Skip to content
Jerrod Heard

#13Jerrod Heard

WR·Texas·20151.6 pts line value1st Round

Jerrod Heard is a Possession Receiver WR for Texas. Jerrod's 2015 season ranks in the 63th percentile nationally by opponent-adjusted EPA per play across 292 plays — a average rate for the WR.

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 Jerrod Heard'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.

2015 Production

Passing
92/159 Comp/Att1214 Pass yards5 Pass TD5 INT57.9% Comp %
Rushing
556 Rush yards3 Rush TD139 Carries4.0 Yards/carry
Receiving
1 Receptions3 Rec yards0 Rec TD3.0 Yards/rec

Performance Analysis · 2015 · vs WR peers

  • Efficiency63
  • Volume100
  • Explosiveness0
  • Consistency20
  • Pass-Down89
Player type
Possession Receiver WR

Chain-mover who earns targets through reliability. High volume, short-to-intermediate routes, consistent floor every week.

High target shareChain moverReliable floor
Peer percentiles
Opponent-adjusted EPA (WEPA/play)63th %ile · average
Game-to-game consistency20th %ile · below avg
Key findings
  • High-volume role — one of the team's most-used WRs by play share.
  • High game-to-game variance — boom-or-bust profile.
  • 3 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 — 0.30 EPA/play decline from first to second half.
  • Peak game: 0.80 EPA/play in Wk 2 vs Rice (SP+ -15).

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
Zach AbeyNavy0.3702.9101.8
D.J. FosterArizona State0.2001.034.8
Shai WertsGeorgia Southern0.2101.932.1
Shai WertsGeorgia Southern0.3602.351.8
Shai WertsGeorgia Southern0.1500.024.2

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

Game Log · box score + EPA, week by week

+0.8000.80Wk 1 vs Notre Dame: +0.38 EPA/play1Wk 2 vs Rice: +0.80 EPA/play2Wk 3 vs California: +0.52 EPA/play3Wk 4 vs Oklahoma State: -0.10 EPA/play4Wk 5 vs TCU: -0.17 EPA/play5Wk 6 vs Oklahoma: +0.25 EPA/play6Wk 8 vs Kansas State: +0.09 EPA/play8Wk 9 vs Iowa State: -0.37 EPA/play9Wk 10 vs Kansas: +0.41 EPA/play10Wk 11 vs West Virginia: +0.06 EPA/play11Wk 13 vs Texas Tech: +0.15 EPA/play13Wk 14 vs Baylor: -0.44 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1@Notre DameL3-3822.40.38
2vsRiceW42-28-14.60.80
3vsCaliforniaL44-4512.10.52
4vsOklahoma StateL27-309.9-0.10
5@TCUL7-5019.0-0.17
6vsOklahomaW24-1722.70.25
8vsKansas StateW23-92.60.09
9@Iowa StateL0-24-0.3-0.37
10vsKansasW59-20-21.30.41
11@West VirginiaL20-3812.90.06
13vsTexas TechL45-484.5133.0030.15
14@BaylorW23-1719.5-0.44

Usage & Situational · Pro

Snap-share proxy
Overall
37.8%
Passing plays
66.2%
Rushing plays
22.7%
Standard downs
30.7%
Passing downs
50.3%
EPA by down type
Standard downs
0.07
Passing downs
0.30
Pass / Rush EPA
0.11 / 0.30

Usage = share of team plays (CFBD has no true snap counts).

Career · rolling EPA, game by game

Per-game EPA5-game avg
+0.920−0.56
EPA per play · 2015 · 12 games

Chart shows per-game EPA (bars) and rolling 5-game average (line). Season breaks marked with dashed lines. Line value = est. points over replacement per game.

EPA = expected points added (opponent-adjusted). NIL estimates are model-based ranges, not reported deals. Data: CollegeFootballData. Not betting advice.