Skip to content
Wondame Davis Jr.
Wondame Davis Jr.

#7Wondame Davis Jr.

WR·UTEP·2025

Wondame Davis Jr. is a Vertical Threat WR for UTEP. Wondame's 2025 season produced 17.8 total EPA across 42 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 Wondame Davis Jr.'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
25 Receptions604 Rec yards6 Rec TD24.2 Yards/rec
Returns
6 Kick returns61 KR yards0 KR TD

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume21
  • Explosiveness100
  • Consistency53
  • Pass-Down100
Player type
Vertical Threat WR

Elite deep receiver who stretches the field. Wins downfield, commands safety attention, and creates the threat that opens underneath routes.

Downfield threatYAC upsideCreates space for teammates
Peer percentiles
Opponent-adjusted EPA (WEPA/play)100th %ile · elite
Game-to-game consistency53th %ile · average
Key findings
  • Top-10% efficiency among WRs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • 4 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Production faded as the season progressed — 0.34 EPA/play decline from first to second half.
  • Peak game: 1.14 EPA/play in Wk 4 vs UL Monroe (SP+ -22).

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
Dane KinamonAir Force0.4100.716.0
Keytaon ThompsonVirginia0.3700.615.2
Micah DavisAir Force0.3700.616.3
JoJo NatsonUtah State0.3901.019.9
Savion WilliamsTCU0.4501.125.2

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

Game Log · box score + EPA, week by week

+1.1401.14Wk 4 vs UL Monroe: +1.14 EPA/play4Wk 5 vs Louisiana Tech: +1.11 EPA/play5Wk 7 vs Liberty: -0.12 EPA/play7Wk 10 vs Kennesaw State: -0.57 EPA/play10Wk 11 vs Jacksonville State: +0.89 EPA/play11Wk 12 vs Missouri State: -0.20 EPA/play12Wk 13 vs New Mexico State: +0.47 EPA/play13Wk 14 vs Delaware: +0.33 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
4vsUL MonroeL25-31-21.6611919.82441.14
5vsLouisiana TechL11-30-1.325829.01351.11
7vsLibertyL8-19-9.02168.0010-0.12
8vsSam HoustonW35-17-27.837926.3036
10@Kennesaw StateL20-33-5.42199.5012-0.57
11vsJacksonville StateL27-30-6.7516633.21750.89
12@Missouri StateL24-38-10.7188.008-0.20
13vsNew Mexico StateL31-34-15.512727.01270.47
14@DelawareL31-61-10.9311237.31680.33

Usage & Situational · Pro

Snap-share proxy
Overall
7.4%
Passing plays
13.4%
Rushing plays
0.0%
Standard downs
7.6%
Passing downs
6.9%
EPA by down type
Standard downs
0.23
Passing downs
0.82
Pass / Rush EPA
0.42 / —

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.