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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.

70 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
2Victor WembanyamaF-C · SAS+6.5+2.2+4.31,866
3Kawhi LeonardF · TOR+6.2+4.2+2.02,079
10OG AnunobyF · NYK+4.3+2.5+1.82,224
13Julian ChampagnieF · SAS+4.3+2.8+1.52,266
24Moussa DiabateF · CHA+3.3+2.4+0.91,899
35RJ BarrettF-G · TOR+2.8+3.5-0.71,726
38Oso IghodaroF · PHX+2.7+1.3+1.41,806
40Cameron JohnsonF · DEN+2.7+2.4+0.31,647
48Luka DoncicF-G · LAL+2.4+2.8-0.32,289
52Evan MobleyF-C · CLE+2.4+0.8+1.62,074
57Brandon MillerF · CHA+2.4+0.4+1.91,968
64Duncan RobinsonF · DET+2.1+2.4-0.32,113
69Herbert JonesF · NOP+2.0+0.5+1.51,587
78Kevin DurantF · HOU+1.8+1.5+0.32,839
79Sam HauserF · BOS+1.8+1.9-0.11,931
88Sandro MamukelashviliF · LAL+1.6+1.1+0.51,747
89Pascal SiakamF · IND+1.6+1.9-0.32,055
91Julius RandleF · BKN+1.6+2.4-0.82,610
95Mikal BridgesF · NYK+1.5+0.8+0.72,692
100Jabari Smith Jr.F · HOU+1.3+0.4+0.92,704
102Tobias HarrisF · SAS+1.3+0.3+1.01,741
111Tari EasonF · HOU+1.2+0.5+0.71,549
118Keldon JohnsonF · SAS+1.1-0.1+1.31,912
120Naz ReidF-C · CHA+1.1-0.7+1.82,007
122Wendell Carter Jr.F · ORL+1.1-0.2+1.32,283
124Michael Porter Jr.F · BKN+1.1+1.9-0.81,688
128Precious AchiuwaF · SAC+1.0+0.6+0.51,745
143Toumani CamaraF · POR+0.80.0+0.82,722
145Tristan Da SilvaF · ORL+0.8-0.2+1.01,894
147LeBron JamesF · PHI+0.8-0.2+1.01,982
150Jaden McDanielsF · MIN+0.7+0.6+0.22,316
165Zion WilliamsonF · NOP+0.6+0.60.01,840
167Dominick BarlowF · PHI+0.5-0.5+1.01,689
173Jalen JohnsonF · ATL+0.50.0+0.52,530
174Deni AvdijaF · POR+0.5+2.1-1.62,193
183Saddiq BeyF · NOP+0.4+0.7-0.32,245
184Trey Murphy IIIF · NOP+0.4+0.8-0.42,340
190Harrison BarnesF · SAS+0.3+0.8-0.51,986
195Cooper FlaggF · DAL+0.3-0.1+0.42,342
201Rui HachimuraF · LAC+0.3+0.3-0.11,923
215Naji MarshallF · DAL+0.1-0.2+0.42,182
223Jerami GrantF · MEM+0.1+1.6-1.51,695
231Ronald Holland IIF · DET0.0-2.3+2.31,548
247Kelly Oubre Jr.F · IND-0.1+1.1-1.21,574
259Jay HuffF-C · IND-0.2-1.6+1.41,719
265Norman PowellF-G · CHI-0.3-0.2-0.11,713
267Onyeka OkongwuF-C · ATL-0.4-0.8+0.52,297
268Paolo BancheroF · ORL-0.4+0.3-0.62,497
281Miles BridgesF · PHX-0.5+0.3-0.82,386
297Noah ClowneyF · BKN-0.7+0.1-0.81,780
306Matas BuzelisF · CHI-0.8-0.5-0.22,248
323John CollinsF-C · DET-1.0-1.3+0.31,872
330Jaylen WellsF · MEM-1.1+0.3-1.41,821
331Jake LaRaviaF · LAL-1.1+0.7-1.82,058
332Bobby PortisF · MIA-1.1-0.3-0.81,618
338Alperen SengunF-C · HOU-1.2+0.7-1.82,397
345P.J. WashingtonF · DAL-1.2-1.8+0.61,736
349Brandon IngramF · LAC-1.3-0.2-1.02,600
353Kyle KuzmaF · MIL-1.3-0.5-0.81,806
362Andrew WigginsF-G · MIA-1.5-0.8-0.72,062
364Brice SensabaughF · UTA-1.5+0.3-1.91,756
383Zaccharie RisacherF · DAL-1.8-1.5-0.31,503
391Isaac OkoroF-G · CHI-1.9+0.3-2.11,695
401Draymond GreenF · GSW-2.0-1.6-0.31,865
435Cody WilliamsF · MIN-3.0-0.7-2.31,631
436Airious BaileyF · UTA-3.0-1.4-1.61,988
438Royce O'NealeF · CHA-3.1-1.4-1.82,210
440Nicolas ClaxtonF-C · CHI-3.4-2.0-1.41,920
442Jarace WalkerF · IND-3.9-2.4-1.51,952
443Will RileyF · WAS-4.0-1.3-2.61,633

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".