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2025-26 regular season

Impact rating

How many points per 100 possessions a player adds to his team's margin, after accounting for the nine other players on the floor. Split into offense and defense.

135 players

Impact: points per 100 possessions better or worse than an average player, with 80% ranges. Rank is league wide among players with 250+ minutes.

#PlayerImpact-9.00+9.0ODMin
1Shai Gilgeous-AlexanderG · OKC+7.0+4.7+2.32,257
6Derrick WhiteG · BOS+5.2+1.5+3.72,621
7Dyson DanielsG · ATL+4.9+2.6+2.32,518
8Marcus SmartG · HOU+4.5+1.6+3.01,765
9Amen ThompsonG-F · HOU+4.3+2.1+2.32,953
12Alex CarusoG · OKC+4.3+1.0+3.31,020
14Donovan MitchellG · CLE+4.2+3.7+0.52,342
16Ausar ThompsonG-F · DET+4.1+1.6+2.51,894
18Devin VassellG-F · SAS+4.0+3.0+1.02,044
19Jimmy ButlerG-F · GSW+4.0+2.3+1.71,182
20Cade CunninghamG-F · DET+4.0+2.8+1.22,171
21Donte DiVincenzoG · MIN+3.9+1.7+2.22,494
22Ajay MitchellG · OKC+3.7+1.5+2.21,472
25Devin BookerG · PHX+3.3+1.3+2.02,144
26Jrue HolidayG · POR+3.3+0.7+2.61,557
27Jalen SuggsG · ORL+3.2+0.3+2.91,573
29Miles McBrideG · NYK+3.1+1.9+1.21,080
30Davion MitchellG · MIA+3.1+1.8+1.31,999
31Hugo GonzálezG · BOS+2.9+1.0+1.91,081
32Collin GillespieG · PHX+2.9+1.3+1.62,280
33CJ McCollumG · ATL+2.8+0.8+2.02,263
37Sam MerrillG · CLE+2.8+2.0+0.81,377
39Austin ReavesG · LAL+2.7+1.3+1.41,762
42Cedric CowardG · MEM+2.6+2.1+0.61,598
45Jamal SheadG · TOR+2.6+0.8+1.81,850
46Javonte GreenG-F · DET+2.5-0.1+2.61,443
47Scottie BarnesG-F · TOR+2.5+0.4+2.02,681
50Cason WallaceG · OKC+2.4-0.3+2.72,045
51LaMelo BallG · MIN+2.4+3.8-1.42,017
54De'Aaron FoxG · SAS+2.4+2.2+0.22,231
55Dylan HarperG · SAS+2.4+0.7+1.71,558
56Christian BraunG · DEN+2.4+1.3+1.11,399
58Nickeil Alexander-WalkerG · ATL+2.3+2.0+0.32,602
60Desmond BaneG · ORL+2.2+0.9+1.42,751
61De'Anthony MeltonG · GSW+2.2+1.4+0.81,121
66Moses MoodyG · GSW+2.1-0.5+2.51,536
67Stephen CurryG · GSW+2.1+3.2-1.11,329
74Kevin HuerterG · DET+1.8+1.0+0.81,549
75Coby WhiteG · CHA+1.8+2.0-0.21,250
76Peyton WatsonG · CLE+1.8+2.8-1.01,598
80Ryan RollinsG · MIL+1.7+1.2+0.52,374
83Isaiah JoeG · DET+1.7+0.6+1.01,506
84Kon KnueppelG-F · CHA+1.7+1.4+0.22,548
85Jose AlvaradoG · NYK+1.7-0.1+1.81,370
87Josh OkogieG · UTA+1.6+0.4+1.21,353
90Tyrese MaxeyG · PHI+1.6+0.4+1.22,661
94Jaime Jaquez Jr.G · MIL+1.5+1.0+0.52,115
96VJ EdgecombeG · PHI+1.5+0.9+0.62,623
101Tim Hardaway Jr.G · MIA+1.3+1.2+0.12,127
105Jordan GoodwinG · PHX+1.3+0.5+0.81,571
106Immanuel QuickleyG · TOR+1.3+0.8+0.52,231
109Jamal MurrayG · DEN+1.2+4.0-2.82,652
110Payton PritchardG · BOS+1.2+1.5-0.32,553
114Jalen BrunsonG · NYK+1.2+2.3-1.12,590
115Pelle LarssonG · MIA+1.2+0.8+0.41,848
116Landry ShametG · NYK+1.2-0.6+1.81,171
117Svi MykhailiukG · UTA+1.1+1.3-0.11,149
123Nique CliffordG · SAC+1.1+0.2+0.91,881
125Nah'Shon HylandG · MIN+1.1+0.3+0.81,177
131Ryan NembhardG · DEN+1.0+0.7+0.31,171
135Craig PorterG · CLE+0.9+0.8+0.11,148
138Kris DunnG · LAC+0.9+0.1+0.82,223
