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Will Howard

#18Will Howard

Will Howard is a Dual-Threat QB for Kansas State. Will's 2023 season ranks in the 0th percentile nationally by opponent-adjusted EPA per play across 427 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 Will Howard'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.

2023 Production

Passing
219/358 Comp/Att2643 Pass yards24 Pass TD10 INT61.2% Comp %
Rushing
364 Rush yards9 Rush TD80 Carries4.5 Yards/carry

Performance Analysis · 2023 · vs QB peers

  • Efficiency0
  • Volume100
  • Dual-Threat100
  • Consistency83
  • Clutch56
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)0th %ile · below avg
Game-to-game consistency83th %ile · above 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 consistency — reliable floor each week.
  • 5 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Strong second-half surge — EPA/play improved 0.11 from the first to second half of the season.
  • Peak game: 0.79 EPA/play in Wk 8 vs TCU (SP+ 8).

NIL Market Tier· 2023

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.

Game Log · box score + EPA, week by week

+0.7900.79Wk 1 vs Southeast Missouri State: +0.68 EPA/play1Wk 2 vs Troy: +0.58 EPA/play2Wk 3 vs Missouri: +0.21 EPA/play3Wk 4 vs UCF: +0.38 EPA/play4Wk 6 vs Oklahoma State: -0.07 EPA/play6Wk 7 vs Texas Tech: +0.24 EPA/play7Wk 8 vs TCU: +0.79 EPA/play8Wk 9 vs Houston: +0.39 EPA/play9Wk 10 vs Texas: +0.35 EPA/play10Wk 11 vs Baylor: +0.47 EPA/play11Wk 12 vs Kansas: +0.45 EPA/play12Wk 13 vs Iowa State: +0.24 EPA/play13
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+C/ATTPass YdsPass TDINTQBRRush YdsRush TDEPA/play
1vsSoutheast Missouri StateW45-018/262972165.9510.68
2vsTroyW42-139.821/322503181.43320.58
3@MissouriL27-3019.325/392703165.02100.21
4vsUCFW44-313.427/422550181.06420.38
6@Oklahoma StateL21-296.715/341521342.41041-0.07
7@Texas TechW38-216.16/9860029.7000.24
8vsTCUW41-37.910/161543097.66200.79
9vsHoustonW41-0-7.815/171642094.82400.39
10@TexasL30-3323.226/423274157.4-1000.35
11vsBaylorW59-25-8.319/292353093.3-310.47
12@KansasW31-279.913/241652182.71810.45
13vsIowa StateL35-427.524/482881170.84610.24

Usage & Situational · Pro

Snap-share proxy
Overall
49.1%
Passing plays
90.9%
Rushing plays
13.7%
Standard downs
45.9%
Passing downs
57.1%
EPA by down type
Standard downs
0.34
Passing downs
0.42
Pass / Rush EPA
0.32 / 0.60

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

Career · rolling EPA, game by game

Per-game EPA5-game avg
+0.82+0.20
EPA per play · 2024 · 16 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.