Dynasty rookie board

The same career-value model that runs the big board, pointed at the only question a dynasty GM ever has: which rookies return fantasy production, and for how long. Quarterbacks, running backs, receivers and tight ends only — nobody starts a left tackle.

The 2026 class has been drafted — this board is the model’s pre-draft read, useful as a receipt against how the rookies actually landed.

Format1QB Superflex|Year2027 2026 2025 2024 2023 2022

1QB starts one quarterback, so even good QB prospects slide — QBs carry a 0.80 multiplier. Superflex starts two, which makes the position the scarcest asset in the format — QBs carry 1.30 instead. Nothing else changes between the two boards.

#	Player	Pos	College	Dynasty score	How it's built	Bust	Tier	Consensus
1	Fernando Mendoza	QB	Indiana	114.4	88.0 × 1.30	5%	Elite	3
2	Carnell Tate	WR	Ohio St.	95.2	86.6 × 1.10	0% class average	Elite	5
3	Jordyn Tyson	WR	Arizona St.	91.5	83.2 × 1.10	7%	Elite	11
4	Omar Cooper Jr.	WR	Indiana	90.3	82.0 × 1.10	0% class average	Elite	19
5	Makai Lemon	WR	USC	81.4	74.0 × 1.10	3%	Elite	9
6	KC Concepcion	WR	Texas A&M	81.2	73.8 × 1.10	0% class average	Elite	17
7	Germie Bernard	WR	Alabama	78.7	71.6 × 1.10	10%	Starter	45
8	Jeremiyah Love	RB	Notre Dame	78.4	92.2 × 0.85 × 1.00	11%	Elite	1
9	Kenyon Sadiq	TE	Oregon	77.6	81.6 × 0.95	6%	Elite	12
10	Chris Bell	WR	Louisville	74.5	67.8 × 1.10	1%	Starter	52
11	Antonio Williams	WR	Clemson	73.5	66.8 × 1.10	20%	Starter	61
12	Ty Simpson	QB	Alabama	72.4	55.7 × 1.30	27%	Starter	33
13	Denzel Boston	WR	Washington	70.6	64.2 × 1.10	6%	Starter	25
14	Cole Payton	QB	North Dakota St.	70.4	54.1 × 1.30	21%	Starter	86
15	Zachariah Branch	WR	Georgia	67.0	60.9 × 1.10	0% class average	Starter	66
16	Bryce Lance	WR	North Dakota St.	65.4	59.4 × 1.10	19%	Starter	116
17	Ted Hurst	WR	Georgia St.	63.9	58.1 × 1.10	24%	Starter	100
18	Eli Stowers	TE	Vanderbilt	62.8	66.1 × 0.95	20%	Starter	46
19	Elijah Sarratt	WR	Indiana	61.6	56.0 × 1.10	0% class average	Starter	74
20	Skyler Bell	WR	Connecticut	61.3	55.7 × 1.10	21%	Starter	103
21	Taylen Green	QB	Arkansas	60.2	46.3 × 1.30	28%	Starter	140
22	Drew Allar	QB	Penn St.	58.4	44.9 × 1.30	33%	Starter	113
23	Chris Brazzell II	WR	Tennessee	57.3	52.1 × 1.10	1%	Starter	57
24	Malachi Fields	WR	Notre Dame	55.5	50.5 × 1.10	22%	Starter	77
25	Mike Washington Jr.	RB	Arkansas	55.5	65.2 × 0.85*	15%	Starter	72
26	Jadarian Price	RB	Notre Dame	52.8	63.8 × 0.85 × 0.97	15%	Starter	43
27	Caleb Douglas	WR	Texas Tech	50.1	45.5 × 1.10	25%	Starter	—
28	Garrett Nussmeier	QB	LSU	48.8	37.5 × 1.30	27%	Starter	128
29	Jonah Coleman	RB	Washington	48.6	59.2 × 0.85 × 0.97	20%	Starter	131
30	Max Klare	TE	Ohio St.	47.5	50.0 × 0.95	21%	Starter	78
31	Brenen Thompson	WR	Mississippi St.	46.5	42.2 × 1.10	27%	Starter	114
32	Kevin Coleman Jr.	WR	Missouri	46.4	42.2 × 1.10	19%	Starter	112
33	Justin Joly	TE	North Carolina St.	41.8	44.0 × 0.95	23%	Starter	139
34	Emmett Johnson	RB	Nebraska	41.6	50.3 × 0.85 × 0.97	28%	Starter	87
35	Sam Roush	TE	Stanford	40.4	42.5 × 0.95	29%	Starter	69
36	Cade Klubnik	QB	Clemson	38.9	30.0 × 1.30	37%	—	—
37	Jack Endries	TE	Texas	38.8	40.9 × 0.95	18%	Starter	99
38	Barion Brown	WR	LSU	38.7	35.2 × 1.10	22%	Starter	—
39	Kaytron Allen	RB	Penn St.	37.5	47.2 × 0.85 × 0.94	27%	Starter	123
40	CJ Daniels	WR	Miami (FL)	37.5	34.1 × 1.10	24%	Starter	58
