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Moussa Barry

#8Moussa Barry

Moussa Barry is a Versatile WR for Western Kentucky. Moussa's 2025 season produced 5.3 total EPA across 47 plays.

What projects, and what doesn't · WRs · 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)0.47
    Beats guessing the WR average by 16%. n=6,302 WR seasons
  • EPA per play (efficiency)0.09
    Not projectable — we do not forecast this. n=5,767 WR seasons
  • Total EPA (value)0.45
    Beats guessing the WR average by 12%. n=5,767 WR seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Moussa Barry'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
34 Receptions488 Rec yards1 Rec TD14.4 Yards/rec

Performance Analysis · 2025 · vs WR peers

  • Efficiency50
  • Volume17
  • Explosiveness49
  • Consistency0
  • Pass-Down100
Player type
Versatile WR

Balanced profile without a single dominant trait — contributes across multiple dimensions.

Balanced usageMulti-role
Peer percentiles
Opponent-adjusted EPA (WEPA/play)50th %ile · average
Game-to-game consistency0th %ile · below avg
Key findings
  • Limited usage share suggests a rotational or specialist role.
  • High game-to-game variance — boom-or-bust profile.
  • 4 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 0.68 from the first to second half of the season.
  • Peak game: 1.25 EPA/play in Wk 13 vs LSU (SP+ 10).

NIL Market Tier· 2025

On3 valuation ↗
Starter

Meaningful starter. Local collective + position-group 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 · WR · 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
Amare JonesTulane0.1800.012.8
Brandon ChatmanNavy0.2300.612.0
Eli HeidenreichNavy0.2200.815.4
Davis BrysonKennesaw State0.2000.019.4
Hyleck FosterMarshall0.1800.518.2

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

Game Log · box score + EPA, week by week

+1.2501.25Wk 1 vs North Alabama: -0.24 EPA/play1Wk 2 vs Toledo: -0.66 EPA/play2Wk 4 vs Nevada: -0.46 EPA/play4Wk 5 vs Missouri State: +0.25 EPA/play5Wk 8 vs Florida International: +0.62 EPA/play8Wk 9 vs Louisiana Tech: -0.72 EPA/play9Wk 10 vs New Mexico State: -0.23 EPA/play10Wk 12 vs Middle Tennessee: +0.64 EPA/play12Wk 13 vs LSU: +1.25 EPA/play13Wk 14 vs Jacksonville State: +1.09 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
0vsSam HoustonW41-24-27.869015.0048
1vsNorth AlabamaW55-62105.006-0.24
2@ToledoL21-456.0311036.7039-0.66
4vsNevadaW31-16-13.43124.006-0.46
5@Missouri StateW27-22-10.711313.00130.25
6@DelawareW27-24-10.911212.0012
8vsFlorida InternationalL6-25-10.52178.50110.62
9@Louisiana TechW28-27-1.311515.0015-0.72
10vsNew Mexico StateW35-16-15.55397.8121-0.23
12vsMiddle TennesseeW42-26-16.045213.00220.64
13@LSUL10-1310.311818.00181.25
14@Jacksonville StateL34-37-6.736822.70321.09
20vsSouthern MissW27-16-7.123216.0018

Usage & Situational · Pro

Snap-share proxy
Overall
5.8%
Passing plays
10.4%
Rushing plays
0.0%
Standard downs
5.3%
Passing downs
6.9%
EPA by down type
Standard downs
-0.11
Passing downs
0.48
Pass / Rush EPA
0.11 / —

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.