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Dakota Twitty

#9Dakota Twitty

Dakota Twitty is a Slot Specialist TE for Virginia.

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 Dakota Twitty'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
11 Receptions129 Rec yards0 Rec TD11.7 Yards/rec

Performance Analysis · 2025 · vs TE peers

  • Efficiency100
  • Volume13
  • Explosiveness32
  • Consistency72
  • Pass-Down17
Player type
Slot Specialist TE

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)100th %ile · elite
Game-to-game consistency72th %ile · average
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 consistency — reliable floor each week.
  • 3 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Peak game: 1.22 EPA/play in Wk 3 vs William & Mary.

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
Johnny LanganRutgers0.3000.017.7
Jordan MyersRice0.2700.215.9
Johnny LanganRutgers0.2400.08.9
Seth GreenMinnesota0.3900.032.4

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

Game Log · box score + EPA, week by week

+1.2201.22Wk 1 vs Coastal Carolina: -0.14 EPA/play1Wk 2 vs NC State: +0.64 EPA/play2Wk 3 vs William & Mary: +1.22 EPA/play3Wk 4 vs Stanford: +0.74 EPA/play4Wk 5 vs Florida State: +0.12 EPA/play5
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsCoastal CarolinaW48-7-15.12157.508-0.14
2@NC StateL31-354.811212.00120.64
3vsWilliam & MaryW55-1612626.00261.22
4vsStanfordW48-20-11.824723.50260.74
5vsFlorida StateW46-387.25295.8080.12

Usage & Situational · Pro

Snap-share proxy
Overall
4.5%
Passing plays
9.9%
Rushing plays
0.0%
Standard downs
3.5%
Passing downs
7.1%
EPA by down type
Standard downs
0.44
Passing downs
0.25
Pass / Rush EPA
0.36 / —

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.