41	Ja'Kobi Lane	WR	USC	37.2	33.8 × 1.10	17%	Starter	136
42	Athan Kaliakmanis	QB	Rutgers	37.0	28.4 × 1.30	47%	—	—
43	Kendrick Law	WR	Kentucky	35.2	32.0 × 1.10	25%	Starter	—
44	Will Kacmarek	TE	Ohio St.	32.8	34.5 × 0.95	14%	Starter	—
45	Reggie Virgil	WR	Texas Tech	32.7	29.7 × 1.10	23%	Starter	144
46	Nate Boerkircher	TE	Texas A&M	32.3	34.0 × 0.95	32%	Starter	118
47	Demond Claiborne	RB	Wake Forest	32.0	38.7 × 0.85 × 0.97	34%	Starter	—
48	Tanner Koziol	TE	Houston	31.9	33.6 × 0.95	12%	Starter	—
49	Zavion Thomas	WR	LSU	31.7	28.9 × 1.10	17%	Starter	—
50	Malik Benson	WR	Oregon	31.1	28.3 × 1.10	21%	Starter	—
51	Cyrus Allen	WR	Cincinnati	30.4	27.6 × 1.10	36%	Starter	91
52	Jam Miller	RB	Alabama	27.9	32.8 × 0.85*	66%	Starter	126
53	Josh Cameron	WR	Baylor	27.8	25.2 × 1.10	26%	Starter	68
54	Adam Randall	RB	Clemson	26.9	31.6 × 0.85 × 1.00	34%	Starter	—
55	Riley Nowakowski	TE	Indiana	26.2	27.5 × 0.95	28%	Starter	—
56	Kaden Wetjen	WR	Iowa	26.2	23.8 × 1.10	23%	Starter	—
57	Jaren Kanak	TE	Oklahoma	25.9	27.3 × 0.95	33%	Starter	—
58	Josh Cuevas	TE	Alabama	25.7	27.0 × 0.95	35%	Starter	—
59	Marlin Klein	TE	Michigan	25.6	27.0 × 0.95	35%	Starter	137
60	Matthew Hibner	TE	SMU	25.4	26.8 × 0.95	32%	Starter	—
61	Behren Morton	QB	Texas Tech	24.3	18.7 × 1.30	40%	—	—
62	Anthony Smith	WR	East Carolina	23.5	21.4 × 1.10	26%	Starter	—
63	Bauer Sharp	TE	LSU	22.4	23.6 × 0.95	15%	Starter	—
64	Seth McGowan	RB	Kentucky	22.0	29.6 × 0.85 × 0.88	19%	Starter	—
65	Seydou Traore	TE	Mississippi St.	22.0	23.1 × 0.95	21%	Elite	—
66	Lewis Bond	WR	Boston Col.	21.5	19.5 × 1.10	26%	Starter	130
67	Eli Raridon	TE	Notre Dame	21.4	22.5 × 0.95	21%	Starter	62
68	Emmanuel Henderson Jr.	WR	Kansas	21.3	19.4 × 1.10	40%	Starter	—
69	CJ Williams	WR	Stanford	21.2	19.3 × 1.10	26%	Starter	—
70	Max Bredeson	TE	Michigan	20.7	21.8 × 0.95	25%	Starter	—
71	Dallen Bentley	TE	Utah	19.5	20.5 × 0.95	36%	Starter	—
72	Carsen Ryan	TE	BYU	17.5	18.4 × 0.95	21%	Starter	—
73	Kaelon Black	RB	Indiana	11.5	15.5 × 0.85 × 0.87	15%	Starter	—

* Age not on file yet for this back, so the RB age adjustment is skipped (multiplier ×1.00) until it lands.

How this differs from the big board

Built from the same models as the big board — here's exactly how the lens differs. The base is the served career-value model score, untouched. On top of it sit three documented adjustments, all shown per player in the table:

Dynasty score = model score × position multiplier (Superflex) × RB age multiplier

Position: QB ×1.30, RB ×0.85, WR ×1.10, TE ×0.95 — QB scarcity by format, the RB career-length discount, the WR longevity premium, the TE slow-onboarding haircut.
RB age cliff: RB only: 1.00 at age 22 or younger at draft, minus 0.05 per year older, floor 0.85. When we don't have a player's age on file, no adjustment is applied and the row says so.
Tier reads: shown only where the tier model itself stands behind them; when it isn't confident, you get a dash, not a guess.

The multipliers are round numbers encoding dynasty-market convention (QB scarcity by format, the RB age cliff, WR longevity, the TE year-3 breakout) — convention, not Draftanomics research. The model signal is entirely in the base. College production volume (target and workload share) is already inside the base score as model features — it isn't double-counted here. See methodology for how the career-value model is fit and validated.