Heisman odds

Who is likely to win the Heisman Trophy, and who is likely to be in New York. A model's guess, built to be checked: below the table is how it has done on every season since 2013.

Updated Nov 13, through Week 11. Ballots are due Dec 7, when the finalists are announced; the winner is named Dec 12. Championship games count; bowls and the playoff do not.

#	Player	Win	Wk	Finalist	So far	Proj. yds	What has to happen
1	Darian Mensah QB · Miami (FL) · #6, 8–1	30%	▼0.9	69%	2,701 pass yds, 28 TD · 137 rush, 2 TD	3,910	36% if Miami (FL) finishes top 4 (50% likely) · 25% if not
2	Keelon Russell QB · Alabama · #2, 7–2	13%	▲0.7	44%	2,263 pass yds, 18 TD · 276 rush, 5 TD	3,420	14% if Alabama finishes top 4 (86% likely) · 2.5% if not
3	Malachi Toney WR/TE · Miami (FL) · #6, 8–1	11%	–	56%	1,027 rec yds, 13 TD	1,480	14% if Miami (FL) finishes top 4 (50% likely) · 7.5% if not
4	Devon Dampier QB · Utah · #11, 9–0	9.9%	▲0.2	30%	2,053 pass yds, 20 TD · 483 rush, 7 TD	3,530	17% if Utah finishes top 4 (30% likely) · 6.8% if not
5	Jeremiah Smith WR/TE · Ohio State · #5, 6–3	6.0%	▼0.5	34%	1,200 rec yds, 14 TD	1,550	22% if Ohio State finishes top 4 (3.7% likely) · 5.4% if not
6	Drew Mestemaker QB · Oklahoma State · #42, 6–3	4.9%	▼0.4	16%	2,962 pass yds, 29 TD · 177 rush, 3 TD	4,050	–
7	Sam Leavitt QB · LSU · #7, 6–3	4.1%	▼0.1	13%	2,551 pass yds, 17 TD · 340 rush, 8 TD	3,710	16% if LSU finishes top 4 (0.6% likely) · 4.0% if not
8	Kevin Jennings QB · SMU · #31, 7–2	2.4%	–	9.6%	2,783 pass yds, 25 TD · 133 rush, 2 TD	3,810	–
9	Noah Fifita QB · Arizona · #27, 7–2	2.1%	–	7.6%	2,777 pass yds, 21 TD · 135 rush, 4 TD	3,760	–
10	Nate Sheppard RB · Duke · #35, 7–2	1.4%	▼0.1	8.2%	1,189 rush yds, 17 TD · 306 rec	1,930	–
11	Wayshawn Parker RB · Utah · #11, 9–0	1.4%	▲0.1	6.1%	762 rush yds, 9 TD · 269 rec	1,420	2.9% if Utah finishes top 4 (30% likely) · 0.7% if not
12	Giovanni Lopez QB · Wake Forest · #23, 8–1	1.3%	–	3.1%	2,176 pass yds, 18 TD · 318 rush, 6 TD	3,350	–
13	Lanorris Sellers QB · South Carolina · #15, 6–3	1.2%	▲0.1	3.3%	2,100 pass yds, 17 TD · 637 rush, 7 TD	3,520	–
14	Conner Weigman QB · Houston · #26, 7–2	1.2%	▲0.1	2.9%	2,279 pass yds, 22 TD · 279 rush, 7 TD	3,330	–
15	Lincoln Kienholz QB · Louisville · #24, 6–3	1.0%	▲0.1	2.5%	2,276 pass yds, 14 TD · 394 rush, 11 TD	3,480	–
	Everyone else	8.8%

Where the chance sits, by position: QB 74%, WR/TE 19%, RB 6.5%. 65 candidates were scored across 10,000 simulated seasons.

The rest of the field

· ranks 16–65

Every other candidate the model scored, 50 more: the players on teams in the top 45 of our ratings who rank among the leading quarterbacks, running backs and receivers in yards and touchdowns. Their chances are small but not zero, and they are what the “everyone else” line above is made of.

