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Last updated Jul 14, 2026
The Hussey Board · 2025–26 · Regular season only
2025–26 NBA Player Rankings
The Board ranks per-minute impact. It starts with each player's individual production, then checks how his lineups actually performed.
The answer first
Top 25
“Why this rank” shows whether individual statistics or the results of the player's lineups changed the answer. Teammates and opponents are accounted for in the lineup step.
#1Nikola JokićDEN · C · 65 games · 2,265 minutesHis box-score stats looked like those of a top-10 player (#1), powered by high-volume, efficient scoring despite costly turnovers.100.0likely #1–#17100thpercentile#2Shai Gilgeous-AlexanderOKC · PG · 68 games · 2,259 minutesHis box-score stats looked like those of a top-10 player (#3), powered by high-volume, efficient scoring.99.6likely #1–#44100thpercentile#3Kawhi LeonardLAC · SF · 65 games · 2,085 minutesHis box-score stats looked like those of a top-10 player (#6), powered by high-volume, efficient scoring.98.6likely #2–#8799thpercentile#4Giannis AntetokounmpoMIL · PF · 36 games · 1,039 minutesHis box-score stats looked like those of a top-10 player (#2), powered by high-volume, efficient scoring despite costly turnovers.98.3likely #3–#5296thpercentile#5Victor WembanyamaSAS · C · 64 games · 1,866 minutesHis box-score stats looked like those of a top-10 player (#4), powered by rebounding and shot blocking.98.2likely #2–#7399thpercentile#6Luka DončićLAL · PG · 64 games · 2,289 minutesHis box-score stats looked like those of a top-10 player (#5), powered by high-volume, efficient scoring.98.2likely #2–#11199thpercentile#7Stephen CurryGSW · PG · 43 games · 1,329 minutesHis box-score stats still looked like those of a top-10 player (#7), powered by high-volume, efficient scoring.97.8likely #4–#15594thpercentile#8Jimmy ButlerGSW · SF · 38 games · 1,182 minutesHis box-score stats still looked like those of a top-10 player (#8), powered by high-volume, efficient scoring.97.5likely #4–#16192ndpercentile#9Donovan MitchellCLE · SG · 70 games · 2,342 minutesHis box-score stats looked like those of a top-20 player (#11), powered by high-volume, efficient scoring.97.1likely #5–#17998thpercentile#10Tyrese MaxeyPHI · PG · 70 games · 2,661 minutesHis box-score stats looked like those of a top-10 player (#10), powered by high-volume, efficient scoring.96.8likely #6–#20299thpercentile#11Cade CunninghamDET · PG · 64 games · 2,172 minutesHis box-score stats looked like those of a top-20 player (#13), powered by rebounding and shot blocking.96.4likely #6–#20098thpercentile#12Joel EmbiidPHI · C · 38 games · 1,201 minutesHis box-score stats looked like those of a top-10 player (#9), powered by elite passing. Weak on-court lineup results pulled him from #9 to #12.96.0likely #6–#19989thpercentile#13Jayson TatumBOS · PF · 16 games · 522 minutesHis box-score stats looked like those of a top-40 player (#26), powered by elite passing despite below-average scoring efficiency. Strong on-court lineup results lifted him from #26 to #15.95.1likely #8–#23168thpercentile#14Jamal MurrayDEN · PG · 75 games · 2,652 minutesHis box-score stats looked like those of a top-25 player (#24), powered by high-volume, efficient scoring. Strong on-court lineup results lifted him from #24 to #16.95.0likely #8–#23098thpercentile#15Lauri MarkkanenUTA · PF · 42 games · 1,443 minutesHis box-score stats looked like those of a top-40 player (#30), powered by elite ball security. Strong on-court lineup results lifted him from #30 to #17.94.6likely #8–#23190thpercentile#16Chet HolmgrenOKC · PF · 69 games · 1,997 minutesHis box-score stats looked like those of a top-50 player (#49), powered by rebounding and shot blocking. Strong on-court lineup results lifted him from #49 to #14.94.5likely #10–#22295thpercentile#17Kevin DurantHOU · SF · 78 games · 2,840 minutesHis box-score stats still looked like those of a top-20 player (#17), powered by high-volume, efficient scoring despite costly turnovers.94.2likely #9–#23198thpercentile#18LaMelo BallCHO · PG · 72 games · 2,017 minutesHis box-score stats looked like those of a top-40 player (#27), powered by elite passing. Strong on-court lineup results lifted him from #27 to #13. A smaller role then lowered his final rank to #18.94.1likely #11–#22495thpercentile#19Derrick WhiteBOS · SG · 77 games · 2,625 minutesHis box-score stats looked like those of a top-75 player (#65), powered by elite shot blocking despite below-average scoring efficiency. Strong on-court lineup results lifted him from #65 to #19.93.9likely #9–#23997thpercentile#20Alperen ŞengünHOU · C · 72 games · 2,398 minutesHis box-score stats looked like those of a top-25 player (#25), powered by elite passing despite below-average scoring efficiency. Strong on-court lineup results lifted him from #25 to #21.93.2likely #9–#24196thpercentile#21Michael Porter Jr.BRK · SF · 52 games · 1,689 minutesHis box-score stats looked like those of a top-20 player (#15), powered by elite rebounding. Weak on-court lineup results pulled him from #15 to #22.92.8likely #10–#23891stpercentile#22Scottie BarnesTOR · PF · 80 games · 2,681 minutesHis box-score stats looked like those of a top-20 player (#19), powered by elite passing despite costly turnovers. Weak on-court lineup results pulled him from #19 to #24.92.1likely #10–#24597thpercentile#23Karl-Anthony TownsNYK · C · 75 games · 2,322 minutesHis box-score stats looked like those of a top-75 player (#53), powered by elite rebounding. Strong on-court lineup results lifted him from #53 to #25.91.7likely #10–#24996thpercentile#24Collin GillespiePHO · PG · 80 games · 2,282 minutesHis box-score stats looked like those of a top-75 player (#51), powered by strong rebounding. Strong on-court lineup results lifted him from #51 to #23.91.3likely #12–#24796thpercentile#25Anthony EdwardsMIN · SG · 61 games · 2,137 minutesHis box-score stats looked like those of a top-25 player (#21), powered by high-volume, efficient scoring. Weak on-court lineup results pulled him from #21 to #28.91.0likely #10–#24795thpercentile
View all 395 ranked players →How to read it
Impact per minute, value across the season
Impact Rate answers who played best while on the court. Season Value adds workload; the percentile shows how a player's total regular-season contribution compares with everyone on this Board.
The likely-rank range shows model uncertainty. A wider range means the exact order is less certain, even when the central estimate is high.
Read how the rankings work →