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Darien Williams

#7Darien Williams

Darien Williams is a Slot Specialist WR for Syracuse.

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 Darien Williams'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

Receiving
9 Receptions112 Rec yards1 Rec TD12.4 Yards/rec

Air yards

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

6
Targets
6.8y
Avg depth
2.8y
After catch
67%
Catch rate

The ball travels 6.8 yards in the air on an average target 2.1 yards shorter than the median. Another 2.8 comes after the catch.

Where he is targeted

targets · completion rate · yards
deep
0
1
0% · 0y
0
short
3
100% · 6y
0
2
50% · 19y
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 · 2025 · vs WR peers

  • Efficiency0
  • Volume13
  • Explosiveness36
  • Consistency60
  • Pass-Down76
Player type
Slot Specialist WR

The offense's primary passing-down weapon — routes, separation, and reliability on 3rd down define this role.

3rd-down converterRoute technicianHigh passing-down share
Peer percentiles
Opponent-adjusted EPA (WEPA/play)0th %ile · below avg
Game-to-game consistency60th %ile · average
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.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Peak game: 2.19 EPA/play in Wk 3 vs Colgate.

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
Brandon ChatmanNavy0.2300.612.0

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

Game Log · box score + EPA, week by week

+2.1902.19Wk 3 vs Colgate: +2.19 EPA/play3Wk 11 vs Miami: +0.14 EPA/play11Wk 13 vs Notre Dame: +1.19 EPA/play13Wk 14 vs Boston College: -0.46 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
3vsColgateW66-2437224.01352.19
11@MiamiL10-3820.72136.5080.14
13@Notre DameL7-7024.422010.00161.19
14vsBoston CollegeL12-34-8.5273.505-0.46

Usage & Situational · Pro

Snap-share proxy
Overall
4.5%
Passing plays
9.5%
Rushing plays
0.6%
Standard downs
3.1%
Passing downs
7.6%
EPA by down type
Standard downs
-0.24
Passing downs
-0.09
Pass / Rush EPA
-0.06 / -1.07

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.