The race, week by week

NFL MVP and Awards Tracker

Award forecasts alongside on-field performance. Follow the leaders, see what drives their rankings, and revisit each weekly snapshot.

Updates after completed weekly games

Last updated:

Coach of the Year

2026 season · Through week 3

Choose a historical snapshot

2026 · W5 2026 · W4 2026 · W3 2026 · W2 2026 · W1 2026 · W0

Forecast leader

Klint Kubliak

LV · HC

Historical top-three hit rate

33%

6 retrospective validation seasons at this horizon

Forecast status

Experimental

Win percentages withheld pending validation

Race trajectory

Predicted rank by weekly snapshot for the current top 8. Each point is what the board said after that week, not a recomputation; weeks ranked below 25 run off the bottom.

Weekly leaders

Week 1

Klint Kubliak

Week 2

Klint Kubliak

Week 3

Klint Kubliak

Methodology and validation

Each award has a separate regularized model trained on earlier seasons only. Candidates come from statistics available at the selected cutoff. Missing winners count as misses. The model predicts award winners; it does not estimate ballot share.

Remaining-season player totals shrink toward prior-season rates with a four-game prior. Team records use a beta prior. Coach forecasts compare projected wins with a preseason baseline formed from the prior season record. These projections assume continued availability and do not yet model future injury risk. Full-game production informs the award forecast; competitive-drive EPA is a separate performance measure. Awards do not change team ratings.

Historical results use reconstructed source files and a 24-hour result-availability assumption. Previously inspected years are retrospective validation, not a fresh holdout. CPOY training excludes seasons before the 2024 criteria change.

Winner hit rate: 17%. Winner coverage: 100%. Log loss: 3.19. Brier score: 0.95.

Precise probabilities require at least eight validation seasons, complete winner coverage, better log loss than a uniform baseline, and a leader-confidence gap of at most ten percentage points. Until then, rankings remain experimental.

Sources: nflverse player and schedule data, NFL Record and Fact Book, and NFL Honors results.

