Who is predicted to win the 2026-27 NBA MVP?

Nikola Jokić of the DEN leads at 44.3% across 10,000 simulated seasons, ahead of Victor Wembanyama at 20.4%.

What would change the MVP prediction?

The forecast docks a player carrying two straight MVPs, because bids for a third have gone badly. Switch that penalty off and Shai Gilgeous-Alexander leads instead. How hard to dock him is the open question: the record points to about 0.836, but with so few third-straight runs to learn from, anything from 1.965 down to no penalty at all fits it. The favourite only changes below 0.4.

What do NBA MVP voters reward most?

Player efficiency rating: the median MVP sits at the 100th percentile of his own season's candidates. Value over replacement: the median MVP sits at the 99th percentile of his own season's candidates. Box plus/minus: the median MVP sits at the 99th percentile of his own season's candidates.

MVP forecast · Act 1 of 12

83 candidates.
Not one game played

10,000

Each simulated season deals every candidate a real historical projection error — whole vectors of it, so a player who beats his scoring projection also beats his efficiency projection, the way it actually happens — and then re-ranks the field.

MVP forecast · Act 2 of 12

Nikola Jokić · DEN

44.3%

The model's MVP is Nikola Jokić

He finishes top five in 89.7% of simulated seasons. Hold that thought — all of it rests on one assumption.

Top-five finish

89.7%

Stays eligible

94.4%

Mean finish

6.48

Candidates

MVP forecast · Act 3 of 12

Four players hold 99.4% of it between them

Nikola JokićDEN44.3%

Victor WembanyamaSAS20.4%

Shai Gilgeous-AlexanderOKC15.5%

Luka DončićLAL9.3%

Everyone below them is competing for the remainder. Twenty names cover 99.4% of the probability; the other 63 split what is left.

MVP forecast · Act 4 of 12

One assumption changes the answer

A player carrying two straight MVPs gets docked some of his score, because bids for a third have gone badly. Nobody knows how much to dock him — so move the slider and watch the field rearrange itself.

How hard to dock a two-time winner · 0.75 deployed

Snaps to the 12 penalties the pipeline actually simulated — nothing between them is invented.

Nikola Jokić44.3%

Victor Wembanyama20.4%

Shai Gilgeous-Alexander15.5%

Luka Dončić9.3%

Cade Cunningham3.2%

The answer flips at 0.4 — dock him less than that and Shai Gilgeous-Alexander wins it, dock him that or more and Nikola Jokić does.

MVP forecast · Act 5 of 12

81%

of the realistic penalties still point to Nikola Jokić

So how hard should a back-to-back winner be docked? The record says about 0.84 — but with so few third-straight runs to learn from, anything from a brutal 1.97 down to no penalty at all fits it just as well.

0.75

The dock this forecast uses

Enough to take Shai Gilgeous-Alexander from 49% down to 15%. It is where the slider on the last screen is sitting.

0.84

What the record suggests

Measured from every player who went into a season chasing a third straight MVP since 2000-01. A shade harsher than the dock above.

0 – 1.97

How sure of it we are: not very

There have been too few three-peat runs to pin the number down. Everything in this range fits the history equally well — including no penalty whatsoever.

0.40

Where the answer changes

Dock him any less than this and Shai Gilgeous-Alexander takes over. Most of the range above sits on the other side of it.

MVP forecast · Act 6 of 12

It is a shift, not a ceiling

Three-peat bids have gone nought for seven since 1999-2000, against a 40% repeat rate for one-peat defenders. That is what the penalty encodes. It is not a rule that a third straight MVP cannot happen — Russell, Chamberlain and Bird each won one. A big enough simulated season still wins.

Which is the honest way to hold any of this: the model assumes voters keep rewarding what they have rewarded since 2000, and it knows nothing about who gets traded in February.

MVP forecast · Act 7 of 12

Where the two routes disagree

One projects each player's stat line first and is aware of this season's rosters; the other projects nothing and assumes last season's. They fail differently, so where they agree the call is robust — and where they disagree, the disagreement is the finding.

Roster-aware

1Victor WembanyamaSAS3.71
2Nikola JokićDEN3.45
3Shai Gilgeous-AlexanderOKC3.4
4Luka DončićLAL3
5Kawhi LeonardTOR1.8
6Cade CunninghamDET1.64

Last season's rosters

1Victor WembanyamaSAS3.19
2Nikola JokićDEN3.11
3Luka DončićLAL2.67
4Shai Gilgeous-AlexanderOKC2.64
5Cade CunninghamDET1.42
6Donovan MitchellCLE1.3

MVP forecast · Act 8 of 12

The median MVP led his field in efficiency

These are the stats the model says voters reward. Here is where past winners actually landed in them, ranked against the candidate pool of their own season.

