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Dezmen Roebuck

#2Dezmen Roebuck

Dezmen Roebuck is a Versatile WR for Washington.

2026 Usage Outlook · projected share of team plays

7%
projected
band 4%'25 7%11%

Regressed toward the WR mean. Model correlation r≈0.47 on a 2019-2025 walk-forward — volume only; efficiency not projected.

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 Dezmen Roebuck'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.

2026 Production

Receiving
14 Receptions100 Rec yards0 Rec TD7.1 Yards/rec

Air yards

Where the ball goes, and how much of the gain is the throw rather than the run after it.

23
Targets
4.6y
Avg depth
7.0y
After catch
61%
Catch rate

The ball travels 4.6 yards in the air on an average target 4.3 yards shorter than the median. Another 7.0 comes after the catch.

Where he is targeted

targets · completion rate · yards
deep
0
0
1
0% · 0y
short
7
57% · 33y
5
60% · 30y
10
70% · 47y
leftmiddleright

Depth and direction come from CFBD’s passing detail, which is backfilled after the games: this covers weeks 1–2 only. Spikes, throwaways and intentional grounding are excluded before any average.

Performance Analysis · 2026 · vs WR peers

  • Efficiency0
  • Volume45
  • Explosiveness1
  • Consistency50
  • Pass-Down100
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
Key findings
  • Below-average efficiency vs WR peers — value comes through volume, not per-play impact.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.

NIL Market Tier· 2026

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
Amare JonesTulane0.1800.012.8
De'Michael HarrisSouthern Miss0.1300.715.2
Hyleck FosterMarshall0.1800.518.2
Brandon ChatmanNavy0.2300.612.0
Davis BrysonKennesaw State0.2000.019.4

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

Game Log · box score + EPA, week by week

+0.1300.13Wk 1 vs Washington State: -0.13 EPA/play1Wk 2 vs Utah State: +0.00 EPA/play2
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsWashington StateW24-10-3.77415.9014-0.13
2vsUtah StateW16-14-11.57598.40180.00

Usage & Situational · Pro

Snap-share proxy
Overall
15.6%
Passing plays
28.6%
Rushing plays
0.0%
Standard downs
14.3%
Passing downs
19.4%
EPA by down type
Standard downs
-0.17
Passing downs
0.18
Pass / Rush EPA
-0.06 / —

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.