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Luke Lachey

#85Luke Lachey

TE·Iowa·2024

Luke Lachey is a Versatile TE for Iowa.

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 Luke Lachey'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.

2024 Production

Receiving
28 Receptions231 Rec yards0 Rec TD8.3 Yards/rec

Performance Analysis · 2024 · vs TE peers

  • Efficiency100
  • Volume12
  • Explosiveness8
  • Consistency75
  • Pass-Down87
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 consistency75th %ile · above 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 consistency — reliable floor each week.
  • 6 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Peak game: 1.26 EPA/play in Wk 1 vs Illinois State.

NIL Market Tier· 2024

On3 valuation ↗
Elite

Top-3 player at position nationally. Collective + national brand 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
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

+1.2601.26Wk 1 vs Illinois State: +1.26 EPA/play1Wk 3 vs Troy: +0.64 EPA/play3Wk 4 vs Minnesota: -0.28 EPA/play4Wk 7 vs Washington: +0.60 EPA/play7Wk 8 vs Michigan State: +0.53 EPA/play8Wk 9 vs Northwestern: +0.67 EPA/play9Wk 13 vs Maryland: +0.93 EPA/play13Wk 14 vs Nebraska: +0.05 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsIllinois StateW40-066310.50191.26
3vsTroyW38-21-6.63258.30130.64
4@MinnesotaW31-1410.4393.006-0.28
6@Ohio StateL7-3531.25397.8013
7vsWashingtonW40-163.122010.00110.60
8@Michigan StateL20-32-4.623618.00280.53
9vsNorthwesternW40-14-8.23175.70100.67
13@MarylandW29-13-3.9199.0090.93
14vsNebraskaW13-105.5294.5070.05
20vsMissouriL24-2714.0144.004

Usage & Situational · Pro

Snap-share proxy
Overall
4.1%
Passing plays
11.6%
Rushing plays
0.0%
Standard downs
3.7%
Passing downs
5.4%
EPA by down type
Standard downs
0.53
Passing downs
0.75
Pass / Rush EPA
0.60 / —

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.