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Tiger Bachmeier

#19Tiger Bachmeier

WR·BYU·2025

Tiger Bachmeier is a Slot Specialist WR for BYU.

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 Tiger Bachmeier'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
7 Receptions59 Rec yards0 Rec TD8.4 Yards/rec
Returns
1 Kick returns21 KR yards0 KR TD5 Punt returns48 PR yards0 PR TD

Performance Analysis · 2025 · vs WR peers

  • Efficiency0
  • Volume8
  • Explosiveness10
  • Consistency0
  • 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)0th %ile · below avg
Game-to-game consistency0th %ile · below avg
Key findings
  • Below-average efficiency vs WR peers — value comes through volume, not per-play impact.
  • Limited usage share suggests a rotational or specialist role.
  • High game-to-game variance — boom-or-bust profile.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Strong second-half surge — EPA/play improved 0.98 from the first to second half of the season.
  • Peak game: 2.09 EPA/play in Wk 14 vs UCF (SP+ -1).

NIL Market Tier· 2025

On3 valuation ↗
Contributor

Rotational contributor. Smaller collective or local 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
De'Michael HarrisSouthern Miss0.1300.715.2
Amare JonesTulane0.1800.012.8
Hyleck FosterMarshall0.1800.518.2
Davis BrysonKennesaw State0.2000.019.4
Brandon ChatmanNavy0.2300.612.0

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

Game Log · box score + EPA, week by week

+2.0902.09Wk 1 vs Portland State: +0.14 EPA/play1Wk 5 vs Colorado: -1.00 EPA/play5Wk 6 vs West Virginia: -0.06 EPA/play6Wk 9 vs Iowa State: +0.09 EPA/play9Wk 12 vs TCU: +0.08 EPA/play12Wk 14 vs UCF: +2.09 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsPortland StateW69-0188.0080.14
2vsStanfordW27-3-11.8
4@East CarolinaW34-138.0
5@ColoradoW24-21-8.3-1.00
6vsWest VirginiaW38-24-6.82157.5010-0.06
9@Iowa StateW41-279.922512.50170.09
12vsTCUW44-138.3155.0050.08
14vsUCFW41-21-1.2166.0062.09

Usage & Situational · Pro

Snap-share proxy
Overall
2.7%
Passing plays
6.2%
Rushing plays
0.3%
Standard downs
1.9%
Passing downs
4.7%
EPA by down type
Standard downs
-0.44
Passing downs
-0.01
Pass / Rush EPA
-0.19 / —

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.