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Cameron Flowers

#4Cameron Flowers

Cameron Flowers is a Versatile WR for Western Kentucky. Cameron's 2025 season produced 9.7 total EPA across 38 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 Cameron Flowers'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
19 Receptions204 Rec yards1 Rec TD10.7 Yards/rec
Returns
10 Kick returns162 KR yards0 KR TD

Air yards

Where the ball goes, and how much of the gain is the throw rather than the run after it.

11
Targets
8.8y
Avg depth
2.1y
After catch
64%
Catch rate

The ball travels 8.8 yards in the air on an average target about the median for the position. Another 2.1 comes after the catch.

Where he is targeted

targets · completion rate · yards
deep
0
0
1
0% · 0y
short
1
0% · 0y
1
100% · 0y
8
75% · 60y
leftmiddleright

Depth and direction come from CFBD’s passing detail, which is backfilled after the games: this covers weeks 1–2 only. Spikes, throwaways and intentional grounding are excluded before any average.

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume12
  • Explosiveness25
  • Consistency27
  • Pass-Down45
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)100th %ile · elite
Game-to-game consistency27th %ile · below avg
Key findings
  • Top-10% efficiency among WRs — elite opponent-adjusted EPA rate.
  • 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.
  • Production faded as the season progressed — 0.58 EPA/play decline from first to second half.
  • Peak game: 2.07 EPA/play in Wk 2 vs Toledo (SP+ 6).

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 · 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
Tyler BuchnerNotre Dame0.2500.312.8
Samajie GrantArizona0.2500.315.5
Justin LynchTemple0.2400.315.1
Brandon ChatmanNavy0.2300.612.0
Nick NashSan José State0.3100.514.0

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

Game Log · box score + EPA, week by week

+2.0702.07Wk 1 vs North Alabama: +0.11 EPA/play1Wk 2 vs Toledo: +2.07 EPA/play2Wk 4 vs Nevada: +1.09 EPA/play4Wk 5 vs Missouri State: +0.25 EPA/play5Wk 6 vs Delaware: +0.13 EPA/play6Wk 8 vs Florida International: +0.02 EPA/play8Wk 9 vs Louisiana Tech: +0.24 EPA/play9Wk 10 vs New Mexico State: +1.21 EPA/play10Wk 12 vs Middle Tennessee: -0.90 EPA/play12Wk 13 vs LSU: +0.62 EPA/play13Wk 14 vs Jacksonville State: -1.00 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsNorth AlabamaW55-622110.50200.11
2@ToledoL21-456.02189.01112.07
4vsNevadaW31-16-13.413030.00301.09
5@Missouri StateW27-22-10.733311.00260.25
6@DelawareW27-24-10.95377.40230.13
8vsFlorida InternationalL6-25-10.5231.5050.02
9@Louisiana TechW28-27-1.311717.00170.24
10vsNew Mexico StateW35-16-15.523316.50201.21
12vsMiddle TennesseeW42-26-16.0-0.90
13@LSUL10-1310.311212.00120.62
14@Jacksonville StateL34-37-6.7-1.00
20vsSouthern MissW27-16-7.1

Usage & Situational · Pro

Snap-share proxy
Overall
4.3%
Passing plays
7.1%
Rushing plays
0.8%
Standard downs
3.6%
Passing downs
5.7%
EPA by down type
Standard downs
0.27
Passing downs
0.24
Pass / Rush EPA
0.28 / -0.03

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.