1,436 -0.8 -2.0 -2.8 0.0
Skal Labissiere 2018 1,240 -2.0 -0.8 -2.8 0.0
Shawn Marion 2015 1,126 -2.1 -0.7 -2.8 0.0
James Johnson 2016 1,024 -2.1 -0.7 -2.8 0.0
JaMychal Green 2019 1,512 -1.0 -1.8 -2.8 -0.1
Tyler Zeller 2018 1,175 -1.9 -1.0 -2.8 -0.1
D’Angelo Russell 2017 1,811 -0.3 -2.5 -2.8 -0.1
Shaun Livingston 2017 1,565 -2.0 -0.8 -2.8 -0.1
Glen Davis 2014 1,820 -3.2 +0.3 -2.8 0.0
Josh Jackson 2019 1,988 -3.4 +0.6 -2.8 -0.1
Mirza Teletovic 2017 1,160 -0.7 -2.1 -2.8 -0.1
Frank Kaminsky 2017 1,954 -1.1 -1.7 -2.8 -0.1
Quincy Acy 2018 1,359 -2.2 -0.7 -2.9 -0.1
Marvin Bagley III 2019 1,567 -1.1 -1.8 -2.9 -0.1
Quincy Acy 2015 1,287 -2.5 -0.4 -2.9 -0.1
Lou Williams 2014 1,578 +0.9 -3.8 -3.0 -0.2
JaMychal Green 2018 1,542 -1.3 -1.6 -3.0 -0.2
Brandon Bass 2015 2,015 -1.7 -1.2 -3.0 -0.2
Jeff Green 2017 1,534 -2.6 -0.4 -3.0 -0.2
Lance Thomas 2018 1,353 -3.0 +0.0 -3.0 -0.2
Mo Williams 2014 2,021 -1.2 -1.8 -3.0 -0.3
Trey Lyles 2017 1,168 -3.2 +0.2 -3.0 -0.1
Mason Plumlee 2014 1,389 -1.8 -1.2 -3.0 -0.2
Emmanuel Mudiay 2019 1,607 -1.0 -2.0 -3.0 -0.2
Greivis Vasquez 2015 2,092 -0.5 -2.5 -3.0 -0.3
Marreese Speights 2016 1,033 -3.6 +0.6 -3.0 -0.1
Matthew Dellavedova 2017 2,145 -1.2 -1.8 -3.0 -0.3
Bobby Portis 2017 1,121 -1.7 -1.3 -3.0 -0.1
Jason Smith 2016 1,181 -2.3 -0.8 -3.0 -0.2
Dante Cunningham 2018 1,562 -2.4 -0.6 -3.0 -0.2
Lavoy Allen 2014 1,087 -2.7 -0.3 -3.0 -0.2
Donald Sloan 2015 1,107 -1.2 -1.8 -3.0 -0.2
Malcolm Delaney 2017 1,251 -3.3 +0.2 -3.0 -0.2
Mario Hezonja 2016 1,413 -2.2 -0.9 -3.0 -0.2
Patrick Patterson 2018 1,328 -2.9 -0.2 -3.1 -0.2
Sterling Brown 2019 1,196 -2.0 -1.1 -3.1 -0.2
Tyler Ulis 2017 1,123 -0.5 -2.6 -3.1 -0.2
Timofey Mozgov 2017 1,104 -4.3 +1.2 -3.1 -0.2
Robert Sacre 2015 1,133 -3.6 +0.5 -3.1 -0.2
Arron Afflalo 2016 2,371 -0.6 -2.5 -3.1 -0.4
JR Smith 2018 2,950 -0.5 -2.7 -3.1 -0.5
Shabazz Napier 2015 1,012 -2.0 -1.1 -3.1 -0.2
Tony Snell 2018 2,187 -1.2 -1.9 -3.1 -0.4
Markieff Morris 2019 1,329 -2.2 -0.9 -3.1 -0.3
Terrance Ferguson 2019 2,059 -1.6 -1.6 -3.1 -0.4
Isaiah Whitehead 2017 1,643 -2.5 -0.7 -3.2 -0.3
Jamal Crawford 2017 2,353 -0.8 -2.3 -3.2 -0.4
Ramon Sessions 2016 1,667 -0.3 -2.9 -3.2 -0.4
Rodions Kurucs 2019 1,362 -2.6 -0.6 -3.2 -0.3
KJ McDaniels 2015 1,352 -3.9 +0.7 -3.2 -0.3
Patrick McCaw 2017 1,255 -2.0 -1.2 -3.2 -0.3
JJ Hickson 2014 1,859 -3.1 -0.1 -3.2 -0.4
Brandon Rush 2017 1,030 -2.3 -0.9 -3.2 -0.2
Noah Vonleh 2016 1,186 -3.2 -0.0 -3.2 -0.3
Lance Stephenson 2019 1,123 -1.1 -2.1 -3.2 -0.3
Brandon Bass 2014 2,266 -2.1 -1.2 -3.2 -0.5
Joffrey Lauvergne 2017 1,006 -2.0 -1.2 -3.2 -0.2
Gerald Henderson 2017 1,667 -1.6 -1.6 -3.2 -0.4
Randy Foye 2015 1,087 -0.3 -2.9 -3.2 -0.3
Wendell Carter Jr. 2019 1,110 -4.7 +1.4 -3.2 -0.3
Joe Harris 2017 1,138 -2.3 -1.0 -3.3 -0.3
James Johnson 2019 1,164 -2.5 -0.7 -3.3 -0.3
James Ennis III 2019 1,462 -1.3 -1.9 -3.3 -0.4
Kirk Hinrich 2015 1,736 -2.2 -1.0 -3.3 -0.5
Kris Dunn 2017 1,333 -3.3 +0.0 -3.3 -0.4
Lance Stephenson 2018 1,999 -0.2 -3.1 -3.3 -0.6
Marquese Chriss 2018 1,527 -3.6 +0.3 -3.3 -0.4
Carl Landry 2015 1,192 -1.9 -1.4 -3.3 -0.3
Marreese Speights 2015 1,274 -1.7 -1.6 -3.3 -0.4
Eric Gordon 2014 2,057 +0.6 -3.9 -3.3 -0.6
Bobby Portis 2016 1,102 -2.6 -0.7 -3.3 -0.3
Nik Stauskas 2016 1,809 -1.7 -1.6 -3.3 -0.5
James Anderson 2014 2,309 -2.0 -1.4 -3.4 -0.7
Carlos Boozer 2015 1,692 -1.6 -1.8 -3.4 -0.5
Wesley Johnson 2014 2,240 -2.2 -1.2 -3.4 -0.7
O.J. Mayo 2014 1,346 -1.3 -2.1 -3.4 -0.4
John Henson 2014 1,856 -2.4 -1.0 -3.4 -0.6
Rodney Stuckey 2014 1,950 -1.0 -2.4 -3.4 -0.7
Rodney Hood 2018 1,876 -0.5 -2.9 -3.4 -0.7
Hollis Thompson 2014 1,742 -0.4 -3.0 -3.4 -0.6
Al Jefferson 2016 1,264 -2.2 -1.2 -3.4 -0.5
D’Angelo Russell 2016 2,259 -1.7 -1.8 -3.5 -0.8
Joffrey Lauvergne 2016 1,041 -1.4 -2.1 -3.5 -0.4
Alfonzo McKinnie 2019 1,238 -1.2 -2.2 -3.5 -0.5
Tristan Thompson 2014 2,594 -0.7 -2.8 -3.5 -1.0
Will Bynum 2014 1,054 -0.3 -3.2 -3.5 -0.4
Kevin Seraphin 2015 1,307 -3.0 -0.6 -3.5 -0.5
Ian Clark 2018 1,645 -1.1 -2.4 -3.5 -0.7
Bojan Bogdanovic 2017 2,347 -0.5 -3.1 -3.6 -1.0
Steve Blake 2016 1,029 -1.5 -2.0 -3.6 -0.5
Mike Scott 2015 1,295 -1.4 -2.2 -3.6 -0.6
Norris Cole 2015 1,937 -1.9 -1.7 -3.6 -0.8
Shabazz Muhammad 2016 1,682 +0.1 -3.6 -3.6 -0.7
Ben McLemore 2017 1,176 -1.8 -1.8 -3.6 -0.5
Dante Exum 2015 1,817 -2.8 -0.8 -3.6 -0.8
OG Anunoby 2019 1,352 -3.3 -0.3 -3.6 -0.6
Norris Cole 2016 1,198 -1.0 -2.6 -3.6 -0.5
Mike Scott 2019 1,588 -1.5 -2.2 -3.7 -0.7
Devin Booker 2016 2,108 -0.4 -3.2 -3.7 -1.0
Tony Parker 2019 1,003 -0.6 -3.1 -3.7 -0.5
Willie Cauley-Stein 2017 1,421 -3.1 -0.6 -3.7 -0.7
Tony Snell 2014 1,277 -2.8 -0.9 -3.7 -0.6
Luke Ridnour 2014 1,177 -1.6 -2.1 -3.7 -0.6
Justin Jackson 2018 1,506 -2.3 -1.4 -3.7 -0.8
Tim Hardaway Jr. 2015 1,681 +0.4 -4.1 -3.7 -0.8
Harrison Barnes 2014 2,360 -3.2 -0.6 -3.8 -1.2
Jaylen Brown 2017 1,556 -3.3 -0.5 -3.8 -0.8
Robert Sacre 2014 1,089 -4.0 +0.2 -3.8 -0.6
Kendall Marshall 2014 1,564 +0.5 -4.3 -3.8 -0.8
Tony Wroten 2014 1,765 -2.3 -1.5 -3.8 -0.9
Zach Randolph 2018 1,508 +0.1 -3.8 -3.8 -0.8
Doug McDermott 2016 1,861 -0.4 -3.4 -3.8 -1.0
Jeff Green 2014 2,805 -1.6 -2.2 -3.8 -1.5
Luis Scola 2014 1,642 -3.5 -0.3 -3.8 -0.9
Kyle Singler 2016 1,028 -2.4 -1.4 -3.8 -0.6
Jonathon Simmons 2019 1,116 -3.2 -0.6 -3.9 -0.6
Jabari Parker 2016 2,408 -1.2 -2.7 -3.9 -1.4
Stanley Johnson 2016 1,768 -3.3 -0.5 -3.9 -1.0
Sergio Rodriguez 2017 1,518 -0.5 -3.4 -3.9 -0.9
Dennis Schroder 2015 1,806 -1.3 -2.6 -3.9 -1.1
Marco Belinelli 2016 1,672 -1.1 -2.8 -3.9 -1.0
Archie Goodwin 2016 1,114 -0.7 -3.2 -3.9 -0.7
Jahlil Okafor 2016 1,591 -3.3 -0.7 -3.9 -0.9
Cedi Osman 2019 2,444 -1.1 -2.8 -3.9 -1.5
Brandon Knight 2017 1,140 -2.0 -1.9 -3.9 -0.7
Kobe Bryant 2016 1,863 -0.2 -3.8 -4.0 -1.2
Omer Asik 2016 1,178 -3.5 -0.5 -4.0 -0.7
Paul Pierce 2016 1,285 -3.2 -0.8 -4.0 -0.8
Austin Rivers 2015 1,813 -2.4 -1.6 -4.0 -1.2
Caron Butler 2014 1,838 -1.7 -2.4 -4.0 -1.2
Jarrett Allen 2018 1,441 -2.9 -1.1 -4.1 -1.0
Mindaugas Kuzminskas 2017 1,016 -0.4 -3.7 -4.1 -0.7
Brandon Rush 2016 1,165 -1.3 -2.8 -4.1 -0.8
Ty Lawson 2016 1,485 -3.1 -1.0 -4.1 -1.1
D’Angelo Russell 2018 1,234 -0.6 -3.5 -4.1 -0.9
Meyers Leonard 2019 1,048 +0.1 -4.3 -4.1 -0.7
Will Barton 2019 1,517 -1.9 -2.2 -4.1 -1.1
Ryan Kelly 2015 1,233 -1.9 -2.3 -4.2 -0.9
Damjan Rudez 2015 1,047 -1.4 -2.8 -4.2 -0.8
Trey Lyles 2019 1,128 -3.6 -0.6 -4.2 -0.8
Derrick Williams 2016 1,435 -1.4 -2.8 -4.2 -1.0
Jamal Crawford 2018 1,776 +0.7 -4.9 -4.2 -1.3
Nick Young 2016 1,033 -0.8 -3.4 -4.2 -0.7
Hollis Thompson 2016 2,154 -0.9 -3.3 -4.2 -1.6
Julius Randle 2017 2,132 -1.6 -2.6 -4.2 -1.6
Derrick Williams 2014 1,820 -2.0 -2.2 -4.2 -1.3
Greg Stiemsma 2014 1,007 -4.1 -0.2 -4.2 -0.8
Andrew Harrison 2017 1,593 -2.8 -1.5 -4.2 -1.2
Robin Lopez 2018 1,690 -4.3 +0.1 -4.2 -1.3
Glen Davis 2015 1,048 -5.6 +1.3 -4.3 -0.8
Jarell Martin 2018 1,661 -3.8 -0.5 -4.3 -1.3
Malik Monk 2019 1,258 -0.6 -3.7 -4.3 -1.0
Gorgui Dieng 2018 1,403 -3.0 -1.3 -4.3 -1.1
Luc Mbah a Moute 2014 1,003 -3.0 -1.3 -4.3 -0.8
Marquese Chriss 2017 1,743 -3.0 -1.3 -4.3 -1.4
Shelvin Mack 2017 1,360 -1.9 -2.4 -4.3 -1.1
Doug McDermott 2017 1,574 -0.3 -4.0 -4.3 -1.2
Evan Turner 2014 2,606 -2.3 -2.0 -4.3 -2.2
De’Aaron Fox 2018 2,026 -2.4 -2.0 -4.3 -1.7
Dragan Bender 2018 2,069 -3.3 -1.0 -4.4 -1.7
Randy Foye 2017 1,284 -2.7 -1.7 -4.4 -1.1
Troy Daniels 2018 1,622 -0.5 -3.9 -4.4 -1.4
Kevin Martin 2016 1,144 -1.6 -2.8 -4.5 -1.0
Bobby Portis 2019 1,299 -1.2 -3.3 -4.5 -1.1
Derrick Williams 2015 1,462 -1.0 -3.4 -4.5 -1.3
Mike Scott 2014 1,628 -1.5 -2.9 -4.5 -1.4
Gary Neal 2015 1,193 -0.7 -3.8 -4.5 -1.1
Josh Jackson 2018 1,959 -3.2 -1.3 -4.5 -1.8
Andrew Nicholson 2014 1,174 -3.7 -0.8 -4.5 -1.1
Jarrett Allen 2019 2,206 -1.5 -3.1 -4.6 -2.1
Bismack Biyombo 2017 1,793 -4.0 -0.6 -4.6 -1.7
Norman Powell 2018 1,102 -2.8 -1.8 -4.6 -1.1
Bojan Bogdanovic 2016 2,115 -1.3 -3.3 -4.6 -2.0
Dante Cunningham 2016 1,971 -2.0 -2.7 -4.6 -1.9
Kendrick Perkins 2015 1,181 -5.3 +0.6 -4.7 -1.2
Frank Jackson 2019 1,169 -1.9 -2.8 -4.7 -1.2
Ben McLemore 2018 1,091 -2.3 -2.4 -4.7 -1.1
JaKarr Sampson 2015 1,131 -3.6 -1.2 -4.8 -1.2
JJ Hickson 2015 1,411 -3.7 -1.1 -4.8 -1.5
Meyers Leonard 2017 1,253 -3.4 -1.4 -4.8 -1.3
Shelvin Mack 2019 1,246 -2.8 -2.0 -4.8 -1.3
Spencer Hawes 2015 1,331 -4.4 -0.5 -4.9 -1.5
Nik Stauskas 2019 1,015 -1.7 -3.2 -4.9 -1.1
Nik Stauskas 2015 1,127 -1.3 -3.7 -4.9 -1.3
Henry Sims 2015 1,399 -3.1 -1.9 -5.0 -1.6
Emmanuel Mudiay 2016 2,068 -3.1 -2.0 -5.1 -2.5
Diante Garrett 2014 1,048 -4.0 -1.1 -5.1 -1.2
Zach Collins 2018 1,115 -3.5 -1.5 -5.1 -1.3
Gary Neal 2014 1,218 -0.6 -4.5 -5.1 -1.5
PJ Hairston 2016 1,335 -2.8 -2.4 -5.1 -1.6
Jameer Nelson 2016 1,036 -1.3 -3.8 -5.1 -1.2
Roy Hibbert 2016 1,878 -4.3 -0.9 -5.2 -2.3
Brandon Ingram 2017 2,279 -2.5 -2.7 -5.2 -2.8
Bismack Biyombo 2018 1,495 -4.1 -1.1 -5.2 -1.9
Quinn Cook 2019 1,252 -1.1 -4.1 -5.2 -1.6
Marreese Speights 2014 1,050 -4.0 -1.3 -5.3 -1.3
Jason Smith 2015 1,785 -2.7 -2.7 -5.4 -2.4
Joe Johnson 2018 1,259 -3.8 -1.6 -5.4 -1.7
Alonzo Gee 2014 1,020 -3.3 -2.1 -5.4 -1.4
Enes Kanter 2014 2,138 -3.2 -2.3 -5.4 -2.9
Emmanuel Mudiay 2018 1,245 -3.0 -2.4 -5.5 -1.7
Tony Parker 2018 1,138 -2.1 -3.4 -5.5 -1.6
Rashad Vaughn 2016 1,001 -3.1 -2.4 -5.5 -1.4
Dennis Smith Jr. 2018 2,049 -2.2 -3.3 -5.5 -2.9
Tim Hardaway Jr. 2014 1,875 -0.0 -5.5 -5.6 -2.7
Ben McLemore 2014 2,187 -1.9 -3.7 -5.6 -3.2
Jameer Nelson 2018 1,013 -3.0 -2.7 -5.6 -1.5
Jahlil Okafor 2017 1,134 -4.7 -0.9 -5.7 -1.7
Lance Thomas 2015 1,490 -4.0 -1.7 -5.7 -2.3
Lance Stephenson 2015 1,573 -3.4 -2.3 -5.8 -2.4
Carlos Boozer 2014 2,262 -4.3 -1.6 -5.9 -3.7
JaKarr Sampson 2016 1,160 -4.0 -2.0 -6.0 -1.9
Arron Afflalo 2017 1,580 -1.3 -4.8 -6.0 -2.6
Thon Maker 2018 1,368 -3.1 -3.0 -6.1 -2.3
Wayne Selden 2019 1,439 -3.0 -3.2 -6.3 -2.6
Semi Ojeleye 2018 1,380 -4.6 -1.7 -6.3 -2.5
D.J. Augustin 2017 1,538 -2.2 -4.2 -6.4 -2.8
Emmanuel Mudiay 2017 1,406 -2.5 -4.0 -6.5 -2.7
Jose Calderon 2015 1,270 -1.4 -5.3 -6.8 -2.6
Jamal Crawford 2019 1,211 -1.0 -5.8 -6.8 -2.5
Elliot Williams 2014 1,157 -3.5 -3.7 -7.2 -2.7
Terrence Jones 2016 1,044 -3.4 -4.6 -8.0 -2.8
Kevin Knox 2019 2,158 -3.8 -4.3 -8.1 -6.0
Zach LaVine 2015 1,902 -3.5 -4.8 -8.3 -5.4
Collin Sexton 2019 2,605 -2.8 -5.5 -8.3 -7.4

