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The race, week by week
Award forecasts alongside on-field performance. Follow the leaders, see what drives their rankings, and revisit each weekly snapshot.
2026 season · Through week 5
Forecast leader
Denzel Boston
CLE · WR
Historical top-three hit rate
50%
6 retrospective validation seasons at this horizon
Forecast status
Experimental
Win percentages withheld pending validation
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.
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: 50%. Winner coverage: 100%. Log loss: 2.13. Brier score: 0.72.
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.
Top 25 · 65 candidates
| Rank | Candidate | Season line | Weekly move | Performance rank | Win probability |
|---|---|---|---|---|---|
| 1 | Denzel BostonCLE · WR5 games played. Projected finish: 918.2 receiving yards · 7.9 receiving TDs. Shrunk competitive EPA above a positional baseline: 0.49. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 330 rec yds, 3 TD | 0 | #4 | Experimental |
| 2 | Carnell TateTEN · WR5 games played. Projected finish: 787.5 receiving yards · 0.9 receiving TDs. Shrunk competitive EPA above a positional baseline: -0.03. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 274 rec yds, 0 TD | 0 | #42 | Experimental |
| 3 | Omar Cooper Jr.NYJ · WR1 games played. Projected finish: 368.8 receiving yards · 1.6 receiving TDs. Shrunk competitive EPA above a positional baseline: 0.01. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 30 rec yds, 0 TD | +7 | #24 | Experimental |
| 4 | Athan KaliakmanisWAS · QB1 games played. Projected finish: 2,205.5 passing yards · 13.7 passing TDs. Shrunk competitive EPA above a positional baseline: -0.47. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 186 pass yds, 1 TD, 1 INT · 16 rush yds, 0 TD | -1 | #51 | Experimental |
| 5 | Jalon DanielsTB · QB3 games played. Projected finish: 2,038.4 passing yards · 12.8 passing TDs. Shrunk competitive EPA above a positional baseline: 1.83. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 337 pass yds, 2 TD, 3 INT · 87 rush yds, 0 TD | +13 | #2 | Experimental |
| 6 | Jeremiyah LoveARI · RB5 games played. Projected finish: 712.5 rushing yards · 3.4 rushing TDs. Shrunk competitive EPA above a positional baseline: 3.15. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 245 rush yds, 1 TD · 36 rec yds, 1 TD | -1 | #1 | Experimental |
| 7 | Emmett JohnsonKC · RB4 games played. Projected finish: 318.7 rushing yards · 1.3 rushing TDs. Shrunk competitive EPA above a positional baseline: 0.38. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 56 rush yds, 0 TD · 74 rec yds, 0 TD | -3 | #7 | Experimental |
| 8 | Fernando MendozaLV · QB1 games played. Projected finish: 1,736.3 passing yards · 10.3 passing TDs. Shrunk competitive EPA above a positional baseline: unavailable. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 48 pass yds, 0 TD, 0 INT · 3 rush yds, 0 TD | Unavailable | Unavailable | Experimental |
| 9 | Caleb DouglasMIA · WR2 games played. Projected finish: 561.3 receiving yards · 1.3 receiving TDs. Shrunk competitive EPA above a positional baseline: 0.03. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 113 rec yds, 0 TD | 0 | #17 | Experimental |
| 10 | Antonio WilliamsWAS · WR5 games played. Projected finish: 509.9 receiving yards · 3.2 receiving TDs. Shrunk competitive EPA above a positional baseline: 0.07. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 155 rec yds, 1 TD | +4 | #13 | Experimental |
| 11 | Josh CameronJAX · WR5 games played. Projected finish: 421.2 receiving yards · 5.5 receiving TDs. Shrunk competitive EPA above a positional baseline: 0.13. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 117 rec yds, 2 TD | +6 | #10 | Experimental |
| 12 | Malachi FieldsNYG · WR5 games played. Projected finish: 488.9 receiving yards · 3.2 receiving TDs. Shrunk competitive EPA above a positional baseline: 0.14. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 146 rec yds, 1 TD | -1 | #9 | Experimental |
