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Hunter Tipton

#0Hunter Tipton

Hunter Tipton is a Versatile TE for Middle Tennessee. Hunter's 2025 season produced 19.1 total EPA across 47 plays.

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 Hunter Tipton'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
39 Receptions411 Rec yards2 Rec TD10.5 Yards/rec

Performance Analysis · 2025 · vs TE peers

  • Efficiency100
  • Volume17
  • Explosiveness24
  • Consistency62
  • Pass-Down97
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 consistency62th %ile · average
Key findings
  • Top-10% efficiency among TEs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • 7 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Strong second-half surge — EPA/play improved 0.58 from the first to second half of the season.
  • Peak game: 1.61 EPA/play in Wk 10 vs Jacksonville State (SP+ -7).

NIL Market Tier· 2025

On3 valuation ↗
Star

Top-10 nationally. Multiple mid-to-large collective deals expected.

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
Ty ThompsonTulane0.4200.720.2
Seth GreenMinnesota0.3900.032.4
Johnny LanganRutgers0.3000.017.7
Evan SvobodaWyoming0.2900.521.8
Jordan MyersRice0.2700.215.9

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

Game Log · box score + EPA, week by week

+1.6101.61Wk 1 vs Austin Peay: -0.28 EPA/play1Wk 2 vs Wisconsin: +0.61 EPA/play2Wk 3 vs Nevada: -0.89 EPA/play3Wk 4 vs Marshall: +1.38 EPA/play4Wk 5 vs Kennesaw State: +0.83 EPA/play5Wk 7 vs Missouri State: -0.14 EPA/play7Wk 9 vs Delaware: +0.93 EPA/play9Wk 10 vs Jacksonville State: +1.61 EPA/play10Wk 11 vs Florida International: +0.77 EPA/play11Wk 12 vs Western Kentucky: +1.13 EPA/play12Wk 13 vs Sam Houston: +0.25 EPA/play13Wk 14 vs New Mexico State: +0.31 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsAustin PeayL14-34166.006-0.28
2@WisconsinL10-42-4.43227.31120.61
3@NevadaW14-13-13.422010.0014-0.89
4vsMarshallL28-42-4.511212.00121.38
5@Kennesaw StateL16-24-5.434515.00210.83
7vsMissouri StateL20-22-10.77547.7012-0.14
9@DelawareL28-31-10.955611.21170.93
10vsJacksonville StateL21-24-6.755611.20281.61
11vsFlorida InternationalL30-56-10.522412.00180.77
12@Western KentuckyL26-421.646817.00371.13
13vsSam HoustonW31-17-27.82157.50110.25
14@New Mexico StateW31-24-15.54338.30200.31

Usage & Situational · Pro

Snap-share proxy
Overall
6.0%
Passing plays
9.5%
Rushing plays
0.0%
Standard downs
5.5%
Passing downs
7.0%
EPA by down type
Standard downs
0.30
Passing downs
0.58
Pass / Rush EPA
0.41 / —

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.