I’m not going to promise that it’s beach reading, but it does contain what we hope are some interesting insights about the NBA, plus more technical details.

Box RAPTOR

RAPTOR in many ways takes its inspiration from BPM, which was designed by Daniel Myers. BPM was designed by fitting a regression model for which the inputs are various traditional statistics (e.g., points, rebounds, etc.) and the dependant variable is long-term Real Adjusted Plus Minus (RAPM). The “box” component of RAPTOR does something similar, only using player-tracking and play-by-play data in addition to traditional statistics.

What is RAPM? It’s a measure of how many points a player contributes per 100 possessions based on his team’s performance when he’s on and off the floor, accounting for the quality of his teammates and his opponents. Adjusting for teammate and opponent strength can be tricky business, however. Mediocre players on great teams, such as JaVale McGee on the 2016-17 and 2017-18 Golden State Warriors, can have strong raw offensive and defensive ratings because they play with excellent teammates; it is obviously necessary to adjust for this when calculating McGee’s contribution to the team. Players with small sample sizes and rarely used lineup combinations can also create problems, so RAPM employs various techniques to regress their performance toward the mean. So in theory, RAPM is a truly comprehensive statistic, measuring all the tangible and intangible ways in which a player contributes to his team’s bottom line. It should also be an unbiased measure, not overvaluing or undervaluing any particular type of skill relative to its actual value on the court.

But in practice, RAPM can be very noisy, taking several seasons to stabilize. It’s also fairly computationally intensive and can be sensitive to relatively subtle choices about exactly how it’s calculated. For these reasons, RAPM is not a great measure for use in a projection system, when our data needs are more time sensitive — e.g., if we want to see how much a player such as De’Aaron Fox improves from one season to the next.

The insight behind BPM — and now RAPTOR — is that we can use other statistics that stabilize much more quickly than RAPM to approximate long-term RAPM. More specifically, we fit a series of regression coefficients using a six-year dataset of RAPM as provided to us by Ryan Davis, with the six years matching the six seasons (2013-14 through 2018-19) for which player tracking data is available. (We made a few adjustments to RAPM from Davis’s version to make it more appropriate for our specific needs.)4

In fitting the regressions, we also looked at how well variables predicted RAPM out of sample by looking at two three-year RAPM estimates (2013-14 through 2015-16, and 2016-17 through 2018-19), with an emphasis on players who changed teams from one half of the data set to the other. If a certain variable predicted RAPM well in the in-sample, six-year regression, but not in the out-of-sample, three-year regressions, that’s generally a sign that it reflects luck rather than skill or that it’s too noisy to provide for a reliable indicator of player value. For instance, data on how many 3-pointers opponents make when a player is the nearest defender is highly predictive of in-sample RAPM but not at all predictive of out-of-sample RAPM. Thus, variables like this were excluded from RAPTOR.

In addition, we used our basketball knowledge to inform our choices of parameters. For instance, 3-point attempts are a good proxy for creating floor spacing or having “gravity” — that is, drawing defenders toward you and therefore giving your teammates more open scoring opportunities. In our various regression specifications, it was ambiguous whether a better statistical fit was produced by using all 3-point attempts or instead weighting 3-point attempts based on how closely contested they were. In situations like these, we went with what made more “basketball sense”: in this case, that players who have a lot of contested threes are the ones who do more to create space. We also separately fit models for offensive and defensive RAPTORs, instead of combining them. Thus, for example, offensive rebounds contribute to a player’s offensive RAPTOR and defensive rebounds to a player’s defensive RAPTOR, rather than blurring them together. So while the regression specifications that follow might seem complex, there was quite a lot of basketball thinking behind them; it wasn’t just a matter of coming up with the best statistical fit.

Box RAPTOR Offense

The variables used in offensive “box” RAPTOR follow below. Although the list includes a few statistics, most of them fall into one of four major categories: scoring and usage; passing; rebounding; and space creation. Before being used in the regression, all variables are adjusted relative to league average. In addition, stats from the playoffs were adjusted to reflect the tougher competition in the postseason. Here are the categories in more detail:

Measures of scoring and usage

Points: This is just what it sounds like. Good ol’ points scored are in fact the highest-weighted category in offensive RAPTOR:

Usage rate: A “usage” is any shooting attempt, turnover or foul drawn that results in free throws, except for fouls (e.g., flagrant fouls and clear path fouls) that result in the team getting the ball back after the free-throw attempt.5 Heaves (shots from beyond half-court, which are almost always taken out of desperation at the end of the quarter) count as only a small fraction of a possession. Although this is complicated by the fact that RAPTOR contains a number of variables related to shooting, usage and scoring, overall it is calibrated such that players who score at average efficiency tend to improve their RAPTORs by doing so, as opposed to not taking any shots at all.

Time of possession: The value of a possession also decreases as time ticks off the shot clock. Thus, merely possessing the ball negatively predicts offensive RAPM, holding other factors constant.

Assisted field goals: In addition, assisted field goals are less valuable than unassisted ones. In some sense, this is a matter of basic accounting: If you’re giving players credit for assists (as RAPTOR does), you probably have to take some credit away from the player who benefits from the assist.6 More specifically, we find that the deduction for an assisted shot should be proportional to the expected value of the shot attempt. RAPTOR recognizes seven types of shots based on their location on the floor:

RAPTOR shot categories
Shot type Expected value of shot*
Dunks 1.83
Shots within 4 feet other than dunks (colloquially, “layups”) 1.16
Shots in the paint but not within 4 feet 0.82
Midrange shots (all 2-pointers not in the paint) 0.80
Corner 3-pointers 1.16
Above-the-break 3-pointers 1.05
Heaves 0.08

Shot values are based on results from 2013-14 through 2018-19. They include the value of “and-one” free-throw attempts after made shots, but not free throws after missed shots, which are not officially recorded as shots by the NBA.