#	Player	Win	Wk	Finalist	So far	Proj. yds
16	Charlie Becker WR/TE · Indiana · #12, 8–1	1.0%	–	3.3%	875 rec yds, 9 TD	1,170
17	Trinidad Chambliss QB · Ole Miss · #9, 6–3	0.9%	▲0.1	2.6%	2,359 pass yds, 18 TD · 187 rush, 7 TD	3,280
18	Wayne Knight RB · UCLA · #14, 9–0	0.9%	▲0.1	2.8%	789 rush yds, 13 TD · 155 rec	1,290
19	Dylan Riley RB · Boise State · #30, 8–1	0.9%	▲0.1	3.2%	1,241 rush yds, 11 TD · 218 rec	1,850
20	C.J. Carr QB · Notre Dame · #3, 8–1	0.7%	▲0.1	2.3%	2,168 pass yds, 21 TD · 89 rush, 3 TD	2,910
21	DeSean Bishop RB · Tennessee · #10, 7–2	0.7%	–	2.0%	1,066 rush yds, 13 TD · 64 rec	1,460
22	Jayden Maiava QB · USC · #13, 7–2	0.5%	▲0.1	1.3%	2,525 pass yds, 20 TD · -71 rush, 2 TD	3,180
23	Caleb Hawkins RB · Oklahoma State · #42, 6–3	0.4%	–	1.6%	1,081 rush yds, 7 TD · 424 rec	1,930
24	Bear Bachmeier QB · BYU · #20, 7–2	0.4%	▲0.1	1.0%	2,022 pass yds, 13 TD · 395 rush, 7 TD	3,180
25	Carlos Hernandez WR/TE · Wake Forest · #23, 8–1	0.3%	–	0.9%	945 rec yds, 7 TD	1,260
26	J'Koby Williams RB · Texas Tech · #21, 8–1	0.2%	–	0.7%	954 rush yds, 7 TD · 208 rec	1,550
27	Braden Pegan WR/TE · Utah · #11, 9–0	0.2%	–	0.5%	591 rec yds, 8 TD	840
28	Ashton Daniels QB · Florida State · #43, 4–5	0.1%	–	0.5%	2,146 pass yds, 14 TD · 413 rush, 13 TD	3,300
29	Jackson Harris WR/TE · LSU · #7, 6–3	0.1%	–	0.6%	800 rec yds, 7 TD	1,080
30	Jamal Roberts RB · Missouri · #19, 6–3	0.1%	–	0.5%	1,071 rush yds, 9 TD · 125 rec	1,530
31	Nick Marsh WR/TE · Indiana · #12, 8–1	0.1%	–	0.5%	669 rec yds, 8 TD	910
32	Collin Dixon WR/TE · Illinois · #41, 6–3	0.1%	–	0.4%	905 rec yds, 12 TD	1,180
33	Nolan James Jr. RB · Notre Dame · #3, 8–1	0.1%	–	0.4%	571 rush yds, 9 TD · 141 rec	930
34	Turbo Richard RB · Indiana · #12, 8–1	0.1%	–	0.3%	745 rush yds, 6 TD · 49 rec	1,080
35	Anthony Colandrea QB · Nebraska · #25, 5–4	0.1%	–	0.2%	2,108 pass yds, 16 TD · 381 rush, 4 TD	3,220
36	Legend Glasker WR/TE · BYU · #20, 7–2	0.1%	–	0.2%	703 rec yds, 5 TD · 114 rush	1,070
37	Dilin Jones RB · LSU · #7, 6–3	0.1%	–	0.2%	715 rush yds, 7 TD · 253 rec	1,250
38	Bo Jackson RB · Ohio State · #5, 6–3	0.1%	–	0.2%	685 rush yds, 6 TD · 145 rec	1,090
39	Jaden Craig QB · TCU · #45, 4–5	0.1%	–	0.2%	2,439 pass yds, 12 TD · 121 rush, 4 TD	3,310
