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Kevin Hogan

#8Kevin Hogan

QB·Stanford·201520146.3 pts line valueDay 3 (Rds 4–7)

Kevin Hogan is a 2-year Dual-Threat QB for Stanford. Kevin's 2014 season ranks in the 30th percentile nationally by opponent-adjusted EPA per play across 411 plays — a developing rate for the QB.

What projects, and what doesn't · QBs · 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)0.46
    Beats guessing the QB average by 16%. n=2,421 QB seasons
  • EPA per play (efficiency)0.05
    Not projectable — we do not forecast this. n=1,965 QB seasons
  • Total EPA (value)0.51
    Beats guessing the QB average by 20%. n=1,965 QB seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Kevin Hogan'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.

2014 Production

Passing
232/352 Comp/Att2792 Pass yards19 Pass TD8 INT65.9% Comp %
Rushing
295 Rush yards5 Rush TD91 Carries3.2 Yards/carry

Performance Analysis · 2014 · vs QB peers

  • Efficiency30
  • Volume100
  • Dual-Threat52
  • Consistency39
  • Clutch77
Player type
Dual-Threat QB

A genuine rushing threat who stresses defenses horizontally. Extends plays with legs and forces extra gap assignments.

Rushing threatScrambles for valueStresses defensive structure
Peer percentiles
Opponent-adjusted EPA (WEPA/play)30th %ile · below avg
Game-to-game consistency39th %ile · below avg
Key findings
  • Below-average efficiency vs QB peers — value comes through volume, not per-play impact.
  • High-volume role — one of the team's most-used QBs by play share.
  • High game-to-game variance — boom-or-bust profile.
  • 6 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 0.40 from the first to second half of the season.
  • Peak game: 0.88 EPA/play in Wk 14 vs UCLA (SP+ 18).

Game Log · box score + EPA, week by week

+1.0701.07Wk 1 vs UC Davis: -1.07 EPA/play1Wk 2 vs USC: +0.27 EPA/play2Wk 3 vs Army: +0.53 EPA/play3Wk 5 vs Washington: +0.15 EPA/play5Wk 6 vs Notre Dame: -0.05 EPA/play6Wk 7 vs Washington State: +0.42 EPA/play7Wk 8 vs Arizona State: +0.12 EPA/play8Wk 9 vs Oregon State: +0.61 EPA/play9Wk 10 vs Oregon: +0.15 EPA/play10Wk 12 vs Utah: -0.17 EPA/play12Wk 13 vs California: +0.66 EPA/play13Wk 14 vs UCLA: +0.88 EPA/play14Wk 1 vs Maryland: +0.52 EPA/play1
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+C/ATTPass YdsPass TDINTQBRRush YdsRush TDEPA/play
1vsUC DavisW45-012/162043183.9-11-1.07
2vsUSCL10-1317.122/302850051.82400.27
3vsArmyW35-0-16.920/282164085.71100.53
5@WashingtonW20-137.817/261781126.35310.15
6@Notre DameL14-1710.818/361580219.6-161-0.05
7vsWashington StateW34-17-1.723/352843057.7-400.42
8@Arizona StateL10-2613.519/392120039.71700.12
9vsOregon StateW38-143.218/272772286.33910.61
10@OregonL16-4524.721/292370164.34200.15
12vsUtahL17-208.817/271042024.7-120-0.17
13@CaliforniaW38-17-0.615/202140195.94610.66
14@UCLAW31-1017.716/192342098.34600.88
1vsMarylandW45-215.714/201892090.05000.52

Usage & Situational · Pro

Snap-share proxy
Overall
51.0%
Passing plays
93.1%
Rushing plays
16.5%
Standard downs
45.9%
Passing downs
61.8%
EPA by down type
Standard downs
0.22
Passing downs
0.41
Pass / Rush EPA
0.32 / 0.16

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

Career · rolling EPA, game by game

Per-game EPA5-game avg
+1.160−1.272015
EPA per play · 2014 — 2015 · 27 games
SeasonTeamLine valueTotal EPA
2014Stanford
6.3
188.7
2015Stanford
11.6
266.1

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.