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Luke Lindenmeyer
Luke Lindenmeyer

#44Luke Lindenmeyer

Luke Lindenmeyer is a Slot Specialist TE for Nebraska. Luke's 2025 season produced 20.2 total EPA across 38 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 Luke Lindenmeyer'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
29 Receptions312 Rec yards2 Rec TD10.8 Yards/rec

Performance Analysis · 2025 · vs TE peers

  • Efficiency100
  • Volume14
  • Explosiveness25
  • Consistency70
  • Pass-Down100
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 consistency70th %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.
  • 5 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 0.18 from the first to second half of the season.
  • Peak game: 2.13 EPA/play in Wk 9 vs Northwestern (SP+ 6).

NIL Market Tier· 2025

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

+2.1302.13Wk 1 vs Cincinnati: +0.73 EPA/play1Wk 2 vs Akron: +1.94 EPA/play2Wk 3 vs Houston Christian: +0.10 EPA/play3Wk 4 vs Michigan: -0.01 EPA/play4Wk 6 vs Michigan State: +0.25 EPA/play6Wk 7 vs Maryland: +1.25 EPA/play7Wk 8 vs Minnesota: +0.72 EPA/play8Wk 9 vs Northwestern: +2.13 EPA/play9Wk 10 vs USC: -0.04 EPA/play10Wk 14 vs Iowa: +0.33 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsCincinnatiW20-174.55479.40190.73
2vsAkronW68-0-13.934414.71221.94
3vsHouston ChristianW59-7199.0090.10
4vsMichiganL27-3012.47608.6023-0.01
6vsMichigan StateW38-27-3.4166.0060.25
7@MarylandW34-310.623015.01231.25
8@MinnesotaL6-241.545213.00260.72
9vsNorthwesternW28-215.811515.00152.13
10vsUSCL17-2116.922311.5023-0.04
14vsIowaL16-4019.722010.00130.33
20vsUtahL22-4422.2166.006

Usage & Situational · Pro

Snap-share proxy
Overall
5.0%
Passing plays
9.9%
Rushing plays
0.0%
Standard downs
3.9%
Passing downs
7.9%
EPA by down type
Standard downs
0.12
Passing downs
1.17
Pass / Rush EPA
0.53 / —

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.