40	Byrum Brown QB · Auburn · #37, 5–4	0.1%	–	0.1%	1,737 pass yds, 11 TD · 607 rush, 8 TD	3,040
41	Thomas Castellanos RB · Texas Tech · #21, 8–1	0.1%	–	0.2%	284 rush yds, 3 TD · 0 rec	1,120
42	Jadan Baugh RB · Florida · #22, 5–4	<0.1%	–	0.1%	836 rush yds, 14 TD · 66 rec	1,160
43	Aidan Chiles QB · Northwestern · #28, 6–3	<0.1%	–	0.1%	1,898 pass yds, 13 TD · 274 rush, 10 TD	2,810
44	Tre Richardson WR/TE · Louisville · #24, 6–3	<0.1%	–	0.1%	685 rec yds, 3 TD · 169 rush	1,110
45	Justin Bowick WR/TE · Oklahoma State · #42, 6–3	<0.1%	–	0.1%	790 rec yds, 10 TD	1,020
46	Cayden Lee WR/TE · Missouri · #19, 6–3	<0.1%	–	0.1%	809 rec yds, 5 TD	1,040
47	Kendrick Raphael RB · SMU · #31, 7–2	<0.1%	–	0.1%	760 rush yds, 10 TD · 163 rec	1,210
48	Wyatt Young WR/TE · Oklahoma State · #42, 6–3	<0.1%	–	0.1%	763 rec yds, 8 TD	1,010
49	Deuce Alexander WR/TE · Ole Miss · #9, 6–3	<0.1%	–	0.1%	669 rec yds, 5 TD	910
50	Amare Thomas WR/TE · Houston · #26, 7–2	<0.1%	–	0.1%	698 rec yds, 8 TD	910
51	Isaac Brown RB · Louisville · #24, 6–3	<0.1%	–	0.1%	745 rush yds, 8 TD · 145 rec	1,160
52	Isaiah Mizell WR/TE · Arizona · #27, 7–2	<0.1%	–	0.1%	753 rec yds, 7 TD	980
53	King Miller RB · USC · #13, 7–2	<0.1%	–	0.1%	681 rush yds, 5 TD · 49 rec	960
54	Gavin Freeman WR/TE · Baylor · #33, 6–3	<0.1%	–	<0.1%	852 rec yds, 3 TD	1,100
55	Griffin Wilde WR/TE · Northwestern · #28, 6–3	<0.1%	–	0.1%	813 rec yds, 5 TD	1,050
56	Rasean Jones WR/TE · Boise State · #30, 8–1	<0.1%	–	<0.1%	661 rec yds, 5 TD	910
57	Donovan Olugbode WR/TE · Missouri · #19, 6–3	<0.1%	–	<0.1%	633 rec yds, 7 TD	820
58	Isaiah Sategna WR/TE · Oklahoma · #17, 5–4	<0.1%	–	<0.1%	625 rec yds, 4 TD	880
59	Caleb Komolafe RB · Northwestern · #28, 6–3	<0.1%	–	<0.1%	643 rush yds, 5 TD · 169 rec	1,060
60	Yamir Knight WR/TE · SMU · #31, 7–2	<0.1%	–	<0.1%	626 rec yds, 6 TD	840
61	Damon Ferguson Jr. RB · Pittsburgh · #44, 6–3	<0.1%	–	<0.1%	662 rush yds, 6 TD · 113 rec	1,010
62	Anthony Evans III WR/TE · Mississippi State · #39, 4–5	<0.1%	–	<0.1%	711 rec yds, 5 TD	910
63	Cataurus Hicks WR/TE · Pittsburgh · #44, 6–3	<0.1%	–	<0.1%	698 rec yds, 6 TD	900
64	Fluff Bothwell RB · Mississippi State · #39, 4–5	<0.1%	–	<0.1%	613 rush yds, 3 TD · 143 rec	990
65	Chris Lawson WR/TE · Washington · #38, 5–4	<0.1%	–	<0.1%	727 rec yds, 3 TD	950

