2026 Finals MVP

The New York Knicks won the 2026 NBA Finals 4–1. Our Game Score model's final Finals MVP ranking:

Series final · NYK win 4–1 · 5 games played

New York Knicks — 2026 NBA Champions

Defeated the San Antonio Spurs 4–1 in the Finals

NYK

New York Knicks

🏆 Champions

4 — 1

NYK wins series 4-1

SAS

San Antonio Spurs

Model MVP pick

Jalen Brunson

NYK · 32.6 PPG

Players tracked

across both rosters

Series result

NYK 4–1

5 games played

MVP Rankings

Our Model — Game Score (Hollinger) weighted by series win probability.

#	Player	Our Model	Kalshi Market	PPG	RPG	APG	FG%	GmSc
1	Jalen Brunson NYK	10.3%	—	32.6	4.2	4.6	42.1%	11.0 11.6 17.3 28.5 32.9
2	OG Anunoby NYK	9.5%	—	21.2	4.8	1.0	52.5%	13.2 17.1 23.5 28.7 6.8
3	Karl-Anthony Towns NYK	7.7%	—	13.0	10.6	2.4	49.0%	15.4 21.4 11.3 11.7 -2.1
4	Josh Hart NYK	7.1%	—	7.6	9.8	4.6	38.2%	12.5 -0.5 15.2 9.4 10.2
5	Mikal Bridges NYK	7.0%	—	10.4	3.6	3.4	46.5%	9.2 19.3 -0.1 3.9 12.3
6	Landry Shamet NYK	5.7%	—	6.8	2.0	1.0	33.3%	7.4 9.3 -0.1 -1.2 0.4
7	Mitchell Robinson NYK	5.6%	—	3.6	5.6	0.6	50.0%	2.4 6.0 6.1 0.7 6.6
8	Jose Alvarado NYK	5.4%	—	4.2	2.6	1.4	33.3%	4.7 1.5 2.5 6.1 -3.6
9	Miles McBride NYK	5.2%	—	2.2	0.6	1.4	18.2%	5.3 1.3 -2.4 -2.8 -1.1
10	Devin Vassell SAS	5.2%	—	12.8	6.8	2.8	53.7%	7.9 15.4 8.0 18.0 14.2
11	Julian Champagnie SAS	5.2%	—	11.0	5.4	1.8	40.9%	14.7 6.4 9.9 6.7 9.1
12	Victor Wembanyama SAS	5.2%	—	26.0	11.2	2.6	42.3%	15.8 22.8 32.3 17.2 16.4
13	Stephon Castle SAS	5.2%	—	14.6	5.4	4.2	37.7%	11.1 4.8 19.5 9.7 -0.3
14	De'Aaron Fox SAS	5.2%	—	12.8	3.0	6.0	34.3%	-0.6 16.1 9.5 13.9 1.4
15	Dylan Harper SAS	5.2%	—	18.0	6.4	3.0	49.3%	13.7 10.7 7.9 14.9 18.3

Methodology

Game Score is John Hollinger's single-number box-score metric: PTS + 0.4×FGM − 0.7×FGA − 0.4×(FTA−FTM) + 0.7×OREB + 0.3×DREB + STL + 0.7×AST + 0.7×BLK − 0.4×PF − TOV. Higher is better; a typical starter averages 10–15, and a dominant Finals performance scores 25+.

Series win probability is the key multiplier. The Finals MVP almost always comes from the winning team (the only exception in NBA history: Jerry West, 1969). So a player averaging 25 Game Score on a team trailing 0–2 has a much lower MVP probability than a player averaging 20 on the team leading 2–0. As the series shifts, so do these rankings.

Usage factor scales by playing time (min 1.0, avg_minutes / 30). Role players who happen to have one efficient stretch don't leapfrog 35-minute starters.

Rankings are converted to probabilities via softmax — the same approach used in our championship odds model.

Not betting advice. See Responsible Gambling if you or someone you know has a problem.

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