140Baylor ScheiermanG · BOS+0.80.0+0.81,428
144Stephon CastleG · SAS+0.8-0.3+1.12,038
153Luke KennardG · PHX+0.7+1.4-0.71,679
163Daniss JenkinsG · DET+0.6-0.6+1.11,453
168Gary Payton IIG · GSW+0.5+0.8-0.31,142
169Quentin GrimesG · LAL+0.5-0.9+1.42,206
170Sion JamesG · CHA+0.5-0.8+1.41,840
172Jaylon TysonG-F · CLE+0.5+0.4+0.21,778
175Josh HartG · NYK+0.5+0.2+0.31,993
176Tre JonesG · CHI+0.5+0.2+0.31,752
178Anthony BlackG · ORL+0.5+0.2+0.21,905
185Anthony EdwardsG · MIN+0.4+2.0-1.62,137
189Jared McCainG · OKC+0.40.0+0.31,159
196Jordan WalshG · BOS+0.3+1.2-0.81,211
198Gradey DickG · LAC+0.3-1.1+1.41,064
199A.J. GreenG · MIL+0.3+0.8-0.52,270
200Grayson AllenG · CHA+0.3+0.7-0.41,465
206Kevin Porter Jr.G · MIL+0.20.0+0.31,261
209Dillon BrooksG-F · PHX+0.2+0.5-0.31,701
210Aaron NesmithG-F · IND+0.2+0.4-0.21,333
216Kobe SandersG · LAC+0.1-0.4+0.61,347
220Jaylen BrownG · PHI+0.1+0.8-0.72,442
222Cam SpencerG · MEM+0.1+0.1-0.11,715
225James HardenG · CLE+0.1+2.0-2.02,438
228Jordan MillerG · LAC0.0+0.7-0.71,329
233Darius GarlandG · LAC0.0+1.0-1.01,344
249Egor DeminG · BKN-0.2-0.7+0.61,308
250Jordan ClarksonG · NYK-0.2-0.3+0.11,280
255Brandin PodziemskiG · GSW-0.2-1.6+1.42,333
261Sidy CissokoG · POR-0.3-1.3+1.01,432
269Josh GiddeyG · CHI-0.4+0.2-0.51,731
271Shaedon SharpeG · POR-0.4-0.6+0.21,465
277Kentavious Caldwell-PopeG · PHI-0.5-0.7+0.21,088
282Aaron WigginsG · ATL-0.5-0.9+0.41,414
284Luguentz DortG · ATL-0.5-0.3-0.21,848
288Reed SheppardG · HOU-0.6-0.1-0.42,147
289Terance MannG · BKN-0.6-0.3-0.31,529
290Pat SpencerG · PHX-0.6+0.3-0.91,225
291Dennis SchroderG · CHA-0.6-0.60.01,696
294Tyler HerroG · MIL-0.6+0.2-0.91,033
299John KoncharG-F · NYK-0.7-2.6+1.91,115
303Ayo DosunmuG · MIN-0.7-0.70.01,881
304Malik MonkG · SAC-0.8-0.1-0.71,363
305Bennedict MathurinG-F · NOP-0.8-0.80.01,620
308Tre JohnsonG · WAS-0.8-0.1-0.71,443
311Klay ThompsonG · MIA-0.9-2.1+1.21,497
317Russell WestbrookG · SAC-0.90.0-0.91,852
321Brandon WilliamsG · GSW-1.0+0.7-1.61,461
328Ja'Kobe WalterG · TOR-1.1-1.4+0.31,473
337Ziaire WilliamsG-F · LAL-1.1-2.7+1.61,281
339Dru SmithG · MIA-1.2-2.1+1.01,136
346Keyonte GeorgeG · UTA-1.2+1.7-2.91,780
350Vit KrejciG · POR-1.3-1.7+0.41,392
358Max ChristieG · DAL-1.4-1.1-0.32,244
367Caleb LoveG · PHI-1.6-0.9-0.71,013
369Will RichardG · GSW-1.6-0.9-0.71,377
371Zach LaVineG · SAC-1.6-0.9-0.71,224
373Ben SheppardG · IND-1.7-1.4-0.21,391
377Nolan TraoréG · BKN-1.7-0.3-1.41,243
380Anfernee SimonsG · PHI-1.8-0.4-1.41,368
384Bilal CoulibalyG · WAS-1.8-0.8-1.01,467
386Keon EllisG · BKN-1.8-1.7-0.11,479
399Collin SextonG · LAL-2.0-1.5-0.41,613
400Caris LeVertG · MIL-2.0-2.6+0.71,149
406Walter Clayton Jr.G · MEM-2.0+0.4-2.41,411
413Andrew NembhardG-F · IND-2.1-0.5-1.61,786
419DeMar DeRozanG · DEN-2.3+0.6-2.92,405
424Jeremiah FearsG · NOP-2.6-0.9-1.62,112
426Bruce BrownG · NYK-2.6-2.3-0.31,998
446Isaiah CollierG · UTA-4.8-1.5-3.21,517
447Gary Trent Jr.G · MIL-4.8-2.3-2.51,376
448Carlton CarringtonG · WAS-5.0-1.9-3.12,270
450Rayan RupertG-F · PHI-5.1-3.6-1.51,070