Source: NBA

While all players who rely heavily on assisted baskets are penalized by this statistic, it has a particularly large effect on players such as DeAndre Jordan who camp out at the basket and depend on assisted dunks. In fact, it’s essential to account for these players’ assisted field goals because they’re strongly correlated with other types of statistics, especially offensive rebounds. Failure to account for assisted field goals will bias the value of offensive rebounds downward, and some advanced stats such as RPM very likely understate the importance of offensive rebounds for this reason.

Measures of passing

Enhanced assists: Likewise, the value of an assist in RAPTOR is proportional to the expected value of the resulting shot. Assists on dunks and corner threes are considerably more valuable than assists on midrange jumpers. In addition, we give partial credit for what the NBA calls “free throw assists”: passes that result in a teammate drawing a shooting foul. However, we find that there isn’t much value in what the NBA calls “potential assists” that don’t result in baskets or free-throw attempts.7 We do, however, give players credit for …

Net passes: The NBA also keeps track of the number of passes a player makes and receives during the game, and a positive passing differential is associated with a higher RAPM in and out of sample.

Measures of rebounding

Enhanced offensive rebounds: Offensive rebounds are a tricky category. On the one hand, the value of an offensive rebound is intrinsically quite high: A team not only gets a new life on its possession after an offensive board, but it is also often in a premium position to score via a putback opportunity. (Although it depends on how the rebound is secured, the average value of a possession after an offensive rebound is around 1.2 points.) On the other hand, a lot of rebounding has to do with being in the right place at the right time. Rebounding can involve a fair amount of luck, and loitering near the basket hoping for rebounds can have negative consequences for a team’s spacing. But in general, offensive rebounds are becoming more valuable as offensive rebounding rates get lower, having fallen from 33 percent in the mid-1980s to about 23 percent in today’s NBA.

For both offensive and defensive rebounds, RAPTOR makes various fixes to the rebound statistics. Essentially, our goal is to calculate how much a rebound affects the expected value of a possession. For instance, after a missed shot, the expected value of a possession was around 0.28 points in 2018-2019 (a 23 percent chance of an offensive rebound times an average of 1.2 points scored conditional on securing the rebound). A defensive rebound would reduce this value to zero and end the possession; an offensive rebound would increase it to 1.2 points.

The NBA’s player tracking data distinguishes between contested and uncontested rebounds. Contested rebounds are more valuable, although this makes less of a difference for offensive than defensive rebounds. The intuition behind this is as follows: Because 77 percent of rebounds are defensive rebounds, only defensive rebounds on which the offense has a serious shot at the ball (i.e., contested rebounds) have all that much value for a defensive player since his team would probably wind up with the ball anyway. On the other hand, in today’s NBA, any offensive rebound is rare, and therefore any offensive rebound is fairly valuable. Thus, players provide value through contested defensive rebounds (but not much through uncontested ones) and through offensive rebounds of any kind.

RAPTOR also evaluates the location of the shot preceding the rebound, as some shots are much more likely to produce offensive rebounds than others. For instance, missed free throws produce offensive rebounds only about 10 percent of the time, so defensive rebounds after free throws have very little value since the remaining expected value of a possession is already close to zero. Layups produce high rates of offensive rebounds, by contrast — so defensive rebounds are worth more in this case.

There are also a couple of more technical fixes to the rebounding stats:

  • If a loose ball foul occurs on the rebound, but the rebound is not credited to a particular player,8 we give the player who drew the foul credit for a contested rebound. We also give the player who committed the foul blame for having yielded a rebound to his opponent (see below).
  • The NBA also keeps track of deferred rebounds: when a player has a chance at the rebound but passes it up to a teammate. Empirically,9 the value of deferred rebounds is quite high, perhaps because it indicates overall selfless play. (Think about Steven Adams giving up rebounds to Russell Westbrook, for instance.) For simplicity’s sake, however, RAPTOR simply treats a deferred rebound as being as valuable as a regular rebound. In addition, we reduce the overall number of rebounds proportionately for all players on the team based on the number of deferred rebounds for the team.

Team offensive rebounds on missed shots: We also find that the shooter has a fair amount of influence on a team’s offensive rebound rate on his missed shots. As I mentioned, some types of shots produce more offensive boards than others; players who get to the rim for floaters and layups can produce particularly high offensive rebounding rates, for instance (see table below). In addition, big men who play away from the basket (Brook Lopez, for example) can cause rebounding problems because there’s often no offensive player in prime position to secure the rebound if they’re playing out on the perimeter. We give slightly more credit to rebounds that occur (i) in bounds and (ii) not after blocked shots, since these are associated with a higher expected value for the remainder of the possession.

Some shots produce far more offensive rebounds
Shot type Offensive Rebound Rate
Dunks 28%
Shots within 4 feet other than dunks (colloquially, “layups”) 35
Shots in the paint but not within 4 feet 28
Midrange shots (all 2-pointers not in the paint) 19
Corner 3-pointers 22
Above-the-break 3-pointers 20
Heaves 26
Free throws 10

Rebound rates are based on results from 2013-14 through 2018-19

Source: NBA

Positional opponents’ defensive rebounds: RAPTOR attempts to figure out which player was matched up with which opponent on a given possession based on their positions as listed in our database. The idea is that centers are matched up against centers, power forwards against power forwards, and so forth. In practice, however, there’s rarely a clean one-to-one correspondence between players at different positions. Instead, in assigning players to positions for our depth charts, we deliberately draw from multiple sources to make most players eligible at multiple positions. The upshot of this is that in RAPTOR, player assignments are probabilistic, which likely makes sense anyway given the amount of switching in today’s NBA.

Despite this being a relatively noisy process, there is some predictive power (including in out-of-sample regressions) in seeing how many points and rebounds a player’s positional matchups secure. Opposing bigs get notably fewer defensive rebounds when playing against Embiid than against most other centers, for example, both because he’s effective at boxing out and because he can sometimes draw them away from the basket with his scoring ability.

Measures of spacing

Defended 3-point attempts: Although it’s possible to imagine more sophisticated measures of player gravity, for the time being, the best publicly available metric to measure spacing is simply 3-point attempts, with an emphasis on 3-point attempts that are closely contested by the defense. This is a little tricky, though: Even shots that the NBA’s data currently describes as “wide open” (no defender within 6 feet) likely involve some degree of defensive pressure.10 Based on players’ shooting percentages, we treat the various shooting categories as follows:

  • Nearest defender within 2 feet: 100 percent covered
  • Nearest defender 2 to 4 feet away: 80 percent covered
  • Nearest defender 4 to 6 feet away: 57 percent covered
  • Nearest defender 6-plus feet away: 31 percent covered

Isolation turnovers: Our research also found that some types of turnovers — which we call isolation turnovers — are more costly than others in terms of predicting in-sample and out-of-sample RAPM. In particular, turnovers that are associated with attempts to score — as opposed to attempts to pass or otherwise contribute11 to a teammate’s opportunity to score — are associated with lower offensive RAPMs and are therefore punished by RAPTOR.12 Isolation turnovers consist of the following categories:

  • 100 percent of travels, charging fouls, 5-second violations, offensive goaltends and baskets from below.
  • 75 percent of lost-ball turnovers, palming turnovers, double dribbles, discontinued dribbles and step-out-of-bounds turnovers.

Miscellaneous offensive metrics

Fast-break starts: Possessions that begin with steals or after certain types of blocked shots are often highly productive, so players deserve some offensive credit for these actions in addition to their value on defense. Specifically, we estimate that a steal increases the value of a subsequent offensive position by 0.2 points, and a blocked shot on which a team comes down with the rebound inbounds increases it by 0.11 points.

Nonshooting defensive fouls drawn: In RAPTOR, the main value of drawing fouls is in the points they create via free throws. But what about fouls that don’t result in free throws? These have a small amount of value also because they (i) reset the shot clock to 14 seconds and (ii) often allow the offense to inbound the ball from an advantageous position, such as along the baseline near the basket, depending on where the foul was committed (empirically, possessions that restart after a nonshooting foul have a fairly high expected value). Thus, we estimate that nonshooting fouls drawn are worth about 0.16 points.

Penalty fouls drawn: Some additional benefits to drawing fouls are hard to measure via RAPM. Because RAPM evaluates players by comparing how a team performs when the player is on or off the court, it struggles with situations where a player creates value for his teammates regardless of whether he’s on the court. In particular, fouls that contribute to the bonus/penalty13 can increase the value of possessions later on in the quarter by making the penalty (which results in free-throw attempts being awarded on nonshooting fouls) more likely to occur. In addition, drawing fouls can put opponents in foul trouble and yield worse opponent lineups going forward. Fortunately, we estimate these effects to be small: Combined, they’re worth about 0.04 points per foul that’s not reflected by RAPM.

Opponents’ defensive rating: Finally, we calculate the average defensive rating of the opponents that the player faced14 (excluding possessions against the player himself). This is another way to account for the degree of difficulty of a player’s competition.

Box RAPTOR Defense

In measuring offense, RAPTOR is relatively elegant. The different aspects of an offensive possession — scoring, rebounding, passing, spacing — are well-represented, and the values assigned to various types of offensive statistics are reasonably intuitive.

Defense is more of an uphill battle. Some of the statistics RAPTOR uses to rate defensive performance are really more like proxies for other unmeasured statistics. We expect that the state of publicly available defensive metrics will improve in future years, and RAPTOR will improve along with them.

Nonetheless, we think RAPTOR majorly moves the ball forward on defense. The R-squared of our defensive RAPTOR regression in predicting within-sample RAPM is about 0.6, as opposed to only about 0.3 using traditional defensive statistics (steals, blocks, defensive rebounds, fouls committed) alone. This brings us a lot closer to capturing major parts of defense that have traditionally gone unmeasured.

Specifically, RAPTOR uses the following variables in its defensive regression:

Steals: Steals are an example of how defensive statistics can serve as both direct and indirect measures of player value. In our defensive RAPM regression, a steal is worth 1.49 points on defense. This is almost certainly more than the direct value that a steal provides, since the average NBA possession is worth around 1.08 points, meaning that the value of terminating a possession with a steal probably isn’t worth much more than 1.08 points.15 However, steals are also a proxy for overall defensive activity, some of which is currently going unmeasured.

Offensive fouls drawn: The same holds for offensive fouls drawn. In fact, they’re worth even more in the RAPM regression.16 Drawn fouls are rated highly by the regression both because they end a possession (often when the opposing team is in a strong position to score) and because they serve as a stand-in for stout overall on-ball defense. Players who are adept at inducing offensive fouls include Kyle Lowry, Ersan Ilyasova, Marcus Smart, Patrick Beverley and J.J. Barea. These types of players often have higher defensive RAPMs than their traditional defensive statistics would imply, and some of the reason for that is that they’ve been producing a lot of “hidden” defensive value by inducing offensive fouls.

Opponents’ field goals made and attempted: Earlier this year, we introduced DRAYMOND, a measure of on-ball defense based on the NBA’s opponents’ shooting statistics. In some ways, DRAYMOND was a first step in the creation of RAPTOR, our first foray into incorporating player tracking data into our projections. But it left two major things to be desired:

  • DRAYMOND placed too much weight on how many shots a defender’s opponents made, which can involve a lot of luck, as opposed to how many shots the player defended.
  • DRAYMOND essentially treated all types of shots equally. Our subsequent research, however, suggests that the current publicly available data on opponents’ 3-point shooting is largely noise. Many 3-point shots are relatively open shots, so which player happens to be the nearest defender is largely random in these cases, and whether the opponent makes the shot adds additional randomness. The opponents’ shooting data is quite a valuable indicator of rim protection or 2-point defense, on the other hand.

Thus, in RAPTOR, the different components of opponents’ shooting are weighted as follows:

  • Each missed 2-point shot when the player is the nearest defender: +1.05 points.
  • Each made 2-point shot: -0.33 points.
  • Each attempted 3-point shot, whether the shot is missed or made : +0.17 points.

As an aside, RAPTOR defensive ratings do not use blocked shots. We find that there is no additional predictive power in using blocks when projecting RAPM, once you’re already accounted for opponents’ field goals.17

Enhanced defensive rebounds: RAPTOR handles defensive rebounding as it does offensive rebounding. Contested defensive rebounds are worth considerably more in RAPTOR than uncontested rebounds. And defensive rebounds after shots that produce a high rate of offensive rebounds (such as layups and other shots near the rim) are worth more than rebounds on shots that don’t.