Rank	Candidate	Season line	Weekly move	Performance rank	Win probability
1	Klint KubliakLV · HC 3 games played. Projected finish: 11.9 projected team wins. Team record improvement: 82.35. Main forecast factors wins above preseason baseline: raises the model score scoring margin: raises the model score record improvement: raises the model score Factors describe the fitted model, not a causal explanation of voters.	3-0, +11.3 margin	0	#1	Experimental
2	Andy ReidKC · HC 3 games played. Projected finish: 11.9 projected team wins. Team record improvement: 64.71. Main forecast factors wins above preseason baseline: raises the model score scoring margin: raises the model score record improvement: raises the model score Factors describe the fitted model, not a causal explanation of voters.	3-0, +12.7 margin	0	#2	Experimental
3	Kevin O'ConnellMIN · HC 3 games played. Projected finish: 11.9 projected team wins. Team record improvement: 47.06. Main forecast factors wins above preseason baseline: raises the model score scoring margin: raises the model score record improvement: raises the model score Factors describe the fitted model, not a causal explanation of voters.	3-0, +10.0 margin	+2	#3	Experimental
4	John HarbaughNYG · HC 3 games played. Projected finish: 9.6 projected team wins. Team record improvement: 43.14. Main forecast factors wins above preseason baseline: raises the model score scoring margin: lowers the model score record improvement: raises the model score Factors describe the fitted model, not a causal explanation of voters.	2-1, -3.0 margin	+3	#4	Experimental
5	Zac TaylorCIN · HC 3 games played. Projected finish: 9.6 projected team wins. Team record improvement: 31.37. Main forecast factors wins above preseason baseline: raises the model score scoring margin: raises the model score record improvement: raises the model score Factors describe the fitted model, not a causal explanation of voters.	2-1, +5.7 margin	-2	#6	Experimental
6	Kyle ShanahanSF · HC 3 games played. Projected finish: 11.9 projected team wins. Team record improvement: 29.41. Main forecast factors scoring margin: raises the model score wins above preseason baseline: raises the model score record improvement: raises the model score Factors describe the fitted model, not a causal explanation of voters.	3-0, +16.0 margin	+2	#7	Experimental
7	Todd MonkenCLE · HC 3 games played. Projected finish: 9.6 projected team wins. Team record improvement: 37.25. Main forecast factors wins above preseason baseline: raises the model score scoring margin: lowers the model score record improvement: raises the model score Factors describe the fitted model, not a causal explanation of voters.	2-1, -5.7 margin	+4	#5	Experimental
8	Aaron GlennNYJ · HC 3 games played. Projected finish: 7.4 projected team wins. Team record improvement: 15.69. Main forecast factors wins above preseason baseline: raises the model score scoring margin: raises the model score record improvement: raises the model score Factors describe the fitted model, not a causal explanation of voters.	1-2, +1.0 margin	-4	#10	Experimental
9	Sean McDermottBUF · HC 3 games played. Projected finish: 11.9 projected team wins. Team record improvement: 29.41. Main forecast factors scoring margin: raises the model score wins above preseason baseline: raises the model score record improvement: raises the model score Factors describe the fitted model, not a causal explanation of voters.	3-0, +7.7 margin	+5	#7	Experimental
10	Jesse MinterBAL · HC 3 games played. Projected finish: 9.6 projected team wins. Team record improvement: 19.61. Main forecast factors wins above preseason baseline: raises the model score scoring margin: raises the model score record improvement: raises the model score Factors describe the fitted model, not a causal explanation of voters.	2-1, +4.7 margin	+3	#9	Experimental
11	Jonathan GannonARI · HC 3 games played. Projected finish: 7.4 projected team wins. Team record improvement: 15.69. Main forecast factors wins above preseason baseline: raises the model score scoring margin: lowers the model score record improvement: raises the model score Factors describe the fitted model, not a causal explanation of voters.	1-2, -6.0 margin	-5	#10	Experimental
12	Ben JohnsonCHI · HC 3 games played. Projected finish: 9.6 projected team wins. Team record improvement: 1.96. Main forecast factors scoring margin: raises the model score wins above preseason baseline: lowers the model score games remaining: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	2-1, +12.0 margin	+7	#15	Experimental
13	Dan CampbellDET · HC 3 games played. Projected finish: 9.6 projected team wins. Team record improvement: 13.73. Main forecast factors wins above preseason baseline: raises the model score record improvement: raises the model score scoring margin: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	2-1, -0.7 margin	+5	#12	Experimental
14	Liam CoenJAX · HC 3 games played. Projected finish: 9.6 projected team wins. Team record improvement: -9.80. Main forecast factors scoring margin: raises the model score wins above preseason baseline: lowers the model score record improvement: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	2-1, +15.3 margin	+9	#19	Experimental
15	Kellen MooreNO · HC 3 games played. Projected finish: 7.4 projected team wins. Team record improvement: -1.96. Main forecast factors wins above preseason baseline: raises the model score scoring margin: lowers the model score games remaining: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	1-2, -0.7 margin	-6	#17	Experimental
16	Dan QuinnWAS · HC 3 games played. Projected finish: 7.4 projected team wins. Team record improvement: 3.92. Main forecast factors wins above preseason baseline: raises the model score scoring margin: lowers the model score games remaining: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	1-2, -5.7 margin	+5	#14	Experimental
17	Brian SchottenheimerDAL · HC 3 games played. Projected finish: 7.4 projected team wins. Team record improvement: -7.84. Main forecast factors scoring margin: raises the model score wins above preseason baseline: lowers the model score record improvement: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	1-2, +2.0 margin	-7	#18	Experimental
18	Mike McCarthyPIT · HC 3 games played. Projected finish: 9.6 projected team wins. Team record improvement: 7.84. Main forecast factors scoring margin: lowers the model score wins above preseason baseline: raises the model score record improvement: raises the model score Factors describe the fitted model, not a causal explanation of voters.	2-1, -2.3 margin	+4	#13	Experimental
19	Dave CanalesCAR · HC 3 games played. Projected finish: 7.4 projected team wins. Team record improvement: -13.73. Main forecast factors wins above preseason baseline: lowers the model score scoring margin: raises the model score record improvement: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	1-2, +2.0 margin	-4	#20	Experimental
20	Robert SalehTEN · HC 3 games played. Projected finish: 5.1 projected team wins. Team record improvement: -17.65. Main forecast factors scoring margin: lowers the model score wins above preseason baseline: raises the model score record improvement: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	0-3, -7.3 margin	-4	#25	Experimental
21	Nick SirianniPHI · HC 3 games played. Projected finish: 9.6 projected team wins. Team record improvement: 1.96. Main forecast factors scoring margin: lowers the model score wins above preseason baseline: lowers the model score games remaining: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	2-1, -4.7 margin	-9	#15	Experimental
22	Mike MacdonaldSEA · HC 3 games played. Projected finish: 9.6 projected team wins. Team record improvement: -15.69. Main forecast factors wins above preseason baseline: lowers the model score scoring margin: raises the model score record improvement: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	2-1, +8.3 margin	-5	#23	Experimental
23	Raheem MorrisATL · HC 3 games played. Projected finish: 7.4 projected team wins. Team record improvement: -13.73. Main forecast factors scoring margin: lowers the model score wins above preseason baseline: lowers the model score record improvement: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	1-2, -5.7 margin	+6	#20	Experimental
24	Shane SteichenIND · HC 3 games played. Projected finish: 7.4 projected team wins. Team record improvement: -13.73. Main forecast factors scoring margin: lowers the model score wins above preseason baseline: lowers the model score record improvement: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	1-2, -6.3 margin	+3	#20	Experimental
25	Sean PaytonDEN · HC 3 games played. Projected finish: 9.6 projected team wins. Team record improvement: -15.69. Main forecast factors wins above preseason baseline: lowers the model score scoring margin: lowers the model score record improvement: lowers the model score Factors describe the fitted model, not a causal explanation of voters.	2-1, -3.3 margin	+5	#23	Experimental

