Skip to content
Dillon Hipp

#85Dillon Hipp

Dillon Hipp is a Versatile TE for Missouri 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 Dillon Hipp'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
3 Receptions17 Rec yards0 Rec TD5.7 Yards/rec

Performance Analysis · 2025 · vs TE peers

  • Efficiency100
  • Volume5
  • Explosiveness0
  • Consistency0
  • Pass-Down50
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)100th %ile · elite
Game-to-game consistency0th %ile · below avg
Key findings
  • Top-10% efficiency among TEs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • High game-to-game variance — boom-or-bust profile.
  • Peak game: 0.60 EPA/play in Wk 5 vs Western Kentucky (SP+ 2).

NIL Market Tier· 2025

On3 valuation ↗
Starter

Meaningful starter. Local collective + position-group 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
Kaden FeaginIllinois0.1500.07.8
Johnny LanganRutgers0.2400.08.9
D'Vaughn PennamonOle Miss0.2000.011.0
Robby PreckelNorthwestern0.0600.12.5
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

+0.8100.81Wk 1 vs USC: -0.81 EPA/play1Wk 5 vs Western Kentucky: +0.60 EPA/play5Wk 14 vs Louisiana Tech: +0.16 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1@USCL13-7316.9111.001-0.81
5vsWestern KentuckyL22-271.6188.0080.60
14vsLouisiana TechL30-42-1.3188.0080.16

Usage & Situational · Pro

Snap-share proxy
Overall
1.9%
Passing plays
3.4%
Rushing plays
0.0%
Standard downs
3.0%
Passing downs
0.0%
EPA by down type
Standard downs
0.15
Passing downs
Pass / Rush EPA
0.15 / —

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.