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 performance⁶ 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 played⁷ 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 season⁸ 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.)⁹

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.¹⁰ 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.¹¹ 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

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.¹² 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,¹³ 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,¹⁴ 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

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.¹⁵ 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 contribute¹⁶ to a teammate’s opportunity to score — are associated with lower offensive RAPMs and are therefore punished by RAPTOR.¹⁷ 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/penalty¹⁸ 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 faced¹⁹ (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.²⁰ 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.²¹ 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.²²

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.²³

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 really²⁴ 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.²⁵

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 ratings²⁶ 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.²⁷
3. Finally, the player’s courtmates’ other courtmates’ weighted average offensive and defensive ratings.²⁸ 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

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.²⁹ 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

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.³⁰

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.³¹

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 same³² 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 season³³ 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.³⁴
• 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 weighted³⁵ 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.³⁶

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	-0.4	+3.4	11.4
Maurice Cheeks	1980	3,298	+2.1	+1.9	+4.0	11.4
Jason Kidd	2011	3,397	+2.0	+1.8	+3.8	11.4
Tim Duncan	2010	2,811	+1.4	+3.9	+5.3	11.4
Rudy Gobert	2019	2,729	+0.7	+4.7	+5.4	11.4
Marques Johnson	1979	2,779	+4.4	+0.9	+5.3	11.4
James Worthy	1987	3,500	+2.4	+1.2	+3.6	11.3
Sidney Moncrief	1985	3,053	+3.7	+0.8	+4.5	11.3
Alvin Robertson	1988	3,097	+2.5	+1.9	+4.4	11.3
Julius Erving	1984	2,877	+2.8	+2.1	+4.9	11.3
Jason Terry	2007	3,075	+4.7	-0.2	+4.5	11.3
Marques Johnson	1980	2,989	+3.8	+0.9	+4.7	11.3
Kyrie Irving	2015	3,194	+5.3	-1.2	+4.1	11.3
Ben Wallace	2005	3,650	-1.3	+4.6	+3.3	11.3
Reggie Miller	1997	2,966	+5.1	-0.4	+4.7	11.3
Kyle Lowry	2017	2,544	+6.3	-0.4	+5.9	11.3

Although LeBron James’s 2008-09 is the top season on a rate basis, when he had an Approximate RAPTOR rating of +12.6 per 100 possessions, it’s Michael Jordan who dominates the list by WAR, both because he got a ton of playing time and because he did all the things that RAPTOR loves: create shots, play defense and so forth. In fact, working on RAPTOR has convinced me that Jordan’s peak was probably a little higher than LeBron’s, something I didn’t necessarily believe before. We’ll save that discussion for another time, though, as well as the conversation about how RAPTOR feels about players such as John Stockton (loves) and Patrick Ewing (hates). For more detail on Approximate RAPTORS, you can find a files here that lists each player’s rating in the regular season and playoffs separately, or a version that combines a player’s performance over the whole season.

Acknowledgements: Thanks to Ryan Davis, Steve Ilardi, Ben Taylor, Seth Partnow, Charles Rolph and Evan Wasch for their advice and assistance on RAPTOR.