The Hidden Heisman · Week 10

The biggest game this week from outside the power conferences

Jackson Gutierrez

Navy · American · W 42–35 vs Temple (MRI #108)

Passing178 yds1 TD

Rushing180 yds5 TD

• Top 0.03% of every FBS player-game since 2012 — #46 of 140,947
• 6 total touchdowns, tied for the most by any FBS player this week
• Not among the top 15 in the Heisman odds that week. A game like this is how a name gets onto the list.

Who reaches New York

The Trust invites three to five players to the ceremony, usually four. This is each candidate's chance of finishing in the top four of the voting, most likely first. Added up, the chances come to about 3.3 offensive finalists. These chances were rescaled after the backtest showed the raw ones running high for everyone but the favorites (a candidate given 9% reached New York about 5% of the time); on held-out seasons that trimmed the error a little, from 0.0322 to 0.0320.

Player	Finalist	Win
Darian Mensah QB · Miami (FL)	69%	30%
Malachi Toney WR/TE · Miami (FL)	56%	11%
Keelon Russell QB · Alabama	44%	13%
Jeremiah Smith WR/TE · Ohio State	34%	6.0%
Devon Dampier QB · Utah	30%	9.9%
Drew Mestemaker QB · Oklahoma State	16%	4.9%
Sam Leavitt QB · LSU	13%	4.1%
Kevin Jennings QB · SMU	9.6%	2.4%

Not in this table: defenders. A player who was mainly a defender has been invited to New York in 4 of the last 14 seasons (2012, 2016, 2019, 2021), so a share of the four places usually goes to someone the model does not score. The leading defensive players on top-ranked teams right now, by tackles, sacks and takeaways: Rasheem Biles (Texas), Braydon Brus (Northwestern), Tony Rojas (Penn State).

The Hidden Heisman this season

Wk	Player	Opponent	Line	Rarity
10	Jackson Gutierrez Navy	vs Temple	178 pass, 1 TD · 180 rush, 5 TD	top 0.03%
9	Brad Jackson Texas State	vs Boise State	327 pass, 4 TD · 54 rush, 1 TD	top 0.81%
8	Gael Ochoa Rice	vs Florida Atlantic	80 pass, 1 TD · 259 rush, 4 TD	top 0.05%
7	Jackson Gutierrez Navy	vs UTSA	120 pass, 2 TD · 139 rush, 2 TD · 63 rece, 0 TD	top 0.37%
6	Jackson Gutierrez Navy	vs Tulsa	95 pass, 1 TD · 232 rush, 3 TD	top 0.18%
5	Jackson Arnold UNLV	vs California	177 pass, 3 TD · 110 rush, 2 TD	top 0.61%
4	Jahiem White North Texas	vs Houston Christian	133 rush, 4 TD	top 1.03%
3	Braden Atkinson Oregon State	vs Montana	333 pass, 5 TD · 4 rush, 1 TD	top 0.91%
2	Jesse Legree Oregon State	vs Texas Tech	240 rece, 2 TD	top 1.64%
1	Jaylin Carter Memphis	vs Arkansas State	183 rush, 4 TD	top 0.44%

One a week, from the Group of Five and the independents (not Notre Dame), leaving out anyone the Heisman odds already give more than 5%. The game is scored on yards and touchdowns — passing yards count a little less, since there are more of them — and scaled by how good the opponent was going in: up to 30% more against a top team, as much as 15% less against a weak one or an FCS side. Decided once each week is final, and never revised. When the regular season is over, the season award goes to the player with the most of those points across all his games, under the same rules.

How it works

The rest of the season is played out 10,000 times with the same engine as the season simulation, so a team that loses twice in November is a different argument from one that goes unbeaten, and each simulated season knows which it is. Each candidate's finished stat line is projected from what he has done and how many games his team has left, using what actually happened to candidates at this point of every past season (hot starts cool, and some players get hurt). Then a model that weighs what voters have rewarded — how much he produced compared with the rest of the field, how he compares within his position, and how good his team is — picks a winner in each simulated season. The chances are how often each player won.

What it cannot see. Defenders are not candidates: nobody who was mainly a defender has won since 1997, but a great one will still take votes, and those sit in “everyone else.” A player who does something remarkable on both sides of the ball, or in one famous game, is worth more to a voter than a stat line says (Travis Hunter in 2024 is the case the model missed worst). A player's output and his team's results are simulated separately, though in life they move together. And it knows nothing of injuries that have not happened yet, except in the proportions they have happened before.

How it has done

Two tests, both on past seasons, both leaving the season being predicted out of everything the model learned. Given a finished regular season, it names the winner first 64% of the time and has him in its top three 86% of the time, across 14 seasons (2012–2025). Picking the most productive player on a top-five team manages 50%.

Standing partway through a season is this page's real job. At each of six points in each season from 2013 to 2025, it saw only what was known then, simulated the rest, and ranked the field. The last two columns are the same model applied to the standings as they stood, with no simulated season and no projection.

Thirteen seasons is a small sample: each season moves a rate by about eight points, so read the pattern, not any one week. Where it says a candidate has a 20–30% chance, candidates like that have won about that often; the very small chances run a little high.