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Micah Woods

#6Micah Woods

Micah Woods is a Versatile WR for South Alabama.

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 Micah Woods'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
11 Receptions113 Rec yards1 Rec TD10.3 Yards/rec
Returns
2 Kick returns38 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.

9
Targets
10.2y
Avg depth
3.8y
After catch
56%
Catch rate

The ball travels 10.2 yards in the air on an average target 1.3 yards deeper than the median. Another 3.8 comes after the catch.

Where he is targeted

targets · completion rate · yards
deep
0
1
0% · 0y
0
short
1
0% · 0y
4
50% · 23y
3
100% · 22y
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
  • Volume8
  • Explosiveness22
  • Consistency70
  • 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)100th %ile · elite
Game-to-game consistency70th %ile · average
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 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 0.42 from the first to second half of the season.
  • Peak game: 1.14 EPA/play in Wk 13 vs Southern Miss (SP+ -7).

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 · 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
Dane KinamonAir Force0.4100.716.0
Savion WilliamsTCU0.4501.125.2
DeAndre HughesAir Force0.4701.328.2
Javion PoseyFlorida Atlantic0.4501.423.8
Quadree HendersonPittsburgh0.5301.633.4

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

Game Log · box score + EPA, week by week

+1.1401.14Wk 5 vs North Texas: -0.47 EPA/play5Wk 6 vs Troy: +1.02 EPA/play6Wk 8 vs Arkansas State: +0.22 EPA/play8Wk 9 vs Georgia State: +0.76 EPA/play9Wk 10 vs Louisiana: +0.43 EPA/play10Wk 12 vs UL Monroe: +0.46 EPA/play12Wk 13 vs Southern Miss: +1.14 EPA/play13
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
5@North TexasL22-3613.8133.003-0.47
6@TroyL24-31-4.813333.01331.02
8vsArkansas StateL14-15-8.82126.0070.22
9@Georgia StateW38-31-24.511111.00110.76
10vsLouisianaL22-31-10.133110.30170.43
12@UL MonroeW26-14-21.62115.50100.46
13vsSouthern MissW42-35-7.111212.00121.14

Usage & Situational · Pro

Snap-share proxy
Overall
2.7%
Passing plays
6.8%
Rushing plays
0.3%
Standard downs
2.8%
Passing downs
2.4%
EPA by down type
Standard downs
0.33
Passing downs
1.02
Pass / Rush EPA
0.63 / -0.86

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.