Positional opponents’ points scored: As mentioned earlier, attempting to infer positional matchups — and counting how many points and rebounds a player’s positional opponents secure — provides helpful information. Since 2013-14, the best and worst players based on positional opponents’ points allowed are as follows:

How NBA players vary in allowing their opponents to score

Positional opponents’ points per 100 possessions for players with at least 10,000 possessions played, 2013-14 through 2018-19

Worst Best
Player Positional opponents’ points per 100 poss. Player Positional opponents’ points per 100 poss.
Damian Lillard 23.9 Marc Gasol 18.0
Jameer Nelson 23.8 Nene 18.4
D’Angelo Russell 23.8 Dwight Howard 18.6
Jerian Grant 23.5 Joakim Noah 19.0
Elfrid Payton 23.3 Joe Ingles 19.0
Kenneth Faried 23.3 Manu Ginobili 19.0
Aaron Brooks 23.3 Andrew Bogut 19.2
Ben McLemore 23.2 Harrison Barnes 19.3
John Wall 23.1 Michael Kidd-Gilchrist 19.4
Mike Conley 23.1 Tim Duncan 19.4
Mason Plumlee 23.1 David West 19.5
Brandon Knight 23.1 Kawhi Leonard 19.5
Ish Smith 23.0 Andre Iguodala 19.5
Montrezl Harrell 23.0 Kyle Anderson 19.6
Emmanuel Mudiay 22.9 Roy Hibbert 19.6
Terrence Jones 22.9 Rudy Gobert 19.6
Karl-Anthony Towns 22.8 CJ Miles 19.7
Jrue Holiday 22.8 JJ Redick 19.7
Devin Booker 22.7 Thabo Sefolosha 19.8
Jordan Clarkson 22.7 Allen Crabbe 19.8

One advantage of this metric is that it can capture players who produce lots of blocks or rebounds at the rim — such as Kenneth Faried or Mitchell Robinson — but who aren’t very mobile defenders and might allow opposing centers and power forwards (especially stretch bigs) to score at high rates. Likewise, players who gamble on steals are sometimes punished by this statistic if they aren’t playing sound fundamental defense.18

Positional opponents’ offensive rebounds: RAPTOR also accounts for how many offensive rebounds a player’s positional matchups secure. Some players such as Hassan Whiteside are effective at producing their own rebounds but also allow opposing bigs to secure offensive rebounds at relatively high rates. Others like Adams are both skilled at getting their own rebounds and at boxing out opponents from getting theirs.

Distance traveled, for perimeter defenders only: As mentioned, current publicly available defensive metrics are more effective at measuring interior/rim defense than perimeter defense. One metric that helps a bit on the perimeter is distance traveled per 100 defensive positions. RAPTOR uses this metric only for defenders that spend a lot of time on the perimeter, based on their ratio of 3-point shots to 2-point shots defended. (It’s not particularly helpful to have a rim protector like Rudy Gobert running all around the backcourt.) This stat can pick up on some additional defensive value for Avery Bradley or Iman Shumpert types who are pesky, active perimeter defenders. It can sometimes also detect players like Harden who take their share of defensive possessions off. This metric is a good candidate to get swapped out for more precise measures of defensive activity in future versions of RAPTOR.

Opponents’ free throws made: RAPTOR deducts value for free throws made on fouls committed by the defensive player. This is its main way of punishing defenders for committing fouls. However, the deduction for a made free throw is relatively minor (0.19 points). This is because fouls, although costly to the team, are at least a sign that the defensive player is challenging shots. (If we had better measures of defensive activity, in other words, the coefficients associated with fouls and free throws would probably be more steeply negative.) In fact, in the predictive formulation of RAPTOR used in our projection models (PREDATOR), fouls are handled slightly differently: A defensive player still gets a deduction when an opponent that he fouled makes a free throw, but the defender actually gets a small amount of credit for committing a foul.

Even though players don’t really19 exert any control over whether their opponents make their free throws, free throws made nevertheless outperforms free throws attempted as a measure of the cost of committing fouls because players do exert some control over who they foul. Big men tend to make free throws at lower rates than wings and guards, so fouls committed by big men (usually against other big men) tend to be less costly. In addition, some very smart defenders (e.g., Green or Gobert) show indications of being selective about who they foul, based in part on which opponents make free throws at a high rate.

Fastbreak turnovers committed: Just as generating turnovers that result in fast breaks help a team’s offense, committing turnovers hurts a team’s defense. Thus, live-ball turnovers (i.e., steals) result in a 0.2-point deduction to a player’s defensive rating, while field-goal attempts that result in blocked shots where the defense rebounds the ball inbounds result in a 0.11-point deduction.

Penalty fouls committed: As described earlier, fouls have some costs (potentially putting the opposing team in the bonus and creating foul trouble) that aren’t well-measured by RAPM, although these effects are small. Thus, players get a 0.04-point deduction for every foul they commit that counts toward the bonus/penalty.

Opponents’ offensive rating: RAPTOR calculates the average offensive rating of the opponents that the player faced as a defender and adjusts his defensive rating accordingly as a way to account for the strength of his competition.

RAPTOR On-Off

In comparison to “Box” RAPTOR, calculating a player’s “On-Off” RAPTOR rating is relatively simple. To calculate it, we undertook essentially the same process as for “Box” RAPTOR, regressing various offensive and defensive ratings against Davis’s six-year RAPM estimates. RAPM can be replicated quite effectively using three types of on-court ratings.20

  1. The player’s offensive and defensive ratings — that is, how many points the team scored and allowed per 100 possessions while he was on the floor, adjusted for strength of opposition.
  2. The player’s courtmates’ weighted average offensive and defensive ratings21 when they weren’t sharing the floor with the player. The average is weighted by the number of possessions that the courtmate shared with the player, multiplied by the number of possessions that the courtmate had without the player.22
  3. Finally, the player’s courtmates’ other courtmates’ weighted average offensive and defensive ratings.23 Whereas a player’s raw offensive and defensive ratings (step 1) are associated with positive coefficients (It’s good if a player’s team is outscoring its opponent while he’s on the floor!) and the player’s courtmates’ ratings (step 2) are associated with negative coefficients (It’s a bad sign for a player’s if his teammates are doing well even when he’s not on the floor!), the ratings of his courtmates’ other courtmates are a positive indicator. (I know this part is a little confusing.) Essentially, high courtmates’ courtmates’ ratings mean the teammates who seemed like they were doing well without the player on the floor may only have been doing well because they were paired with other good teammates.

We find that further iterations (i.e., looking at a player’s courtmates’ courtmates’ courtmates’ ratings) don’t contribute toward predicting RAPM.

We also find that this comparatively simple way to evaluate a player’s on-court/off-court impact not only replicates RAPM extremely well in sample but also predicts out-of-sample RAPM as well or slightly better than RAPM itself, depending on the regression specification. In other words, RAPM doesn’t appear to add much value as compared with computationally simpler approaches to evaluating on-court/off-court ratings.

Combining and Adjusting Box and On-Off Ratings to Create Overall RAPTOR

Overall RAPTOR is a blend of the “Box” and “On-Off” component ratings. We determined the respective weight assigned to “Box” and “On-Off” RAPTOR ratings by testing how well they predicted RAPM out of sample. Specifically, overall RAPTOR is equal to roughly 85 percent of “Box” RAPTOR, plus 21 percent of “On-Off” RAPTOR. A couple of fairly obvious observations about these figures:

  • First, note that the combined value of “Box” and “On-Off” RAPTOR is slightly greater than 100 percent because they provide some nonredundant information. If a player’s “Box” rating is +3.0 and his “On-Off” rating is also +3.0, we’d exepct his overall RAPM to be slightly greater than +3.0, in other words.
  • Also, note that “Box” RAPTOR is quite a bit more predictive of out-of-sample performance than “On-Off” RAPTOR. While on-court/off-court ratings are sometimes treated as though they’re the holy grail of NBA statistics, they’re very noisy. Conversely, many areas of player performance that were once thought to be intractable to statistical analysis can now be measured through player-tracking or play-by-play statistics. Other analysts may differ, but we think the medium-term future of NBA analytics is probably more about assigning value to players based on discrete actions they take on the court and less in trying to perfect an RAPM-like approach.

After combining “Box” and “On-Off” ratings, RAPTOR is then adjusted in two ways. (These are the same adjustments that are made by BPM, so we are again indebted to BPM and Daniel Myers for inspiration.)

The score effects adjustment

If you’re about my age (41) and played a lot of NBA Jam as a kid, you’ll remember computer assistance, which was how the software helped teams who trailed by significant margins by magically making their shots more likely to go in. It turns out that there is something vaguely analogous to this in the real NBA! Relative to the personnel they have on the floor, teams perform substantially worse when they have large leads and substantially better when they trail by significant margins. These tendencies, which we call score effects, can have profound effects. As Jeremias Engleman writes, when a team is behind by 20 points, it’s expected to score around 6 points per 100 possessions more than it does in a tied game, which is like “replacing an average offensive player with LeBron [James].”

In nontechnical language: You need to adjust “junk time” statistics. When a team is way ahead, it tends to be less efficient, and its opponents tend to be more efficient. As a result, unadjusted statistics will tend to underrate players on good teams and overrate players on poor teams because players on good teams are more often playing with significant leads and lollygagging their way through games, especially in the regular season. In crunch time, these teams may have a bigger advantage than their raw stats imply.

Our score effects adjustment is a little different than some of the other ones we’ve seen. Instead of inferring how far a team was ahead or behind based on its average final score, we calculate it directly by evaluating how far it was ahead or behind in an average possession throughout the season. In some cases, this can make a fairly big difference. For instance, the 2018-19 Philadelphia 76ers had a lower average victory margin (+2.7 points) than the Indiana Pacers (+3.3 points). The 76ers frequently had established large leads by the fourth quarter, however, while the Pacers did not — so they actually led their opponents by a larger margin on average throughout the game. Adjusted for score effects, they were a better team, in other words. Furthermore, in examining the impact of score effects on individual players, we evaluate them only for possessions when the player was on the court, rather than the team’s rating for all possessions in the game.

Another important difference in RAPTOR’s score effects adjustment is that it recognizes that the effects become larger in later quarters. A team will coast more with a 15-point lead in the fourth quarter than in the second quarter, in other words. In addition, score effects are considerably larger in the regular season than in the playoffs. This should make intuitive sense: a team is less likely to step off the gas pedal in the postseason when where is more on the line.

How score effects impact NBA efficiency

For every 10 points that it leads by, its scoring margin is affected by ___ points per 100 possessions, controlling for the personnel it has on the floor:

Period Regular season Playoffs
First -1.1 -0.6
Second -1.7 -0.9
Third -2.3 -1.2
Fourth and OT -2.9 -1.5

Note that the adjustment is linear. The values in the chart reflect a 10-point lead. For instance, a team with a 10-point lead will be 2.3 points worse per 100 possessions than in a tied game. But you can multiply them to calculate score effects for any scoring margin. For instance, a team with a 20-point lead would be 4.6 points worse per 100 possessions in the 3rd quarter. Teams benefit from score effects when behind in the game, conversely; that is, they are more efficient than in a tied game.

The team effects adjustment

Finally, RAPTOR adjusts individual players’ ratings so that they sum up to reflect the team’s overall performance, adjusted for score effects and strength of competition. If the Golden State Warriors score 7 adjusted points per 100 possessions more than the league average, for instance, then the Warriors’ players’ offensive RAPTOR ratings should also add up to +7.0, weighted by playing time. In reconciling team and player ratings, we make bigger adjustments to players with higher offensive and defensive usage rates.24 Colloquially speaking, this means that if a team was better or worse than the sum of its parts, we give more of the credit or blame for that to the players who were most heavily involved with the offense or the defense, respectively.

Note that we do not apply the team effects adjustment in the predictive version of RAPTOR, PREDATOR, as it does not appear to improve out-of-sample performance. This implies that the differences between a team’s overall scoring margin and the sum of its statistical components may actually be due mostly to luck rather than necessarily reflecting any intangible or hard-to-measure skills.

Individual Pace Impact

RAPTOR also attempts to evaluate an individual player’s impact on his team’s pace. Because pace is partly a function of a team’s coach and system, these ratings were derived from an analysis only of players who switched teams, and seeing which factors were persistent in predicting pace from one team context to the next. The resulting pace impact estimates reflect a combination of essentially an on-court/off-court pace rating — how much, empirically, a team’s pace changed when the player was on or off the floor — plus various statistical inputs that correlate with pace. Both inducing and committing turnovers tends to increase pace, for instance, as does commiting and drawing fouls, and taking open shots. We estimate that the following players had the biggest impact on their team’s pace in 2018-19 (minimum 1000 minutes played):

Which players had the greatest impact on team pace?

