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 2025 class has been drafted — this board is the model’s pre-draft read, useful as a receipt against how the rookies actually landed.

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.

#PlayerPosCollegeDynasty scoreHow it's builtBustTierConsensus
1Cam WardQBMiami (FL)109.784.4 × 1.303%Elite9
2Tetairoa McMillanWRArizona93.484.9 × 1.107%Elite11
3Travis HunterWRColorado88.980.8 × 1.105%Elite1
4Jaxson DartQBMississippi85.465.7 × 1.304%Starter55
5Shedeur SandersQBColorado84.464.9 × 1.3014%Starter24
6Emeka EgbukaWROhio St.84.376.7 × 1.109%Starter21
7Luther BurdenWRMissouri84.076.4 × 1.100%Starter27
8Tyler WarrenTEPenn St.82.086.3 × 0.956%Elite7
9Ashton JeantyRBBoise St.80.995.2 × 0.85 × 1.0010%Elite3
10Jayden HigginsWRIowa St.75.568.6 × 1.103%Starter47
11Jaylin NoelWRIowa St.74.767.9 × 1.1016%Starter56
12Kyle WilliamsWRWashington St.74.467.6 × 1.1021%Starter98
13Colston LovelandTEMichigan74.178.0 × 0.955%Elite13
14TreVeyon HendersonRBOhio St.73.688.9 × 0.85 × 0.9714%Starter41
15Jalen RoyalsWRUtah St.73.566.8 × 1.1027%Starter84
16Omarion HamptonRBNorth Carolina70.683.5 × 0.85 × 0.9913%Starter28
17Tre HarrisWRMississippi70.464.0 × 1.100%Starter65
18Mason TaylorTELSU69.673.3 × 0.9521%Starter50
19Matthew GoldenWRTexas68.962.6 × 1.100%Starter25
20Elic AyomanorWRStanford67.961.7 × 1.1013%Starter81
21Jalen MilroeQBAlabama65.850.6 × 1.3022%Starter64
22Tory HortonWRColorado St.65.259.3 × 1.1018%Starter110
23Harold FanninTEBowling Green62.966.2 × 0.955%Starter97
24Tai FeltonWRMaryland61.555.9 × 1.1021%Starter112
25Dylan SampsonRBTennessee60.871.6 × 0.85 × 1.0014%Starter123
26Quinshon JudkinsRBOhio St.60.771.4 × 0.85 × 1.0011%Starter53
27Jack BechWRTCU58.453.1 × 1.109%Starter66
28Tyler ShoughQBLouisville58.044.6 × 1.3027%Starter103
29Savion WilliamsWRTCU57.952.7 × 1.1026%Starter165
30Jaylin LaneWRVirginia Tech56.851.7 × 1.1017%Starter42
31Pat BryantWRIllinois55.550.5 × 1.1021%Starter156
32Elijah ArroyoTEMiami (FL)52.355.1 × 0.9523%Starter59
33Junior BergenWRMontana51.046.4 × 1.1024%Elite
34Bhayshul TutenRBVirginia Tech50.059.4 × 0.85 × 0.9924%Starter111
35Kaleb JohnsonRBIowa49.558.3 × 0.85 × 1.0016%Starter61
36Quinn EwersQBTexas48.837.6 × 1.3038%Starter131
37Chimere DikeWRFlorida48.844.4 × 1.1025%Starter
38Terrance FergusonTEOregon47.049.5 × 0.9525%Starter107
39Kyle McCordQBSyracuse46.836.0 × 1.3035%Starter94
40Devin NealRBKansas44.952.9 × 0.85 × 1.0017%Starter147
41Cam SkatteboRBArizona St.44.956.2 × 0.85 × 0.9416%Starter150
42Tez JohnsonWROregon44.740.6 × 1.108%Starter159
43Damien MartinezRBMiami (FL)44.151.9 × 0.85 × 1.0019%Starter168
44DJ GiddensRBKansas St.44.051.8 × 0.85 × 1.0025%Starter71
45Jordan JamesRBOregon43.851.5 × 0.85 × 1.0022%Starter137
46Jaydon BlueRBTexas42.249.7 × 0.85 × 1.0059%Starter153
47RJ HarveyRBCentral Florida41.855.4 × 0.85 × 0.8914%Starter124
48LeQuint AllenRBSyracuse38.345.1 × 0.85 × 1.0063%Starter117
49Will HowardQBOhio St.38.229.4 × 1.3031%Starter83
50Brashard SmithRBSMU37.744.5 × 0.85 × 1.0050%Role player
51Cam MillerQBNorth Dakota St.36.528.0 × 1.3030%Starter164
52Riley LeonardQBNotre Dame36.428.0 × 1.3032%
53Dillon GabrielQBOregon33.826.0 × 1.3027%
54Gunnar HelmTETexas32.133.8 × 0.9532%Starter85
55Trevor EtienneRBGeorgia32.037.6 × 0.85 × 1.0026%Starter162
56Jordan WatkinsWRMississippi31.929.0 × 1.1018%Elite
57Mitchell EvansTENotre Dame31.933.6 × 0.9525%Starter152
58Graham MertzQBFlorida30.723.6 × 1.3036%
59Dominic LovettWRGeorgia30.227.4 × 1.1023%Starter
60Tommy MellottQBMontana St.29.222.5 × 1.3028%
61Caleb LohnerTEUtah28.930.4 × 0.9529%Starter
62LaJohntay WesterWRColorado28.425.8 × 1.1026%Elite
63Ricky WhiteWRUNLV28.325.8 × 1.1025%Starter
64Jimmy HornWRColorado28.125.6 × 1.1027%Elite
65Dont'e ThorntonWRTennessee28.125.6 × 1.107%Elite
66Moliki MatavaoTEUCLA28.029.4 × 0.9538%Starter
67Jackson HawesTEGeorgia Tech27.929.4 × 0.9527%Starter
68Kurtis RourkeQBIndiana27.721.3 × 1.3024%
69Konata MumpfieldWRPittsburgh27.525.0 × 1.1023%Elite
70Arian SmithWRGeorgia26.724.2 × 1.1021%Starter
71Isaac TeSlaaWRArkansas26.624.2 × 1.1018%Starter154
72Oronde Gadsden IITESyracuse26.427.8 × 0.9519%Starter133
73Woody MarksRBUSC26.134.8 × 0.85 × 0.8820%Starter
74Phil MafahRBClemson25.030.1 × 0.85 × 0.9716%Starter
75Luke LacheyTEIowa24.926.2 × 0.9534%Starter
76Jarquez HunterRBAuburn24.729.6 × 0.85 × 0.9866%Starter60
77Thomas FidoneTENebraska24.325.5 × 0.9535%Starter
78KeAndre Lambert-SmithWRAuburn23.921.7 × 1.1018%Starter
79Ollie GordonRBOklahoma St.23.928.1 × 0.85 × 1.0065%Starter82
80Kalel MullingsRBMichigan22.427.1 × 0.85 × 0.9724%Starter
81Kyle MonangaiRBRutgers22.327.4 × 0.85 × 0.9622%Role player
82Gavin BartholomewTEPittsburgh21.522.7 × 0.9513%Starter
83Tahj BrooksRBTexas Tech20.625.5 × 0.85 × 0.9514%Starter
84Jacory Croskey-MerrittRBArizona16.121.1 × 0.85 × 0.9011%Elite
85Robbie OuztsTEAlabama10.410.9 × 0.9532%Starter

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.