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Will Anciaux

#80Will Anciaux

Will Anciaux is a Versatile TE for Kansas State.

What projects, and what doesn't · TEs · 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)0.42
    Beats guessing the TE average by 9%. n=2,225 TE seasons
  • EPA per play (efficiency)0.04
    Not projectable — we do not forecast this. n=2,016 TE seasons
  • Total EPA (value)0.46
    Beats guessing the TE average by 13%. n=2,016 TE seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Will Anciaux'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
6 Receptions45 Rec yards1 Rec TD7.5 Yards/rec
Returns
1 Kick returns9 KR yards0 KR TD

Performance Analysis · 2025 · vs TE peers

  • Efficiency0
  • Volume6
  • Explosiveness3
  • Consistency67
  • Pass-Down100
Player type
Versatile TE

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 consistency67th %ile · average
Key findings
  • Below-average efficiency vs TE 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: 1.46 EPA/play in Wk 5 vs UCF (SP+ -1).

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 · TE · 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
Robby PreckelNorthwestern0.0600.12.5
A.J. DoyleMassachusetts0.0400.02.1
Blake BellOklahoma0.0700.14.4
Kaden FeaginIllinois0.1500.07.8
Jaheim BellSouth Carolina0.1100.08.0

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

Game Log · box score + EPA, week by week

+1.4601.46Wk 5 vs UCF: +1.46 EPA/play5Wk 6 vs Baylor: +0.65 EPA/play6Wk 10 vs Texas Tech: -0.03 EPA/play10Wk 14 vs Colorado: +0.08 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
0vsIowa StateL21-249.9111.001
5vsUCFW34-20-1.2133.0131.46
6@BaylorL34-351.422814.00250.65
10vsTexas TechL20-4327.6144.004-0.03
14vsColoradoW24-14-8.3199.0090.08

Usage & Situational · Pro

Snap-share proxy
Overall
2.1%
Passing plays
4.7%
Rushing plays
0.0%
Standard downs
1.8%
Passing downs
2.8%
EPA by down type
Standard downs
-0.26
Passing downs
0.38
Pass / Rush EPA
0.03 / —

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.