RAPTOR Individual Pace Impact ratings for 2018-19

Increased pace Reduced pace
Russell Westbrook +2.7 Monte Morris -1.8
Stephen Curry +2.2 Ish Smith -1.8
De’Aaron Fox +2.1 Rodney Hood -1.4
Trae Young +1.8 Shelvin Mack -1.4
Lou Williams +1.7 Tristan Thompson -1.4
Draymond Green +1.6 Terry Rozier -1.4
Kent Bazemore +1.6 Fred VanVleet -1.4
Devin Booker +1.4 D.J. Augustin -1.4
Kyrie Irving +1.3 Ryan Arcidiacono -1.4
Giannis Antetokounmpo +1.3 Shaun Livingston -1.3

To be listed, players must have had a minimum of 1000 minutes played between the playoffs and regular season combined.

Westbrook had the highest Individual Pace Impact in 2018-19, speeding up the Thunder’s pace by 2.7 possessions per 48 minutes while he was on the floor, while the Nuggets’ Monte Morris did the most to slow down his team’s pace.

Overall, we find that about half of a team’s pace is a result of the players it has on the floor, while the other half reflects the coach and system.25

Replacement Level, WAR and Market Values

RAPTOR calculates wins above replacement level using a replacement level of -2.75 points per 100 possessions. The replacement level estimate is derived from evaluating the historical performance of players on two-way contracts, who are quite literally on the fringes between the major and minor leagues (the NBA and the G League), a status that reflects the traditional definition of replacement-level players.

In contrast to our previous system, RAPTOR uses the same overall replacement level (-2.75) across different positions, although note that replacement-level guards will tend to be terrible defensively and tolerable offensively, while the reverse is true for replacement-level bigs. This is because, unlike in many other advanced stats, RAPTOR ratings tend to be fairly even across the five traditional positions. The main exception is that point guards are slightly more valuable than shooting guards in RAPTOR on average, which makes sense to us since the league’s best point guards (think of a player like Curry) often have all the skills that off-guards do, but they also have additional ball-handling and passing abilities that off-guards sometimes lack.

RAPTOR ratings are relatively even across positions

And RAPTOR replacement level is set to -2.75 points per 100 possessions….

AVERAGE RAPTOR RATING PER 100 POSSESSIONS, 2013-14 through 2018-19 regular seasons Presumed replacement level
Position Offense Defense Combined Offense Defense Combined
PG +1.00 -0.50 +0.50 -1.10 -1.65 -2.75
SG +0.20 -0.55 -0.35 -1.50 -1.25 -2.75
SF -0.05 +0.05 +0.00 -1.90 -0.85 -2.75
PF -0.50 +0.25 -0.25 -2.30 -0.45 -2.75
C -0.90 +1.10 +0.20 -2.70 -0.05 -2.75

The precise formula that RAPTOR uses to calculate WAR is as follows…

\(\text{WAR} = ({RAPTOR} + 2.75) \times {Minutes Played} \times (({League Pace} + {Individual Pace Impact})/{League Pace}) \times {WAR multiplier}\)

… where the WAR multiplier is 0.0005102 for the regular season and 0.0005262 in the playoffs.26

On our player projection pages, you’ll also find estimated market values — for instance, a certain player is worth $120 million over the next five seasons. These are designed to be slightly nonlinear rather than being a straight-line extrapolation of WAR. That is, a 10-win player is slightly more than twice as valuable as a 5-win player. The reason is that having superstar players makes a team considerably more likely to advance far in the postseason. These market values reflect how NBA teams value both regular-season performance and championships, in other words.

PREDATOR and RAPTOR Projections

As mentioned, RAPTOR now fuels our team and player projections. Or more technically, PREDATOR does, since that’s the version of RAPTOR we use for projecting future performance. The variables in PREDATOR are essentially the same27 as those in RAPTOR, but they use coefficients calculated with out-of-sample rather than in-sample RAPM. However, because we also avoided variables that performed poorly in out-of-sample tests in constructing RAPTOR, it and PREDATOR are extremely well-correlated. PREDATOR and RAPTOR have a 0.98 correlation on offense, and 0.95 on defense.

Our projections also use a variety of biographical inputs apart from RAPTOR and PREDATOR ratings that help in projecting performance going forward:

  • Age
  • Draft position
  • NBA career length
  • Height
  • Weight
  • Position
  • Recent All-NBA, MVP and All-Star appearances

For college players making their NBA debuts, we also use variables related to the strength of their college program and the strength of their college program’s schedule. And for international rookies who did not play in the NCAA, we use variables related to both their country of birth and the country where they played professionally before coming to the NBA. In general, players who come from wealthy countries and who play in higher-quality international leagues start out of the gate faster but do not necessarily show as much improvement following their first few NBA seasons. Conversely, players who played in worse leagues and who come from poorer countries start out slower but show steeper improvement.

Otherwise, RAPTOR projections are essentially the same as our previous projection system, CARMELO, which is described here at some length. These projections basically involve a three-step process:

  1. Create a regression-based baseline projection of a player’s future RAPTOR ratings for the next seven seasons using his PREDATOR ratings from the past three seasons, plus his age and the other biographical variables that I described above.
  2. Identify similar or comparable players using a number of statistical and biographical categories; for instance, Damian Lillard’s top comparables include Chauncey Billups and Ray Allen.
  3. Tweak the player’s projection, and develop a range of uncertainty around the forecast, by seeing how the comparable players performed relative to their baselines when they were the same age as the player is now. For instance, if Allen had a better age-29 season28 than his baseline projection expected, that would favorably impact Lillard’s RAPTOR projection for this season.

Other than the adoption of RAPTOR rather than BPM and RPM as the basis for our projections, changes to our projection methodology this season are relatively subtle. They include the following:

  • We now calculate separate projections for the playoffs and the regular season. Differences between regular-season and playoff performance are mostly attributable to luck and strength of competition. However, there is some persistence in which players tend to perform better or worse in the playoffs than in the regular season. Thus, RAPTOR projections evaluate the difference between a player’s regular season and playoff performances in the past and carry a small amount of that gap forward to future seasons. For 2019-20, players with the largest positive playoff adjustments are Draymond Green (1.4 points per 100 possessions better in the playoffs), LeBron James (+0.9), P.J. Tucker (+0.8), Kawhi Leonard (+0.7), Nikola Jokic (+0.6), Joel Embiid (+0.6), Tristan Thompson (+0.6), Terry Rozier (+0.5) and Paul George (+0.5). And players with the largest downward adjustments for the playoffs are Damian Lillard (-0.9 points), DeMar DeRozan (-0.6), Eric Gordon (-0.6), Klay Thompson (-0.5) and JJ Redick (-0.5).
  • Several of the biographical variables that we employ this year are new. The most interesting one is probably awards received in the past three seasons, which is somewhat helpful for projecting out-of-sample performance. That is to say that MVP, All-NBA and All-Star voters can sometimes pick up on subtle aspects of player quality that RAPTOR misses.29
  • In weighting performance over the past three seasons, our projections previously assigned 60 percent of the weight to the most recent season, 30 percent to the second-most-recent season and 10 percent to the third-most-recent one. While this is a good rule of thumb for players in the middle of their career, it’s too conservative a weighting scheme for very young or very old players. Thus, the weights assigned to past seasons now depend on a player’s age. For a 23-year-old player entering his fourth NBA season, for instance, the program assigns around 76 percent of the weight to the player’s most recent season. What this means is that breakouts for young players (or declines for old players) mostly tend to “stick,” whereas you should expect more mean-reversion if a player shows a sharp apparent improvement or decline in mid-career.

Team Projections

As compared with our player projections, our process for calculating team projections is more straightforward. We create depth charts for each team and project playing time using a combination of algorithms and human inputs. Namely, we tell our depth charts program in which order the team prioritizes its players and (based on recent news accounts) which players are injured and for how long. The program then uses RAPTOR playing time recommendations to estimate how much each player will play at each position given these inputs. Players are allowed to slightly exceed their RAPTOR-recommended number of minutes per game, but if a player is playing significantly more minutes than recommended because the team is short-handed, our projections apply a penalty to his efficiency.

Once we have projected playing time, we can essentially just take a weighted30 sum of RAPTOR ratings to forecast the number of points a team will score and allow in a given game. We can then use Pythagorean expectation to estimate a team’s winning percentage. In the Pythagorean equation, we use an exponent of 14.3 for the regular season and 13.2 for the playoffs.31

One important wrinkle is that in summing up individual RAPTOR projections to the team level, we need to account for score effects. Since RAPTOR ratings reflect a player’s efficiency in a tied game, but good teams often play with a lead — which reduces efficiency — good teams will perform slightly worse than the sum of their RAPTOR ratings, and bad teams will perform slightly better than them. To account for this, we multiply the sum of a team’s player projections by 0.8 in the regular season and by 0.9 in the playoffs.

Approximate RAPTOR ratings for historic players

Since our player projections use data since the 1976-77 NBA season (the first year after the ABA-NBA merger) we also have to approximate RAPTOR ratings for past seasons, even though modern player tracking and play-by-play data wasn’t available then. This requires a few tricks that we don’t have to use on current data. For instance, to do a good job of replicating RAPTORs using older data, we have to adjust for position, giving a boost to shooting guards and small forwards and penalizing centers. We also make heavier use of a team’s overall offensive and defensive ratings than our current RAPTOR ratings do. For seasons from 2000-01 onward, we also use RPM (which accounts for a player’s on-court/off-court impact) as an input.

An interesting philosophical question is whether these Approximate RAPTOR ratings are an optimal reflection of which players were the best of their eras given the (somewhat limited) data available to examine their performance — or, rather, since RAPTORs are calibrated using only data since 2013-14, whether they essentially reflect which past players would have been best under modern conditions. Either way, they help to reveal something about how RAPTOR thinks about players. Here, for example, are the 500 best RAPTOR and Approximate RAPTOR seasons of all time, ranked by combined regular season and playoff WAR.

The 500 best RAPTOR seasons of all time

Using actual RAPTOR (2013-14 onward) and Approximate RAPTOR (1976-77 through 2012-13); all statistics reflect the regular season and playoffs combined for players with a minimum of 1,000 minutes played.