StatMedian MVPPool medianWhere the MVP ranked among that season's candidates

Player efficiency rating 30.516.6100th

Value over replacement 7.82.499.1th

Box plus/minus +9.4+1.999.1th

Points per game 27.415.697.7th

Team wins 59.542.097.6th

Usage rate 31%22%96.8th

Offensive rating 114.0107.495th

True shooting 61.6%55.3%92.7th

Assists per game 6.73.190.7th

Defensive rating lower is better102.5106.184.5th

32.8

Nikola Jokić

PER · 2021-22

11.2

Stephen Curry

VORP · 2015-16

33.1

Joel Embiid

Points per game · 2022-23

96.4

Tim Duncan

Defensive rating · 2002-03

MVP forecast · Act 9 of 12

Injury risk is priced in, not assumed away

A player who does not clear the games threshold in a simulated season is not eligible in it. So availability is part of the forecast rather than a caveat underneath it.

Nikola JokićDEN94.4%

Victor WembanyamaSAS85.9%

Shai Gilgeous-AlexanderOKC95.9%

Luka DončićLAL91.2%

MVP forecast · Act 10 of 12

A preseason MVP pick is a weak instrument

Last season's rosters

41%picked first

82%in its top five

3.59mean rank

Worst miss: Derrick Rose at 17th (2010-11)

Roster-aware

41%picked first

71%in its top five

4mean rank

Worst miss: Derrick Rose at 20th (2010-11)

Both routes are scored on the same 17 seasons. A preseason forecast cannot pick a player who was not already a candidate last season, and it knows nothing about who gets hurt.

MVP forecast · Act 11 of 12

How it turned out

Sealed until the votes are counted

This forecast says Nikola Jokić at 44.3%. Come back after June 2027 and this screen will say who actually won it, and where the model had him.