Bars show the 80% range on a scale from -9.0 to +9.0. The tick is the rating. A range that crosses 0 means we cannot tell the player apart from average yet.

How this works

The method

Every game is cut into stints: stretches where the same ten players are on the floor. For each stint we count the points each side scored per 100 possessions. One regression then asks: which players, when they are on the floor, go with more points for their team and fewer for the other team, after accounting for everyone else out there? That is the offense (O) and defense (D) number; Impact is the sum.

With about 500 players and a lot of noise, the plain answer overreacts, so every player is pulled toward average (a ridge regression). How hard to pull is picked by testing on games the model did not see: we split games into 5 groups, fit on 4 and score the fifth. Longer stints count more because they have more possessions.

The range comes from refitting the model 50 times on reshuffled sets of games. 8 in 10 of those fits land inside the bar.

What we measured

Data
36,423 stints from 1,230 games, 582 players (450 with 250+ minutes)
Pull toward average
Strength 3,000, the best of 10 tried
Test error
63.3 points per 100 on unseen games, against 63.5 for guessing league average (112.3) every stint: 0.32% better. Single stints are short and mostly luck, so the gain is small even when the player signal is real.
Typical range width
3.2 points for the middle player
Matches on/off
Correlation 0.81 with raw on/off net rating (450 players)
Matches Courtside score
Correlation 0.47 with the box score based Courtside score (352 players)
Fitted
2026-09-27 · rapm-v1

What it cannot see

  • One season is noisy. Two players a point apart are usually not different; read the ranges, not the ranks.
  • It uses no box score at all: no points, rebounds or steals. A player gets credit only for what the scoreboard did while he played, so bench players who share the floor with the same teammates are hard to separate.
  • It does not know about role, matchups, garbage time or injuries, and players with few minutes stay close to 0 by design.
  • Players under 250 minutes are stored but shown as "not enough minutes".