RAPTOR
Name
Season
Min. played
Off.
Def.
Total
WAR
Michael Jordan 1991 3,723 +9.1 +3.2 +12.3 28.8
LeBron James 2009 3,634 +9.3 +3.2 +12.6 28.5
Michael Jordan 1989 3,973 +8.3 +2.7 +11.0 28.0
Michael Jordan 1990 3,871 +8.6 +2.2 +10.8 27.0
Stephen Curry 2016 3,314 +10.4 +2.1 +12.5 26.7
Michael Jordan 1988 3,738 +7.5 +3.7 +11.2 26.6
Michael Jordan 1993 3,850 +7.6 +2.8 +10.4 26.0
Michael Jordan 1992 4,022 +7.0 +2.7 +9.6 25.5
Michael Jordan 1996 3,823 +7.6 +2.7 +10.3 25.5
Stephen Curry 2015 3,439 +8.6 +2.4 +11.0 25.1
LeBron James 2010 3,426 +9.2 +2.3 +11.4 24.8
LeBron James 2013 3,837 +8.5 +1.1 +9.6 24.2
Chris Paul 2009 3,203 +8.2 +3.7 +11.8 23.8
Kevin Garnett 2004 4,014 +4.4 +4.5 +8.8 23.6
Dwyane Wade 2006 3,851 +6.4 +2.8 +9.2 23.5
Draymond Green 2016 3,687 +3.9 +5.4 +9.4 23.5
John Stockton 1992 3,625 +7.7 +2.2 +9.9 23.4
Larry Bird 1986 3,883 +6.4 +2.6 +9.0 23.3
Tim Duncan 2003 4,202 +3.9 +4.2 +8.1 23.3
John Stockton 1991 3,476 +7.8 +2.2 +10.1 22.8
James Harden 2019 3,291 +9.6 +1.1 +10.7 22.8
Chris Paul 2008 3,492 +9.0 +1.0 +10.0 22.8
Michael Jordan 1997 3,910 +6.9 +1.8 +8.6 22.7
Chris Paul 2015 3,302 +8.6 +2.1 +10.7 22.6
Larry Bird 1987 4,020 +6.5 +1.7 +8.2 22.4
John Stockton 1988 3,320 +7.6 +2.8 +10.4 22.3
John Stockton 1989 3,310 +7.5 +2.8 +10.2 21.9
Shaquille O’Neal 2000 4,163 +4.4 +3.2 +7.6 21.8
LeBron James 2012 3,309 +7.9 +2.1 +10.0 21.6
Magic Johnson 1987 3,570 +8.2 +0.8 +9.0 21.3
Magic Johnson 1991 3,756 +8.3 +0.0 +8.4 21.3
Kevin Garnett 2003 3,586 +4.9 +4.1 +8.9 21.2
Larry Bird 1988 3,728 +6.6 +1.8 +8.4 21.1
LeBron James 2011 3,985 +6.0 +1.5 +7.6 21.1
LeBron James 2007 4,083 +4.6 +2.6 +7.3 21.0
James Harden 2018 3,172 +8.8 +1.3 +10.1 20.9
Kobe Bryant 2008 4,055 +6.1 +1.2 +7.2 20.8
Magic Johnson 1989 3,404 +8.6 +0.5 +9.2 20.7
Stephen Curry 2017 3,239 +9.3 -0.1 +9.2 20.7
Dwyane Wade 2009 3,333 +7.1 +2.3 +9.4 20.6
LeBron James 2008 3,579 +6.8 +1.6 +8.4 20.5
Larry Bird 1985 3,976 +5.4 +1.9 +7.3 20.4
Charles Barkley 1990 3,504 +7.5 +1.2 +8.6 20.4
David Robinson 1994 3,387 +4.6 +4.5 +9.1 20.4
John Stockton 1994 3,566 +7.0 +1.4 +8.4 20.3
Magic Johnson 1990 3,313 +9.0 +0.3 +9.3 20.3
Scottie Pippen 1992 4,063 +4.5 +2.5 +7.0 20.2
LeBron James 2006 3,965 +6.4 +0.8 +7.3 20.2
Hakeem Olajuwon 1993 3,760 +2.0 +5.8 +7.8 20.2
David Robinson 1995 3,697 +2.8 +5.2 +7.9 20.1
John Stockton 1990 3,109 +8.2 +1.7 +9.9 20.1
John Stockton 1997 3,635 +7.1 +0.9 +8.0 20.0
Larry Bird 1984 3,989 +4.7 +2.3 +7.1 20.0
LeBron James 2016 3,531 +6.0 +2.2 +8.2 19.9
Ray Allen 2001 3,897 +7.1 +0.1 +7.2 19.8
Charles Barkley 1993 3,885 +5.5 +1.7 +7.2 19.7
Kevin Durant 2014 3,937 +7.1 -0.3 +6.8 19.7
Jason Kidd 2003 3,841 +4.4 +2.9 +7.3 19.7
Magic Johnson 1982 3,553 +6.1 +1.9 +8.1 19.6
Clyde Drexler 1992 3,598 +6.4 +1.4 +7.8 19.6
Paul George 2019 3,045 +5.3 +4.2 +9.5 19.4
Michael Jordan 1987 3,409 +5.5 +2.8 +8.4 19.4
Scottie Pippen 1996 3,567 +5.1 +2.7 +7.8 19.4
James Harden 2015 3,617 +7.7 -0.2 +7.5 19.3
Hakeem Olajuwon 1994 4,266 +0.8 +5.3 +6.1 19.3
Chris Paul 2014 2,643 +7.7 +3.7 +11.4 19.3
David Robinson 1996 3,372 +3.6 +5.0 +8.5 19.2
LeBron James 2017 3,538 +6.9 +0.9 +7.8 19.2
Scottie Pippen 1997 3,848 +4.9 +2.1 +7.0 19.2
John Stockton 1995 3,060 +8.0 +1.5 +9.5 19.0
Kobe Bryant 2009 3,900 +5.9 +0.8 +6.7 19.0
Kevin Durant 2013 3,604 +6.5 +1.0 +7.5 18.9
Chris Paul 2011 3,130 +6.7 +2.4 +9.0 18.8
Dirk Nowitzki 2006 4,072 +5.9 +0.4 +6.3 18.8
Dirk Nowitzki 2003 3,839 +4.6 +2.2 +6.8 18.8
John Stockton 1996 3,594 +7.0 +0.4 +7.5 18.8
Mookie Blaylock 1997 3,497 +4.6 +3.1 +7.7 18.6
Tim Duncan 2002 3,709 +3.6 +3.5 +7.1 18.5
Kareem Abdul-Jabbar 1977 3,483 +4.5 +3.1 +7.6 18.5
Tracy McGrady 2003 3,262 +8.0 +0.3 +8.4 18.5
Anfernee Hardaway 1996 3,488 +6.6 +1.0 +7.6 18.5
Magic Johnson 1983 3,550 +6.5 +0.9 +7.4 18.4
Julius Erving 1982 3,569 +5.0 +2.4 +7.3 18.4
Scottie Pippen 1991 3,718 +3.9 +3.0 +6.8 18.3
Manu Ginobili 2005 2,965 +5.9 +3.3 +9.2 18.3
Gary Payton 1996 4,073 +3.5 +2.4 +6.0 18.3
Kobe Bryant 2003 3,932 +5.4 +0.9 +6.3 18.2
Nikola Jokic 2019 3,061 +6.1 +2.7 +8.7 18.2
David Robinson 1991 3,261 +2.8 +5.5 +8.2 18.2
Stephen Curry 2014 3,142 +7.8 +0.5 +8.3 18.1
Michael Jordan 1998 4,053 +4.3 +1.6 +6.0 18.1
Scottie Pippen 1995 3,410 +3.6 +4.0 +7.6 18.0
Dwyane Wade 2011 3,651 +5.6 +1.2 +6.8 17.9
Kawhi Leonard 2017 2,903 +7.3 +2.0 +9.3 17.9
Dwyane Wade 2010 3,002 +7.2 +1.7 +8.9 17.9
Kevin Garnett 2008 3,315 +2.9 +5.0 +7.8 17.9
Jason Kidd 2002 3,859 +4.1 +2.1 +6.2 17.7
Karl Malone 1996 3,838 +3.9 +2.3 +6.2 17.6
Tim Duncan 2007 3,462 +2.2 +5.0 +7.2 17.6
Tim Hardaway 1997 3,837 +4.8 +1.4 +6.2 17.6
Clyde Drexler 1991 3,485 +5.5 +1.6 +7.1 17.6
Stephen Curry 2019 3,177 +7.5 +0.3 +7.8 17.6
Charles Barkley 1989 3,223 +7.4 +0.5 +7.9 17.5
Kawhi Leonard 2016 2,719 +5.1 +4.7 +9.9 17.5
Ben Wallace 2004 3,974 -1.5 +7.3 +5.9 17.5
Magic Johnson 1984 3,404 +5.9 +1.3 +7.3 17.5
Isiah Thomas 1985 3,444 +6.3 +0.9 +7.2 17.5
LeBron James 2018 3,948 +7.5 -1.7 +5.8 17.4
Michael Jordan 1985 3,315 +5.9 +1.6 +7.5 17.4
Karl Malone 1997 3,814 +4.9 +1.3 +6.2 17.4
James Harden 2017 3,354 +7.4 -0.3 +7.1 17.3
Draymond Green 2015 3,274 +1.9 +5.5 +7.3 17.3
Terry Porter 1991 3,260 +6.2 +1.4 +7.7 17.3
Gary Payton 1997 3,759 +4.9 +1.3 +6.2 17.3
Kevin Durant 2010 3,470 +5.2 +1.8 +7.0 17.2
Scottie Pippen 1994 3,143 +3.8 +4.1 +7.9 17.2
Vince Carter 2001 3,518 +6.3 +0.5 +6.8 17.2
Magic Johnson 1985 3,468 +6.9 +0.0 +6.9 17.1
Shaquille O’Neal 2002 3,198 +4.2 +3.4 +7.7 17.0
Clyde Drexler 1990 3,536 +4.7 +1.9 +6.6 17.0
Mike Conley 2013 3,332 +3.4 +3.8 +7.2 16.9
David Robinson 1990 3,377 +1.9 +5.2 +7.1 16.9
Karl Malone 1998 3,825 +4.9 +1.0 +5.9 16.9
Julius Erving 1981 3,466 +4.0 +2.8 +6.8 16.9
Draymond Green 2017 3,064 +1.4 +6.4 +7.8 16.8
Gary Payton 2000 3,646 +5.7 +0.6 +6.3 16.8
Magic Johnson 1986 3,119 +7.3 +0.5 +7.8 16.8
Horace Grant 1992 3,715 +3.6 +2.5 +6.1 16.8
Gary Payton 1998 3,573 +5.6 +0.8 +6.4 16.8
Russell Westbrook 2016 3,424 +6.6 -0.0 +6.6 16.8
Paul George 2014 3,679 +3.0 +3.0 +6.0 16.7
John Stockton 2001 2,583 +7.0 +2.9 +9.9 16.6
Magic Johnson 1988 3,602 +6.4 -0.2 +6.2 16.6
Shaquille O’Neal 2001 3,600 +4.8 +1.4 +6.2 16.6
Shawn Marion 2006 4,112 +2.2 +2.9 +5.1 16.5
Mookie Blaylock 1994 3,330 +4.3 +2.7 +6.9 16.4
Kobe Bryant 2001 3,477 +5.3 +1.1 +6.4 16.3
Paul Pierce 2008 3,864 +3.9 +1.5 +5.5 16.3
Moses Malone 1983 3,446 +3.2 +3.3 +6.5 16.3
Clyde Drexler 1995 3,577 +5.1 +0.9 +6.0 16.3
Kevin Garnett 2005 3,121 +4.6 +3.0 +7.6 16.3
Tracy McGrady 2005 3,483 +4.7 +1.7 +6.4 16.3
David Robinson 1992 2,564 +2.5 +7.2 +9.7 16.2
Charles Barkley 1991 2,824 +7.6 +0.8 +8.4 16.2
Kobe Bryant 2006 3,591 +6.7 -0.6 +6.1 16.2
Terry Porter 1990 3,596 +5.5 +0.6 +6.0 16.2
John Stockton 1993 3,056 +6.3 +1.3 +7.6 16.2
Baron Davis 2002 3,719 +4.2 +1.5 +5.7 16.1
Clyde Drexler 1988 3,230 +5.3 +1.7 +7.0 16.1
Tim Duncan 2001 3,700 +1.8 +3.9 +5.7 16.0
Julius Erving 1980 3,506 +3.5 +2.6 +6.2 16.0
LeBron James 2005 3,388 +5.1 +1.4 +6.5 16.0
Charles Barkley 1988 3,170 +6.9 +0.3 +7.1 15.9
Kareem Abdul-Jabbar 1980 3,761 +3.1 +2.4 +5.6 15.9
Manu Ginobili 2008 2,858 +5.4 +2.7 +8.1 15.9
Magic Johnson 1980 3,453 +4.6 +1.6 +6.2 15.9
Kyle Lowry 2016 3,617 +5.3 +0.4 +5.8 15.8
Shawn Marion 2007 3,465 +2.7 +3.5 +6.2 15.8
Chris Paul 2013 2,559 +8.0 +1.3 +9.3 15.8
Tim Hardaway 1991 3,611 +5.1 +0.7 +5.8 15.8
Chris Paul 2012 2,604 +7.3 +1.8 +9.1 15.7