| 13 | Ted Hurst IIITB · WR4 games played. Projected finish: 486.7 receiving yards · 3.5 receiving TDs. Shrunk competitive EPA above a positional baseline: 0.03. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 128 rec yds, 1 TD | +2 | #18 | Experimental |
| 14 | Germie BernardPIT · WR4 games played. Projected finish: 516.7 receiving yards · 1 receiving TDs. Shrunk competitive EPA above a positional baseline: 0.11. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 4 rush yds, 0 TD · 140 rec yds, 0 TD | +17 | #12 | Experimental |
| 15 | Jonah ColemanDEN · RB2 games played. Projected finish: 328.3 rushing yards · 4.6 rushing TDs. Shrunk competitive EPA above a positional baseline: 0.19. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 39 rush yds, 1 TD · 19 rec yds, 0 TD | -9 | #8 | Experimental |
| 16 | Dohnte MeyersCIN · WR5 games played. Projected finish: 477.2 receiving yards · 0.9 receiving TDs. Shrunk competitive EPA above a positional baseline: 0.12. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 10 rush yds, 0 TD · 141 rec yds, 0 TD | -4 | #11 | Experimental |
| 17 | KC ConcepcionCLE · WR5 games played. Projected finish: 495.9 receiving yards · 0.9 receiving TDs. Shrunk competitive EPA above a positional baseline: -0.22. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 9 rush yds, 0 TD · 149 rec yds, 0 TD | -9 | #48 | Experimental |
| 18 | Jack StrandATL · QB1 games played. Projected finish: 1,773.7 passing yards · 10.3 passing TDs. Shrunk competitive EPA above a positional baseline: unavailable. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 59 pass yds, 0 TD, 1 INT · 16 rush yds, 0 TD | -11 | Unavailable | Experimental |
| 19 | Jadarian PriceSEA · RB3 games played. Projected finish: 504.1 rushing yards · 1.4 rushing TDs. Shrunk competitive EPA above a positional baseline: -0.90. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 119 rush yds, 0 TD · 21 rec yds, 0 TD | -3 | #52 | Experimental |
| 20 | Mike Washington Jr.LV · RB5 games played. Projected finish: 432.5 rushing yards · 3.4 rushing TDs. Shrunk competitive EPA above a positional baseline: 0.49. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 125 rush yds, 1 TD · 4 rec yds, 0 TD | -7 | #5 | Experimental |
| 21 | DJ HermanMIA · RB2 games played. Projected finish: 211.3 rushing yards · 1.6 rushing TDs. Shrunk competitive EPA above a positional baseline: 0.00. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 18 rec yds, 0 TD | 0 | #25 | Experimental |
| 22 | Kaelon BlackSF · RB5 games played. Projected finish: 458.2 rushing yards · 1.1 rushing TDs. Shrunk competitive EPA above a positional baseline: 0.97. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 136 rush yds, 0 TD · 5 rec yds, 0 TD | -3 | #3 | Experimental |
| 23 | Reggie VirgilARI · WR1 games played. Projected finish: 365.4 receiving yards · 1.6 receiving TDs. Shrunk competitive EPA above a positional baseline: -0.00. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 29 rec yds, 0 TD | Unavailable | #31 | Experimental |
| 24 | Chris BellMIA · WR5 games played. Projected finish: 362.9 receiving yards · 0.9 receiving TDs. Shrunk competitive EPA above a positional baseline: 0.06. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 26 rush yds, 0 TD · 92 rec yds, 0 TD | +4 | #15 | Experimental |
| 25 | Makai LemonPHI · WR5 games played. Projected finish: 400.2 receiving yards · 0.9 receiving TDs. Shrunk competitive EPA above a positional baseline: -0.10. Main forecast factors
Factors describe the fitted model, not a causal explanation of voters. | 108 rec yds, 0 TD | +7 | #46 | Experimental |
Performance ranks use shrunk competitive epa above a positional baseline. Offensive credit splits passing EPA between passer and receiver and excludes noncompetitive drives. It subtracts a positional 25th-percentile baseline and uses a 150-opportunity prior to reduce small-sample outliers. Defensive ranks use a descriptive box-stat index. These are separate measures and do not imply equal value across positions.