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Messiah Burch

#4Messiah Burch

Messiah Burch is a Pass-Catching Back for Buffalo.

What projects, and what doesn't · RBs · 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)0.52
    Beats guessing the RB average by 18%. n=4,219 RB seasons
  • EPA per play (efficiency)0.10
    Not projectable — we do not forecast this. n=3,575 RB seasons
  • Total EPA (value)0.41
    Beats guessing the RB average by 9%. n=3,575 RB seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Messiah Burch'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

Rushing
41 Rush yards0 Rush TD11 Carries3.7 Yards/carry
Receiving
4 Receptions-1 Rec yards0 Rec TD-0.3 Yards/rec

Performance Analysis · 2025 · vs RB peers

  • Efficiency0
  • Volume12
  • Explosiveness14
  • Consistency58
  • Receiving100
Player type
Pass-Catching Back

Third-down weapon out of the backfield. Routes, hands, and separation in coverage define this role as much as rushing.

3rd-down backReceiving threatPass protection
Peer percentiles
Opponent-adjusted EPA (WEPA/play)0th %ile · below avg
Game-to-game consistency58th %ile · average
Key findings
  • Below-average efficiency vs RB peers — value comes through volume, not per-play impact.
  • Limited usage share suggests a rotational or specialist role.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Production faded as the season progressed — 0.51 EPA/play decline from first to second half.

NIL Market Tier· 2025

On3 valuation ↗
Contributor

Rotational contributor. Smaller collective or local 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.

Game Log · box score + EPA, week by week

+1.3401.34Wk 1 vs Minnesota: -0.50 EPA/play1Wk 2 vs St. Francis (PA): +0.09 EPA/play2Wk 3 vs Kent State: +0.07 EPA/play3Wk 4 vs Troy: +0.08 EPA/play4Wk 9 vs Akron: -1.34 EPA/play9Wk 14 vs Ohio: -0.62 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
1@MinnesotaL10-231.52-4-2.002-10-0.50
2vsSt. Francis (PA)W45-64399.801-200.09
3@Kent StateW31-28-19.3177.000.07
4vsTroyL17-21-4.8166.001200.08
9vsAkronL16-24-13.91-5-5.00-1.34
14vsOhioL26-31-4.02-2-1.00-0.62

Usage & Situational · Pro

Snap-share proxy
Overall
4.1%
Passing plays
2.8%
Rushing plays
5.3%
Standard downs
5.1%
Passing downs
1.7%
EPA by down type
Standard downs
-0.52
Passing downs
0.11
Pass / Rush EPA
-0.27 / -0.52

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.