Kobe Bryant 2010 3,758 +4.2 +1.1 +5.3 15.7
Paul Pierce 2002 3,974 +3.3 +1.6 +4.9 15.7
Chris Paul 2016 2,545 +7.7 +1.6 +9.3 15.7
Jason Kidd 2009 3,272 +3.2 +3.4 +6.5 15.5
Mookie Blaylock 1996 3,319 +4.2 +2.1 +6.4 15.5
Shaquille O’Neal 1995 3,728 +3.8 +1.6 +5.4 15.5
Grant Hill 1997 3,350 +4.3 +2.0 +6.3 15.4
Tim Duncan 2005 3,072 +2.7 +4.5 +7.1 15.4
Chauncey Billups 2006 3,630 +6.5 -1.0 +5.6 15.4
Russell Westbrook 2017 2,996 +7.8 -0.9 +6.8 15.3
Baron Davis 2001 3,589 +3.1 +2.5 +5.5 15.3
Hakeem Olajuwon 1989 3,186 +0.2 +6.4 +6.6 15.3
Ben Wallace 2003 3,595 -1.4 +6.9 +5.6 15.3
Clyde Drexler 1989 3,192 +5.2 +1.5 +6.6 15.3
Dirk Nowitzki 2001 3,524 +3.9 +1.8 +5.7 15.2
Dirk Nowitzki 2005 3,571 +3.8 +1.8 +5.6 15.2
Chauncey Billups 2008 3,002 +6.9 +0.3 +7.2 15.2
Fat Lever 1988 3,334 +3.8 +2.4 +6.2 15.2
Jason Kidd 2007 3,417 +4.3 +1.7 +5.9 15.2
Dirk Nowitzki 2011 3,330 +4.2 +1.9 +6.1 15.2
Anthony Davis 2015 2,627 +3.8 +4.7 +8.5 15.2
David Robinson 1993 3,632 +1.2 +4.3 +5.4 15.1
LeBron James 2014 3,665 +6.0 -0.9 +5.2 15.1
Kevin Johnson 1989 3,673 +5.4 -0.1 +5.3 15.1
Victor Oladipo 2018 2,813 +3.4 +4.1 +7.5 15.1
Karl Malone 1992 3,742 +4.1 +1.0 +5.1 15.0
Dwight Howard 2009 3,724 +0.7 +4.4 +5.1 15.0
Damian Lillard 2019 3,488 +6.4 -0.8 +5.6 15.0
Larry Bird 1981 3,989 +2.1 +2.5 +4.6 15.0
Steve Nash 2006 3,594 +6.5 -1.0 +5.5 15.0
Larry Bird 1982 3,413 +3.3 +2.5 +5.8 14.9
Shaquille O’Neal 1994 3,350 +4.1 +1.9 +6.0 14.9
Manu Ginobili 2007 2,662 +5.5 +2.6 +8.1 14.9
Steve Francis 2001 3,194 +5.3 +1.1 +6.4 14.9
Shawn Marion 2003 3,655 +2.5 +2.7 +5.2 14.9
Rajon Rondo 2010 3,938 +2.4 +2.2 +4.6 14.8
Jimmy Butler 2017 3,048 +4.6 +2.2 +6.8 14.8
Maurice Cheeks 1982 3,263 +3.6 +2.5 +6.1 14.8
Shawn Marion 2005 3,781 +3.1 +1.8 +4.9 14.8
Dwight Howard 2010 3,340 +0.9 +5.0 +5.9 14.8
Kareem Abdul-Jabbar 1979 3,524 +3.0 +2.5 +5.5 14.7
Hakeem Olajuwon 1986 3,233 +1.8 +4.2 +6.1 14.7
Larry Bird 1983 3,222 +4.1 +2.2 +6.2 14.7
Charles Barkley 1986 3,449 +3.5 +2.0 +5.5 14.7
Elton Brand 2006 3,616 +3.5 +1.7 +5.2 14.6
Paul George 2016 3,094 +3.5 +2.6 +6.2 14.6
Patrick Ewing 1994 4,004 -1.0 +5.3 +4.4 14.6
Kevin Garnett 2002 3,305 +3.6 +2.3 +6.0 14.6
Dwight Howard 2011 3,193 +1.1 +5.1 +6.2 14.6
Kenny Anderson 1997 3,250 +4.4 +1.6 +6.0 14.6
Derrick Rose 2011 3,675 +5.3 -0.3 +5.0 14.5
Julius Erving 1977 3,698 +3.0 +1.9 +4.9 14.5
Tracy McGrady 2001 3,265 +4.0 +1.9 +6.0 14.5
Kawhi Leonard 2019 2,979 +5.7 +0.9 +6.6 14.5
Kobe Bryant 2004 3,420 +5.1 +0.4 +5.5 14.5
James Harden 2014 3,040 +6.5 -0.1 +6.4 14.4
Anfernee Hardaway 1995 3,750 +4.9 -0.1 +4.8 14.4
Tracy McGrady 2002 3,090 +5.1 +1.3 +6.4 14.4
Hakeem Olajuwon 1987 3,149 +1.0 +5.2 +6.2 14.4
Karl Malone 1994 4,032 +2.3 +1.9 +4.2 14.4
John Stockton 2000 2,782 +6.2 +1.2 +7.4 14.4
Kobe Bryant 2002 3,896 +4.6 -0.2 +4.4 14.4
Dan Majerle 1993 4,270 +3.3 +0.6 +3.8 14.4
Kobe Bryant 2007 3,355 +5.8 -0.2 +5.6 14.3
Andrei Kirilenko 2004 2,895 +3.4 +3.7 +7.0 14.3
Brandon Roy 2009 3,141 +5.8 +0.4 +6.2 14.3
Stephen Curry 2013 3,480 +5.3 -0.0 +5.3 14.3
Vince Carter 2006 3,356 +3.5 +2.0 +5.5 14.3
Gilbert Arenas 2006 3,668 +5.7 -0.9 +4.8 14.3
Giannis Antetokounmpo 2019 2,872 +3.9 +2.9 +6.8 14.3
Kevin Johnson 1990 3,364 +6.0 -0.5 +5.5 14.2
Steve Nash 2007 3,095 +7.5 -1.2 +6.3 14.2
Rashard Lewis 2009 3,845 +2.5 +1.9 +4.4 14.2
Allen Iverson 2001 3,995 +3.5 +0.6 +4.1 14.2
Kevin Garnett 2006 2,957 +3.5 +3.2 +6.7 14.1
Maurice Cheeks 1986 3,789 +3.9 +0.6 +4.6 14.1
Kevin Durant 2012 3,383 +5.2 +0.1 +5.4 14.1
Gus Williams 1980 3,533 +2.8 +2.2 +5.1 14.1
Hakeem Olajuwon 1995 3,782 +0.8 +3.7 +4.5 14.1
Kevin Durant 2016 3,304 +5.5 -0.0 +5.4 14.1
Manu Ginobili 2011 2,600 +6.0 +1.8 +7.8 14.1
Jason Kidd 2006 3,425 +3.6 +1.8 +5.3 14.1
Rudy Gobert 2017 2,990 +1.0 +5.6 +6.5 14.1
Byron Scott 1988 3,945 +3.5 +0.7 +4.2 14.0
Isiah Thomas 1984 3,205 +4.7 +1.0 +5.8 14.0
Chris Paul 2006 2,808 +4.0 +3.0 +7.0 13.9
Alvin Robertson 1986 2,976 +2.6 +3.8 +6.4 13.9
Kevin Johnson 1991 2,918 +6.0 +0.6 +6.7 13.9
Karl Malone 1990 3,325 +4.2 +1.2 +5.4 13.9
Ben Wallace 2006 3,532 -1.5 +6.5 +5.0 13.9
Karl Malone 1995 3,342 +3.5 +1.9 +5.4 13.9
Terry Porter 1992 3,654 +4.2 +0.4 +4.6 13.9
Mookie Blaylock 1995 3,190 +3.8 +2.0 +5.8 13.9
Isiah Thomas 1988 3,838 +2.8 +1.4 +4.2 13.9
Gary Payton 1995 3,187 +4.7 +1.1 +5.8 13.9
Scottie Pippen 1993 3,912 +2.3 +1.9 +4.2 13.8
Paul Pierce 2005 3,237 +4.3 +1.2 +5.5 13.8
Tim Hardaway 1998 3,253 +5.1 +0.5 +5.6 13.8
Paul Pressey 1986 3,234 +3.8 +1.8 +5.6 13.8
Deron Williams 2010 3,200 +5.7 -0.0 +5.7 13.8
Reggie Miller 1995 3,306 +5.5 -0.1 +5.4 13.8
David Robinson 1998 2,810 +2.0 +4.9 +6.9 13.8
Steve Nash 2005 3,183 +7.3 -1.5 +5.8 13.8
Ray Allen 2009 3,441 +4.5 +0.6 +5.1 13.8
Doc Rivers 1987 2,835 +5.1 +1.7 +6.8 13.8
Jeff Hornacek 1992 3,421 +4.1 +1.0 +5.1 13.8
Eddie Jones 1998 3,386 +3.8 +1.4 +5.2 13.7
Clyde Drexler 1987 3,267 +3.9 +1.6 +5.5 13.7
Kobe Bryant 2000 3,381 +3.7 +1.4 +5.1 13.7
John Stockton 2002 2,707 +5.2 +2.0 +7.1 13.7
Sam Cassell 2004 3,335 +5.1 +0.2 +5.3 13.7
Chris Paul 2018 2,364 +7.0 +1.6 +8.6 13.7
Chris Mullin 1991 3,681 +4.0 +0.5 +4.5 13.6
Patrick Ewing 1992 3,632 -0.2 +4.8 +4.6 13.6
Marc Gasol 2013 3,405 +0.7 +4.4 +5.1 13.6
Tim Duncan 2004 2,932 +1.9 +4.5 +6.4 13.6
Sidney Moncrief 1984 3,693 +3.9 +0.6 +4.5 13.6
Kevin Love 2014 2,797 +5.7 +0.9 +6.6 13.6
Gilbert Arenas 2007 2,942 +6.2 +0.1 +6.2 13.6
Kyle Lowry 2019 3,114 +3.7 +1.9 +5.6 13.5
Kevin McHale 1987 3,887 +3.9 +0.2 +4.1 13.5
Chauncey Billups 2005 3,851 +3.8 +0.2 +4.1 13.5
Rajon Rondo 2009 3,219 +3.1 +2.4 +5.4 13.5
Dirk Nowitzki 2007 3,059 +5.5 +0.4 +5.9 13.5
Kevin Durant 2011 3,760 +4.7 -0.5 +4.2 13.5
Sidney Moncrief 1982 3,232 +4.4 +1.1 +5.5 13.5
Sleepy Floyd 1987 3,478 +5.4 -0.6 +4.8 13.5
Kyle Lowry 2014 3,133 +4.3 +1.2 +5.6 13.5
Larry Nance 1992 3,561 +2.6 +2.1 +4.7 13.5
Hakeem Olajuwon 1990 3,285 -1.4 +6.7 +5.3 13.4
David Robinson 2001 2,780 +0.6 +6.1 +6.7 13.4
Reggie Miller 1994 3,214 +4.9 +0.5 +5.4 13.4
Deron Williams 2008 3,572 +5.5 -0.9 +4.6 13.4
Russell Westbrook 2013 2,929 +5.3 +0.9 +6.2 13.4
Charles Barkley 1987 2,950 +5.3 +0.8 +6.1 13.4
Ray Allen 2005 3,500 +6.1 -1.4 +4.7 13.4
Doc Rivers 1988 2,911 +4.9 +1.3 +6.2 13.4
Brent Barry 2002 3,189 +4.6 +0.9 +5.5 13.4
Tim Duncan 2008 3,317 +0.9 +4.3 +5.2 13.4
Doug Christie 2003 3,091 +2.3 +3.5 +5.7 13.3
Karl Malone 1993 3,315 +3.9 +1.3 +5.2 13.3
LeBron James 2015 3,337 +4.8 +0.2 +5.0 13.3
Joel Embiid 2019 2,488 +2.7 +4.8 +7.5 13.3
Kevin Durant 2017 2,603 +5.9 +1.1 +7.1 13.3
Ben Wallace 2002 3,329 -0.7 +5.8 +5.1 13.3
Charles Barkley 1995 2,772 +5.0 +1.6 +6.6 13.3
Andre Iguodala 2009 3,538 +2.7 +1.9 +4.6 13.2
Stephon Marbury 2005 3,281 +6.0 -0.8 +5.2 13.2
Fat Lever 1987 3,153 +3.6 +1.9 +5.5 13.2
Chris Paul 2017 2,181 +7.9 +1.2 +9.1 13.2
Chauncey Billups 2007 3,182 +5.7 -0.3 +5.4 13.2
Gary Payton 2002 3,508 +4.8 -0.2 +4.6 13.2
Karl Malone 1991 3,685 +3.1 +1.1 +4.2 13.1
Reggie Miller 2000 3,879 +4.3 -0.5 +3.8 13.1
Maurice Cheeks 1981 2,928 +3.0 +3.0 +6.0 13.1
James Harden 2016 3,318 +5.6 -0.7 +4.9 13.1
Baron Davis 2004 2,946 +4.1 +1.7 +5.9 13.1
Hakeem Olajuwon 1988 2,987 +0.7 +5.1 +5.8 13.1
Charles Barkley 1992 2,881 +5.1 +1.0 +6.1 13.1
Eddie Jones 2000 2,978 +3.5 +2.3 +5.8 13.0
Jeff Hornacek 1996 3,232 +4.9 +0.2 +5.1 13.0
Joakim Noah 2014 3,030 +1.2 +4.5 +5.7 13.0
