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Matthew Klopfenstein
Matthew Klopfenstein

#85Matthew Klopfenstein

Matthew Klopfenstein is a Slot Specialist TE for Baylor.

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 Matthew Klopfenstein'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
8 Receptions73 Rec yards1 Rec TD9.1 Yards/rec

Performance Analysis · 2025 · vs TE peers

  • Efficiency100
  • Volume9
  • Explosiveness14
  • Consistency79
  • Pass-Down65
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 consistency79th %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.
  • 3 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Peak game: 1.31 EPA/play in Wk 5 vs Oklahoma State (SP+ -15).

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
Johnny LanganRutgers0.2400.08.9
Johnny LanganRutgers0.3000.017.7
Jordan MyersRice0.2700.215.9
Evan SvobodaWyoming0.2900.521.8
D'Vaughn PennamonOle Miss0.2000.011.0

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

Game Log · box score + EPA, week by week

+1.3101.31Wk 5 vs Oklahoma State: +1.31 EPA/play5Wk 10 vs UCF: +0.50 EPA/play10Wk 12 vs Utah: +1.14 EPA/play12Wk 14 vs Houston: -0.01 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
3vsSamfordW42-7
5@Oklahoma StateW45-27-15.13248.01111.31
10vsUCFW30-3-1.2177.0070.50
12vsUtahL28-5522.211111.00111.14
14vsHoustonL24-317.433110.3020-0.01

Usage & Situational · Pro

Snap-share proxy
Overall
3.2%
Passing plays
5.7%
Rushing plays
0.0%
Standard downs
2.6%
Passing downs
4.5%
EPA by down type
Standard downs
0.27
Passing downs
0.36
Pass / Rush EPA
0.30 / —

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.