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Drayden Dickmann
Drayden Dickmann

#18Drayden Dickmann

WR·Rice·2025

Drayden Dickmann is a Versatile WR for Rice. Drayden's 2025 season ranks in the 0th percentile nationally by opponent-adjusted EPA per play across 67 plays — a developing rate for the WR.

What projects, and what doesn't · WRs · held out 2019-2025

How well one season predicts the next, measured on seasons the model never trained on. 1.00 would be perfectly predictable; 0.00 means last year told us nothing.

  • Usage share (volume)0.47
    Beats guessing the WR average by 16%. n=6,302 WR seasons
  • EPA per play (efficiency)0.09
    Not projectable — we do not forecast this. n=5,767 WR seasons
  • Total EPA (value)0.45
    Beats guessing the WR average by 12%. n=5,767 WR seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Drayden Dickmann's projection is a projection of opportunity — how much of the offense he runs through. How well he converts it is something this model does not claim to know a year in advance, and the number above is why.

2025 Production

Rushing
-2 Rush yards0 Rush TD14 Carries-0.1 Yards/carry
Receiving
37 Receptions323 Rec yards3 Rec TD8.7 Yards/rec

Performance Analysis · 2025 · vs WR peers

  • Efficiency0
  • Volume26
  • Explosiveness12
  • Consistency0
  • Pass-Down22
Player type
Versatile WR

Balanced profile without a single dominant trait — contributes across multiple dimensions.

Balanced usageMulti-role
Peer percentiles
Opponent-adjusted EPA (WEPA/play)0th %ile · below avg
Game-to-game consistency0th %ile · below avg
Key findings
  • Below-average efficiency vs WR peers — value comes through volume, not per-play impact.
  • Limited usage share suggests a rotational or specialist role.
  • High game-to-game variance — boom-or-bust profile.
  • Production faded as the season progressed — 0.49 EPA/play decline from first to second half.
  • Peak game: 1.36 EPA/play in Wk 4 vs Charlotte (SP+ -27).

NIL Market Tier· 2025

On3 valuation ↗
Contributor

Rotational contributor. Smaller collective or local deals.

Tier is a model estimate based on position, school brand, performance rank, and usage — not a reported deal. NIL deals are private. For a real market valuation, see On3's NIL profile, which factors in social following and actual deal tracking.

Historical Comparables · WR · efficiency + volume + value

Players from 2013–2025 matched on EPA efficiency, play volume, and adjusted value tier — not just one metric.

PlayerTeamWEPA/playLine valTotal EPA
De'Michael HarrisSouthern Miss0.1300.715.2
Amare JonesTulane0.1800.012.8
Hyleck FosterMarshall0.1800.518.2
Davis BrysonKennesaw State0.2000.019.4
Shai WertsGeorgia Southern0.1500.024.2

Comps are statistical — efficiency, volume, and value tier all factor in. Style and conference context differ.

Game Log · box score + EPA, week by week

+1.3601.36Wk 1 vs Louisiana: +0.94 EPA/play1Wk 2 vs Houston: -0.72 EPA/play2Wk 3 vs Prairie View A&M: -0.28 EPA/play3Wk 4 vs Charlotte: +1.36 EPA/play4Wk 5 vs Navy: +0.08 EPA/play5Wk 6 vs Florida Atlantic: +0.04 EPA/play6Wk 7 vs UTSA: +0.16 EPA/play7Wk 9 vs UConn: +0.09 EPA/play9Wk 10 vs Memphis: -0.12 EPA/play10Wk 11 vs UAB: -1.03 EPA/play11Wk 13 vs North Texas: -0.10 EPA/play13Wk 14 vs South Florida: -0.53 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1@LouisianaW14-12-10.134414.70230.94
2vsHoustonL9-357.4482.005-0.72
3vsPrairie View A&MW38-174328.0011-0.28
4@CharlotteW28-17-26.74399.81121.36
5@NavyL13-216.234515.01360.08
6vsFlorida AtlanticL21-27-8.746115.31460.04
7@UTSAL13-613.723316.50330.16
9vsUConnW37-345.14307.50110.09
10vsMemphisL14-387.64133.309-0.12
11vsUABW24-17-15.81-3-3.000-1.03
13vsNorth TexasL24-5613.83175.7010-0.10
14@South FloridaL3-5211.6144.004-0.53

Usage & Situational · Pro

Snap-share proxy
Overall
9.1%
Passing plays
26.7%
Rushing plays
2.7%
Standard downs
8.3%
Passing downs
11.0%
EPA by down type
Standard downs
0.00
Passing downs
-0.16
Pass / Rush EPA
0.19 / -1.01

Usage = share of team plays (CFBD has no true snap counts).

EPA = expected points added (opponent-adjusted). NIL estimates are model-based ranges, not reported deals. Data: CollegeFootballData. Not betting advice.