Rank

Candidate

Season line

Weekly move

Performance rank

Win probability

Klint KubliakLV · HC

3 games played. Projected finish: 11.9 projected team wins.

Team record improvement: 82.35.

Main forecast factors

wins above preseason baseline: raises the model score
scoring margin: raises the model score
record improvement: raises the model score

Factors describe the fitted model, not a causal explanation of voters.

3-0, +11.3 margin

Experimental

Andy ReidKC · HC

3 games played. Projected finish: 11.9 projected team wins.

Team record improvement: 64.71.

Main forecast factors

wins above preseason baseline: raises the model score
scoring margin: raises the model score
record improvement: raises the model score

Factors describe the fitted model, not a causal explanation of voters.

3-0, +12.7 margin

Experimental

Kevin O'ConnellMIN · HC

3 games played. Projected finish: 11.9 projected team wins.

Team record improvement: 47.06.

Main forecast factors

wins above preseason baseline: raises the model score
scoring margin: raises the model score
record improvement: raises the model score

Factors describe the fitted model, not a causal explanation of voters.

3-0, +10.0 margin

Experimental

John HarbaughNYG · HC

3 games played. Projected finish: 9.6 projected team wins.

Team record improvement: 43.14.

Main forecast factors

wins above preseason baseline: raises the model score
scoring margin: lowers the model score
record improvement: raises the model score

Factors describe the fitted model, not a causal explanation of voters.

2-1, -3.0 margin

Experimental

Zac TaylorCIN · HC

3 games played. Projected finish: 9.6 projected team wins.

Team record improvement: 31.37.

Main forecast factors

wins above preseason baseline: raises the model score
scoring margin: raises the model score
record improvement: raises the model score

Factors describe the fitted model, not a causal explanation of voters.

2-1, +5.7 margin

-2

Experimental

Kyle ShanahanSF · HC

3 games played. Projected finish: 11.9 projected team wins.

Team record improvement: 29.41.

Main forecast factors

scoring margin: raises the model score
wins above preseason baseline: raises the model score
record improvement: raises the model score

Factors describe the fitted model, not a causal explanation of voters.

3-0, +16.0 margin

Experimental

Todd MonkenCLE · HC

3 games played. Projected finish: 9.6 projected team wins.

Team record improvement: 37.25.

Main forecast factors

wins above preseason baseline: raises the model score
scoring margin: lowers the model score
record improvement: raises the model score

Factors describe the fitted model, not a causal explanation of voters.

2-1, -5.7 margin

Experimental

Aaron GlennNYJ · HC

3 games played. Projected finish: 7.4 projected team wins.

Team record improvement: 15.69.

Main forecast factors

wins above preseason baseline: raises the model score
scoring margin: raises the model score
record improvement: raises the model score

Factors describe the fitted model, not a causal explanation of voters.

1-2, +1.0 margin

-4

#10

Experimental

Sean McDermottBUF · HC

3 games played. Projected finish: 11.9 projected team wins.

Team record improvement: 29.41.

Main forecast factors

scoring margin: raises the model score
wins above preseason baseline: raises the model score
record improvement: raises the model score

Factors describe the fitted model, not a causal explanation of voters.

3-0, +7.7 margin

Experimental

Jesse MinterBAL · HC

3 games played. Projected finish: 9.6 projected team wins.

Team record improvement: 19.61.

Main forecast factors

wins above preseason baseline: raises the model score
scoring margin: raises the model score
record improvement: raises the model score

Factors describe the fitted model, not a causal explanation of voters.