Tim Duncan 2006 3,277 +1.5 +3.6 +5.0 13.0
Pau Gasol 2009 3,930 +2.9 +0.9 +3.7 13.0
Ron Harper 1989 3,040 +3.3 +2.3 +5.6 13.0
Micheal Ray Richardson 1985 3,252 +3.0 +2.1 +5.1 13.0
Kevin Garnett 2007 2,995 +2.2 +3.6 +5.8 13.0
Maurice Cheeks 1983 2,948 +3.8 +2.0 +5.9 13.0
Kevin Durant 2018 3,132 +5.9 -0.7 +5.2 13.0
Derek Harper 1988 3,634 +3.4 +0.9 +4.2 13.0
Sidney Moncrief 1983 3,087 +4.9 +0.6 +5.5 12.9
Eddie Jones 2002 3,156 +1.9 +3.4 +5.3 12.9
Giannis Antetokounmpo 2018 3,036 +3.3 +2.2 +5.5 12.9
Reggie Miller 1991 3,165 +6.3 -1.0 +5.3 12.9
Bradley Beal 2017 3,189 +4.9 +0.1 +5.1 12.9
Isiah Thomas 1987 3,575 +3.4 +0.8 +4.2 12.9
Dennis Rodman 1992 3,457 +2.4 +2.3 +4.6 12.9
Steve Francis 2003 3,318 +3.3 +1.5 +4.8 12.9
Kawhi Leonard 2015 2,283 +3.4 +4.8 +8.2 12.9
Derek Harper 1990 3,126 +4.0 +1.2 +5.3 12.9
Shaquille O’Neal 2004 3,381 +2.7 +1.9 +4.6 12.8
Jeff Hornacek 1997 3,296 +4.2 +0.6 +4.9 12.8
Anthony Davis 2018 3,085 +1.3 +4.0 +5.3 12.8
Damian Lillard 2018 2,832 +6.2 -0.1 +6.0 12.8
Moses Malone 1981 4,200 +2.5 +0.8 +3.2 12.8
Kawhi Leonard 2014 2,659 +1.7 +4.9 +6.6 12.8
Marques Johnson 1981 2,808 +5.3 +0.9 +6.2 12.8
Jason Kidd 2010 3,124 +3.2 +2.1 +5.3 12.8
Kevin Durant 2019 3,144 +5.2 -0.2 +5.1 12.8
Paul George 2013 3,752 +1.1 +2.8 +3.8 12.8
Derek Harper 1987 2,679 +5.2 +1.4 +6.6 12.8
Jimmy Butler 2018 2,334 +5.7 +2.4 +8.1 12.7
Clyde Drexler 1997 2,894 +4.3 +1.5 +5.8 12.7
Pau Gasol 2011 3,395 +3.0 +1.7 +4.7 12.7
Bobby Jones 1977 2,606 +2.5 +4.3 +6.8 12.7
Larry Bird 1990 3,151 +4.0 +1.2 +5.2 12.7
David Robinson 2000 2,712 +0.8 +5.6 +6.4 12.7
Lamar Odom 2009 3,051 +1.7 +3.6 +5.3 12.7
Reggie Miller 1998 3,423 +4.9 -0.5 +4.5 12.6
Hersey Hawkins 1991 3,439 +3.2 +1.2 +4.4 12.6
Dirk Nowitzki 2008 2,980 +4.6 +0.9 +5.6 12.6
Johnny Moore 1983 2,966 +3.7 +1.9 +5.6 12.6
George Gervin 1979 3,401 +3.9 +0.6 +4.5 12.6
Shaquille O’Neal 2003 3,016 +5.0 +0.5 +5.4 12.6
Doug Christie 2002 3,442 +2.2 +2.2 +4.4 12.6
Dominique Wilkins 1991 3,273 +4.3 +0.5 +4.8 12.6
Allen Iverson 2008 3,582 +4.2 +0.0 +4.2 12.6
Tim Hardaway 1992 3,508 +4.8 -0.5 +4.3 12.6
Hersey Hawkins 1997 3,238 +3.5 +1.3 +4.8 12.6
Giannis Antetokounmpo 2017 3,088 +2.8 +2.5 +5.2 12.6
Norm Nixon 1979 3,472 +3.6 +0.7 +4.3 12.6
Luol Deng 2011 3,895 +1.5 +2.0 +3.5 12.5
Terrell Brandon 1996 2,695 +5.3 +1.1 +6.4 12.5
Dana Barros 1995 3,318 +5.2 -0.5 +4.7 12.5
Paul Pierce 2011 3,117 +3.2 +1.9 +5.1 12.5
Isiah Thomas 1990 3,751 +2.4 +1.3 +3.7 12.5
Bill Walton 1977 3,019 +1.7 +3.7 +5.3 12.5
Dominique Wilkins 1987 3,329 +3.8 +0.9 +4.6 12.5
Rickey Green 1984 3,172 +3.1 +1.8 +5.0 12.5
Baron Davis 2008 3,196 +4.0 +0.9 +4.9 12.5
Baron Davis 2007 2,666 +4.2 +2.0 +6.3 12.5
Gus Williams 1982 3,191 +3.1 +1.9 +4.9 12.5
Scottie Pippen 2000 3,363 +2.5 +1.9 +4.4 12.4
Shawn Marion 2001 2,996 +1.4 +4.0 +5.4 12.4
Dirk Nowitzki 2002 3,248 +4.6 +0.2 +4.7 12.4
Karl Malone 2000 3,333 +4.0 +0.6 +4.6 12.4
Andre Iguodala 2008 3,476 +1.9 +2.3 +4.2 12.4
Reggie Miller 1990 3,317 +5.5 -0.9 +4.6 12.4
Jack Sikma 1982 3,364 +0.6 +3.9 +4.5 12.4
Alvin Robertson 1991 2,716 +3.0 +3.2 +6.1 12.4
Johnny Moore 1985 2,857 +3.4 +2.4 +5.7 12.4
Kemba Walker 2019 2,863 +5.0 +0.8 +5.7 12.3
Dwyane Wade 2012 2,532 +4.3 +2.4 +6.7 12.3
Reggie Miller 1993 3,129 +5.3 -0.3 +5.0 12.3
Manu Ginobili 2010 2,502 +5.7 +1.1 +6.8 12.3
Chauncey Billups 2004 3,639 +3.5 +0.3 +3.8 12.3
Eddie Jones 1997 3,281 +2.7 +1.9 +4.6 12.3
Jason Kidd 2004 2,924 +3.2 +2.2 +5.5 12.3
Kevin Garnett 2001 3,367 +2.2 +2.2 +4.4 12.2
Steve Nash 2010 3,199 +6.7 -2.0 +4.8 12.2
Mark Price 1992 2,741 +6.5 -0.5 +6.0 12.2
Scottie Pippen 1998 2,488 +3.9 +2.8 +6.7 12.2
Dwyane Wade 2005 3,545 +3.7 +0.3 +4.0 12.2
Bill Laimbeer 1990 3,342 +0.1 +4.2 +4.3 12.2
Robert Reid 1981 3,831 +1.3 +2.1 +3.4 12.2
Fat Lever 1989 2,803 +3.7 +2.1 +5.8 12.2
Kemba Walker 2018 2,736 +5.4 +0.6 +6.0 12.2
Jason Kidd 2005 2,617 +4.3 +2.0 +6.3 12.1
Mark Jackson 1988 3,420 +2.8 +1.4 +4.2 12.1
Jrue Holiday 2018 3,275 +2.4 +2.0 +4.4 12.1
Klay Thompson 2015 3,216 +4.0 +0.5 +4.5 12.1
Adrian Dantley 1984 3,438 +5.8 -1.7 +4.1 12.1
Moses Malone 1982 3,534 +3.8 +0.2 +4.0 12.0
Dwyane Wade 2013 3,173 +3.0 +1.6 +4.7 12.0
Kyle Lowry 2018 2,871 +4.9 +0.4 +5.3 12.0
James Harden 2013 3,228 +5.3 -0.8 +4.5 12.0
Micheal Ray Richardson 1981 3,261 +2.5 +2.0 +4.5 12.0
DeAndre Jordan 2015 3,302 +3.1 +1.3 +4.4 12.0
Nick Anderson 1995 3,402 +3.5 +0.6 +4.2 12.0
Andre Miller 2001 2,848 +4.0 +1.5 +5.5 12.0
Andrei Kirilenko 2006 2,604 +2.3 +4.0 +6.3 12.0
Andre Miller 2002 3,023 +5.7 -0.6 +5.1 12.0
Dominique Wilkins 1990 2,888 +5.2 +0.2 +5.4 12.0
Isiah Thomas 1986 2,953 +4.7 +0.5 +5.2 12.0
Mark Price 1990 2,898 +5.5 -0.2 +5.4 12.0
Karl Malone 1989 3,262 +2.7 +1.7 +4.4 12.0
Gary Payton 2001 3,244 +4.4 +0.1 +4.5 12.0
Robert Parish 1981 2,790 +1.4 +4.2 +5.6 12.0
Ray Allen 2006 3,022 +6.6 -1.6 +5.0 12.0
Julius Erving 1983 2,914 +3.4 +1.9 +5.3 12.0
Jeff Hornacek 1990 2,861 +4.3 +1.1 +5.4 11.9
Steve Nash 2008 2,963 +6.8 -1.6 +5.2 11.9
Jason Kidd 2001 3,231 +2.2 +2.3 +4.5 11.9
Metta World Peace 2004 3,298 +1.5 +2.7 +4.3 11.9
Maurice Cheeks 1985 3,099 +3.4 +1.3 +4.8 11.9
Micheal Ray Richardson 1980 3,060 +3.1 +1.7 +4.8 11.9
Scottie Pippen 1990 3,760 +1.1 +2.2 +3.3 11.9
Stephen Curry 2018 2,186 +8.1 -0.5 +7.6 11.8
Russell Westbrook 2018 3,149 +4.3 +0.1 +4.4 11.8
Micheal Williams 1992 2,856 +3.0 +2.3 +5.3 11.8
Ray Allen 2003 2,880 +5.1 +0.0 +5.1 11.8
Shane Battier 2006 2,968 +0.8 +4.3 +5.1 11.8
Chris Mullin 1992 3,514 +3.3 +0.6 +3.9 11.8
Kareem Abdul-Jabbar 1985 3,240 +2.5 +1.8 +4.4 11.8
Rashard Lewis 2008 3,493 +2.4 +1.4 +3.8 11.8
Eddie Jones 2005 3,440 +1.5 +2.4 +3.9 11.8
Hersey Hawkins 1996 3,536 +2.5 +1.2 +3.7 11.8
Paul Pressey 1985 3,172 +3.2 +1.3 +4.5 11.8
Alex English 1983 3,258 +4.6 -0.2 +4.3 11.7
Russell Westbrook 2011 3,485 +3.3 +0.6 +3.8 11.7
Kevin Garnett 2000 3,414 +2.3 +1.8 +4.0 11.7
Manu Ginobili 2006 2,239 +5.3 +2.1 +7.4 11.7
Larry Bird 1980 3,327 +2.2 +2.0 +4.1 11.7
Kevin Johnson 1992 3,234 +4.8 -0.5 +4.3 11.7
Kareem Abdul-Jabbar 1978 2,399 +3.4 +3.4 +6.9 11.7
Patrick Ewing 1990 3,560 +1.5 +2.2 +3.7 11.7
David Robinson 1999 2,154 +1.1 +6.7 +7.8 11.7
Marques Johnson 1983 3,235 +3.3 +1.0 +4.3 11.6
John Stockton 1998 2,454 +6.1 +0.4 +6.5 11.6
Gilbert Arenas 2005 3,724 +4.5 -1.2 +3.3 11.6
Jason Terry 2006 3,642 +4.0 -0.5 +3.5 11.6
Cedric Maxwell 1981 3,328 +3.7 +0.4 +4.1 11.6
Terry Porter 1988 3,140 +4.1 +0.4 +4.5 11.6
Russell Westbrook 2012 3,098 +4.4 +0.1 +4.5 11.6
Tayshaun Prince 2005 4,062 +1.6 +1.2 +2.8 11.6
George Gervin 1978 3,084 +4.3 +0.2 +4.6 11.6
Elton Brand 2002 3,020 +4.1 +0.8 +4.8 11.6
Mike Conley 2017 2,516 +5.5 +0.7 +6.2 11.6
Peja Stojakovic 2004 3,781 +4.3 -1.1 +3.3 11.6
Draymond Green 2018 3,106 +1.0 +3.3 +4.3 11.6
Danny Green 2015 2,516 +3.0 +3.2 +6.2 11.5
Doc Rivers 1989 2,653 +3.8 +2.0 +5.8 11.5
Dan Majerle 1992 3,119 +3.1 +1.4 +4.5 11.5
Fat Lever 1990 2,945 +3.2 +1.7 +4.9 11.5
Josh Smith 2010 3,263 +1.0 +3.2 +4.2 11.5
Isiah Thomas 1989 3,557 +2.4 +1.1 +3.5 11.5
Grant Hill 1996 3,375 +2.3 +1.6 +3.9 11.5
Paul Pierce 2003 3,541 +2.4 +1.2 +3.5 11.5
Charles Barkley 1996 2,796 +4.2 +1.1 +5.3 11.5
Boris Diaw 2006 3,670 +1.7 +1.7 +3.4 11.5
Allen Iverson 2003 4,042 +2.5 +0.3 +2.8 11.5
Dominique Wilkins 1988 3,421 +3.7 +0.1 +3.8 11.4
Danny Ainge 1988 3,688 +3.9 -0.5 +3.4 11.4
Vince Carter 2007 3,613 +3.9