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Sterling Berkhalter
Sterling Berkhalter

#18Sterling Berkhalter

Sterling Berkhalter is a Slot Specialist WR for Wake Forest. Sterling's 2025 season produced 25.5 total EPA across 49 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 Sterling Berkhalter'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
30 Receptions416 Rec yards2 Rec TD13.9 Yards/rec

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume16
  • Explosiveness46
  • Consistency57
  • Pass-Down100
Player type
Slot Specialist WR

The offense's primary passing-down weapon — routes, separation, and reliability on 3rd down define this role.

3rd-down converterRoute technicianHigh passing-down share
Peer percentiles
Opponent-adjusted EPA (WEPA/play)100th %ile · elite
Game-to-game consistency57th %ile · average
Key findings
  • Top-10% efficiency among WRs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • 5 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 — 1.01 EPA/play decline from first to second half.
  • Peak game: 3.71 EPA/play in Wk 2 vs Western Carolina.

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
Savion WilliamsTCU0.4501.125.2
DeAndre HughesAir Force0.4701.328.2
Keytaon ThompsonMississippi State0.4601.232.2
Dane KinamonAir Force0.4100.716.0
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

+3.7103.71Wk 1 vs Kennesaw State: +1.50 EPA/play1Wk 2 vs Western Carolina: +3.71 EPA/play2Wk 3 vs NC State: +0.17 EPA/play3Wk 5 vs Georgia Tech: +1.00 EPA/play5Wk 7 vs Oregon State: +0.64 EPA/play7Wk 9 vs SMU: +0.27 EPA/play9Wk 10 vs Florida State: +0.08 EPA/play10Wk 11 vs Virginia: -0.51 EPA/play11Wk 12 vs North Carolina: +0.10 EPA/play12Wk 13 vs Delaware: +1.18 EPA/play13Wk 14 vs Duke: +0.15 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsKennesaw StateW10-9-5.433411.30181.50
2vsWestern CarolinaW42-1027236.01513.71
3vsNC StateL24-344.834314.30260.17
5vsGeorgia TechL29-309.325025.00391.00
7@Oregon StateW39-14-15.93268.70110.64
9vsSMUW13-1213.455811.60220.27
10@Florida StateL7-427.211313.00130.08
11@VirginiaW16-911.1199.009-0.51
12vsNorth CarolinaW28-12-6.62199.50130.10
13vsDelawareW52-14-10.924221.01231.18
14@DukeL32-496.611616.00160.15
20vsMississippi StateW43-294.15346.8015

Usage & Situational · Pro

Snap-share proxy
Overall
5.7%
Passing plays
11.9%
Rushing plays
0.0%
Standard downs
3.5%
Passing downs
10.1%
EPA by down type
Standard downs
0.08
Passing downs
0.82
Pass / Rush EPA
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.