2-1, +4.7 margin

Experimental

Jonathan GannonARI · HC

3 games played. Projected finish: 7.4 projected team wins.

Team record improvement: 15.69.

Main forecast factors

wins above preseason baseline: raises the model score
scoring margin: lowers the model score
record improvement: raises the model score

Factors describe the fitted model, not a causal explanation of voters.

1-2, -6.0 margin

-5

#10

Experimental

Ben JohnsonCHI · HC

3 games played. Projected finish: 9.6 projected team wins.

Team record improvement: 1.96.

Main forecast factors

scoring margin: raises the model score
wins above preseason baseline: lowers the model score
games remaining: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

2-1, +12.0 margin

#15

Experimental

Dan CampbellDET · HC

3 games played. Projected finish: 9.6 projected team wins.

Team record improvement: 13.73.

Main forecast factors

wins above preseason baseline: raises the model score
record improvement: raises the model score
scoring margin: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

2-1, -0.7 margin

#12

Experimental

Liam CoenJAX · HC

3 games played. Projected finish: 9.6 projected team wins.

Team record improvement: -9.80.

Main forecast factors

scoring margin: raises the model score
wins above preseason baseline: lowers the model score
record improvement: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

2-1, +15.3 margin

#19

Experimental

Kellen MooreNO · HC

3 games played. Projected finish: 7.4 projected team wins.

Team record improvement: -1.96.

Main forecast factors

wins above preseason baseline: raises the model score
scoring margin: lowers the model score
games remaining: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

1-2, -0.7 margin

-6

#17

Experimental

Dan QuinnWAS · HC

3 games played. Projected finish: 7.4 projected team wins.

Team record improvement: 3.92.

Main forecast factors

wins above preseason baseline: raises the model score
scoring margin: lowers the model score
games remaining: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

1-2, -5.7 margin

#14

Experimental

Brian SchottenheimerDAL · HC

3 games played. Projected finish: 7.4 projected team wins.

Team record improvement: -7.84.

Main forecast factors

scoring margin: raises the model score
wins above preseason baseline: lowers the model score
record improvement: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

1-2, +2.0 margin

-7

#18

Experimental

Mike McCarthyPIT · HC

3 games played. Projected finish: 9.6 projected team wins.

Team record improvement: 7.84.

Main forecast factors

scoring margin: lowers the model score
wins above preseason baseline: raises the model score
record improvement: raises the model score

Factors describe the fitted model, not a causal explanation of voters.

2-1, -2.3 margin

#13

Experimental

Dave CanalesCAR · HC

3 games played. Projected finish: 7.4 projected team wins.

Team record improvement: -13.73.

Main forecast factors

wins above preseason baseline: lowers the model score
scoring margin: raises the model score
record improvement: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

1-2, +2.0 margin

-4

#20

Experimental

Robert SalehTEN · HC

3 games played. Projected finish: 5.1 projected team wins.

Team record improvement: -17.65.

Main forecast factors

scoring margin: lowers the model score
wins above preseason baseline: raises the model score
record improvement: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

0-3, -7.3 margin

-4

#25

Experimental

Nick SirianniPHI · HC

3 games played. Projected finish: 9.6 projected team wins.

Team record improvement: 1.96.

Main forecast factors

scoring margin: lowers the model score
wins above preseason baseline: lowers the model score
games remaining: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

2-1, -4.7 margin

-9

#15

Experimental

Mike MacdonaldSEA · HC

3 games played. Projected finish: 9.6 projected team wins.

Team record improvement: -15.69.

Main forecast factors

wins above preseason baseline: lowers the model score
scoring margin: raises the model score
record improvement: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

2-1, +8.3 margin

-5

#23

Experimental

Raheem MorrisATL · HC

3 games played. Projected finish: 7.4 projected team wins.

Team record improvement: -13.73.

Main forecast factors

scoring margin: lowers the model score
wins above preseason baseline: lowers the model score
record improvement: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

1-2, -5.7 margin

#20

Experimental

Shane SteichenIND · HC

3 games played. Projected finish: 7.4 projected team wins.

Team record improvement: -13.73.

Main forecast factors

scoring margin: lowers the model score
wins above preseason baseline: lowers the model score
record improvement: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

1-2, -6.3 margin

#20

Experimental

Sean PaytonDEN · HC

3 games played. Projected finish: 9.6 projected team wins.

Team record improvement: -15.69.

Main forecast factors

wins above preseason baseline: lowers the model score
scoring margin: lowers the model score
record improvement: lowers the model score

Factors describe the fitted model, not a causal explanation of voters.

2-1, -3.3 margin

#23

Experimental