MVP forecast · Act 12 of 12

Every candidate, every number

All 83 MVP candidates with win probability, the same probability without the voter-fatigue penalty, top-five probability, eligibility rate and mean finish.
#	Player	Team	MVP	No penalty	Top 5	Eligible	Mean finish
1	Nikola Jokić	DEN	44.29%	26.29%	89.7%	94%	6.48
2	Victor Wembanyama	SAS	20.42%	13.23%	70.3%	86%	14.3
3	Shai Gilgeous-Alexander	OKC	15.47%	49.06%	80.0%	96%	6.81
4	Luka Dončić	LAL	9.33%	5.49%	62.6%	91%	11.58
5	Cade Cunningham	DET	3.24%	1.86%	27.2%	88%	19.2
6	Kawhi Leonard	TOR	1.75%	1.08%	20.4%	89%	17.51
7	Jalen Duren	DET	0.81%	0.41%	12.5%	83%	25.78
8	Donovan Mitchell	CLE	0.79%	0.44%	14.3%	90%	19.13
9	Jalen Brunson	NYK	0.48%	0.27%	11.7%	96%	17.18
10	Anthony Edwards	MIN	0.42%	0.23%	9.0%	95%	17.73
11	Chet Holmgren	OKC	0.40%	0.21%	14.4%	89%	24.77
12	Alperen Sengun	HOU	0.40%	0.23%	5.5%	95%	23.32
13	Tyrese Maxey	PHI	0.34%	0.20%	10.2%	94%	19.65
14	Kevin Durant	HOU	0.28%	0.18%	8.2%	98%	17.68
15	Karl-Anthony Towns	NYK	0.26%	0.15%	5.4%	94%	25.84
16	James Harden	CLE	0.23%	0.14%	6.9%	97%	18.71
17	Jaylen Brown	PHI	0.15%	0.07%	2.3%	93%	24.6
18	Scottie Barnes	TOR	0.14%	0.06%	3.2%	94%	29.11
19	Devin Booker	PHX	0.12%	0.08%	3.9%	93%	23.15
20	LaMelo Ball	MIN	0.11%	0.04%	2.9%	88%	29.94
21	Evan Mobley	CLE	0.11%	0.06%	4.2%	91%	25.25
22	Kon Knueppel	CHA	0.11%	0.05%	4.3%	98%	24.66
23	LeBron James	PHI	0.10%	0.05%	5.0%	85%	27.31
24	Jalen Johnson	ATL	0.09%	0.06%	2.0%	89%	33.61
25	Jamal Murray	DEN	0.06%	0.01%	6.5%	92%	25.08
26	Stephon Castle	SAS	0.03%	0.01%	3.6%	89%	35.84
27	Amen Thompson	HOU	0.03%	0.02%	4.0%	97%	25.69
28	Zion Williamson	NOP	0.03%	0.01%	0.9%	85%	33.28
29	Cooper Flagg	DAL	0.01%	0.01%	3.8%	89%	27.54
30	Josh Hart	NYK	0.00%	0.00%	0.0%	97%	55.97
31	Dillon Brooks	PHX	0.00%	0.00%	0.0%	80%	65.09
32	Mikal Bridges	NYK	0.00%	0.00%	0.0%	100%	54.39
33	Miles Bridges	PHX	0.00%	0.00%	0.0%	94%	52.89
34	De'Aaron Fox	SAS	0.00%	0.00%	2.5%	92%	31.74
35	Wendell Carter Jr.	ORL	0.00%	0.00%	0.0%	87%	61.09
36	Donte DiVincenzo	MIN	0.00%	0.00%	0.0%	81%	60.78
37	Pascal Siakam	IND	0.00%	0.00%	0.1%	94%	29.88
38	P.J. Washington	DAL	0.00%	0.00%	0.0%	78%	67.49
39	Rui Hachimura	LAC	0.00%	0.00%	0.0%	73%	67.45
40	Andrew Nembhard	IND	0.00%	0.00%	0.0%	77%	65.97
41	RJ Barrett	TOR	0.00%	0.00%	0.0%	72%	55.28
42	Desmond Bane	ORL	0.00%	0.00%	0.0%	97%	46.81
43	Nickeil Alexander-Walker	ATL	0.00%	0.00%	0.2%	98%	43.12
44	Brandon Ingram	LAC	0.00%	0.00%	0.0%	95%	46.66
45	Royce O'Neale	CHA	0.00%	0.00%	0.0%	68%	67.84
46	Norman Powell	CHI	0.00%	0.00%	0.0%	68%	56.34
47	Deni Avdija	POR	0.00%	0.00%	0.1%	93%	43.01
48	Onyeka Okongwu	ATL	0.00%	0.00%	0.0%	95%	49.77
49	Devin Vassell	SAS	0.00%	0.00%	0.1%	89%	57.92
50	Andrew Wiggins	MIA	0.00%	0.00%	0.0%	74%	60.85
51	Saddiq Bey	NOP	0.00%	0.00%	0.0%	91%	64.19
52	Jaden McDaniels	MIN	0.00%	0.00%	0.0%	94%	62.15
53	Immanuel Quickley	TOR	0.00%	0.00%	0.0%	90%	53.6
54	Payton Pritchard	BOS	0.00%	0.00%	0.2%	91%	47.78
55	Derrick White	BOS	0.00%	0.00%	0.4%	97%	42.58
56	Ryan Rollins	MIL	0.00%	0.00%	0.1%	95%	43.07
57	Bam Adebayo	MIA	0.00%	0.00%	0.1%	97%	40.93
58	OG Anunoby	NYK	0.00%	0.00%	0.1%	96%	52.8
59	Dyson Daniels	ATL	0.00%	0.00%	0.1%	98%	40.82
60	CJ McCollum	ATL	0.00%	0.00%	0.0%	84%	49.33
61	Jabari Smith Jr.	HOU	0.00%	0.00%	0.0%	94%	58.05
62	Paolo Banchero	ORL	0.00%	0.00%	0.0%	98%	38.79
63	Jerami Grant	MEM	0.00%	0.00%	0.0%	67%	58.61
64	Rudy Gobert	MIN	0.00%	0.00%	0.0%	95%	31.54
65	Max Christie	DAL	0.00%	0.00%	0.0%	90%	62.58
66	Marcus Smart	HOU	0.00%	0.00%	0.0%	63%	62.1
67	Julius Randle	BKN	0.00%	0.00%	0.5%	95%	29.28
68	Davion Mitchell	MIA	0.00%	0.00%	0.0%	80%	63.35
69	Nikola Vučević	ORL	0.00%	0.00%	0.0%	82%	47.2
70	Jaime Jaquez Jr.	MIL	0.00%	0.00%	0.0%	74%	62.14
71	Naji Marshall	DAL	0.00%	0.00%	0.0%	84%	64.9
72	Herbert Jones	NOP	0.00%	0.00%	0.0%	75%	67.24
73	Collin Gillespie	PHX	0.00%	0.00%	0.0%	81%	56.24
74	AJ Green	MIL	0.00%	0.00%	0.0%	87%	60.79
75	DeMar DeRozan	DEN	0.00%	0.00%	0.1%	99%	27.85
76	Brandon Miller	CHA	0.00%	0.00%	0.1%	90%	44.63
77	Anthony Black	ORL	0.00%	0.00%	0.0%	86%	51.47
78	Toumani Camara	POR	0.00%	0.00%	0.0%	98%	56.75
79	Brandin Podziemski	GSW	0.00%	0.00%	0.0%	91%	50.07
80	Matas Buzelis	CHI	0.00%	0.00%	0.0%	94%	50.03
81	VJ Edgecombe	PHI	0.00%	0.00%	0.1%	97%	42.63
82	Trey Murphy III	NOP	0.00%	0.00%	0.0%	83%	50.91
83	Quentin Grimes	LAL	0.00%	0.00%	0.0%	89%	60.52