Stanford

Profile vs. FBS, 2025

Farther out is better on every spoke. Dashed ring: the FBS median.

• EPA per play

  Expected points added on an average snap: how much each play moved the scoring odds.
  Offense0.0011th
  Defense+0.1530th
• Success rate

  Share of snaps that stayed on schedule: half the yards needed on 1st down, 70% on 2nd, all of them on 3rd or 4th.
  Offense36.3%7th
  Defense42.5%41st
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2029th
  Defense+1.2930th
• Rushing EPA

  EPA per designed run.
  Offense−0.058th
  Defense−0.0587th
• Passing EPA

  EPA per pass play.
  Offense+0.1230th
  Defense+0.3214th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense42.0%7th
  Defense46.9%50th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense24.6%10th
  Defense33.6%14th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.6311th
  Defense2.8850th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense18.4%54th
  Defense17.5%34th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense17.2%23rd
  Defense14.6%30th

Percentiles among the 136 FBS teams this season, where higher is better for the offense and the defense alike (a defense's numbers are what it allowed). The line in each bar is the FBS median. Garbage time excluded. Source: CollegeFootballData.

Drives vs. expectation, 2025

Every snap has an expected-points value: what a drive from that spot, down and distance is worth on average. A drive over expected beat its starting spot; defense counts what Stanford allowed, so lower is better. The adjusted number fits every team against the opponents it actually played, so it leans toward average early in a season. Ranks are among FBS teams.

Game by game

1. L
   HAW
2. L
   BYU
3. W
   BC
4. L
   UVA
5. W
   SJSU
6. L
   SMU
7. W
   FSU
8. L
   MIA
9. L
   PITT
10. L
    UNC
11. W
    CAL
12. L
    ND

Bars above the line: better than expected for Stanford.

Players, 2025

1. Ben GulbransonQB222 plays · +0.148 pts/play · 120th of 231 QBs
   0.62WAR0.17 to 1.05
2. Micah FordRB128 plays · +0.100 pts/play · 83rd of 365 RBs
   0.24WAR0.16 to 0.31
3. C.J. WilliamsWR69 plays · +0.126 pts/play · 102nd of 451 WRs
   0.16WAR0.04 to 0.29
4. Cole TabbRB86 plays · +0.093 pts/play · 169th of 365 RBs
   0.15WAR0.10 to 0.20
5. Elijah BrownQB88 plays · +0.089 pts/play · 179th of 231 QBs
   0.15WAR−0.02 to 0.30
6. Aidan FlintoftP45 plays · +0.122 pts/play · 9th of 100 punters
   0.10WAR0.01 to 0.21
7. Bryce FarrellWR33 plays · +0.154 pts/play · 199th of 451 WRs
   0.10WAR0.04 to 0.17
8. Emmet KenneyPK17 plays · +0.270 pts/play · 52nd of 112 kickers
   0.09WAR0.04 to 0.13

By position group, against FBS

Linemen and defenders are valued as units, in points per game against the median FBS unit, because play-by-play doesn't say who was on the field. Players are valued against a replacement-level backup, so the two aren't added together.

Wins above replacement credits each play's expected points to the players involved, adjusted for the opponent, and compares Stanford's players with a typical backup; 53 points make a win. Only snaps while the game was in doubt count, so a starter on a team that blows opponents out plays fewer of them: read value per play beside WAR. The line under each player (or the range on a phone) is the 90% interval. Ranks are among FBS teams and players. How this works

What it had and what it did, 2025

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  70770746th of 134Roster talent: 707, 46th of 134 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  21121132nd of 134Recruiting: 211, 32nd of 134 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  19%19%98th of 132Returning production: 19%, 98th of 132 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −11.8−11.8110th of 134SP+ rating: −11.8, 110th of 134 in FBS

Ranks and bars among the 134 FBS teams with a talent rating this season, best first; the line in each bar is the FBS median.

Talent conversion

Conversion by season

Fourth-down calls vs. the numbers, 2025

Each real fourth down is valued three ways (go for it, kick, punt) from the score, clock and field position before the snap, using league-wide odds rather than Stanford's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 4 clear-cut ones account for 0.12 of the 0.15 expected wins. The model sees the situation, not the injury report, so a call it disagrees with can still be right. Ranks are among FBS teams; 1st gave up the least.

Costliest calls against the numbers

1. at UNCQ4 0:01 4th & 16 at STAN 26, up 3Went for it; the numbers favored punting−7.7 pts
2. vs CALQ3 8:04 4th & 2 at STAN 40, up 4Punted; the numbers favored going for it−1.5 pts
3. vs SJSUQ2 0:16 4th & 10 at SJSU 41, down 6Punted; the numbers favored a field goal−1.2 pts
4. vs PITTQ3 3:24 4th & 9 at STAN 43, down 12Went for it; the numbers favored punting−1.1 pts
5. vs SJSUQ2 10:26 4th & 2 at STAN 39, down 3Punted; the numbers favored going for it (close call)−0.8 pts
6. vs FSUQ2 6:45 4th & 2 at STAN 38, up 7Punted; the numbers favored going for it (close call)−0.7 pts
7. vs BCQ3 11:12 4th & 3 at STAN 37, tiedPunted; the numbers favored going for it (close call)−0.6 pts
8. at UNCQ2 6:11 4th & 3 at UNC 23, down 3Kicked a field goal; the numbers favored going for it (close call)−0.6 pts

Record vs. expectation, 2025

31st of 136 FBS teams at beating the model's pregame expectations

Expected wins adds up Stanford's chance of winning each game as the model saw it at kickoff - a 70% favorite counts 0.7.

1. L

   HAW
2. L

   BYU
3. W

   BC
4. L

   UVA
5. W

   SJSU
6. L

   SMU
7. W

   FSU
8. L

   MIA
9. L

   PITT
10. L

    UNC
11. W

    CAL
12. L

    ND

What moved it, 2025

Every game starts at Stanford's pregame chance; everything after that is the field. The model's own breakdown of each game's final play splits the on-field part by what drove it, and the parts add up exactly. How it works →

• Scoreboard+1.51
• Possession & field position−0.05
• Clock+0.05
• Timeouts+0.15
• Less the pregame edge, counted before kickoff+1.21

Game by game

• HAWL 20-23 at HAW48% → 100%Before kickoff −2 · On the field +52: Scoreboard +39, Timeouts +14
• BYUL 3-27 at BYU8% → 0%Before kickoff −42 · On the field −8: Scoreboard −12
• BCW 30-20 vs BC16% → 99%Before kickoff −34 · On the field +83: Scoreboard +52, Timeouts +2
• UVAL 20-48 at UVA14% → 0%Before kickoff −36 · On the field −14: Scoreboard −17
• SJSUW 30-29 vs SJSU60% → 78%Before kickoff +10 · On the field +18: Scoreboard +11, Timeouts +2
• SMUL 10-34 at SMU10% → 0%Before kickoff −40 · On the field −9: Scoreboard −14
• FSUW 20-13 vs FSU12% → 77%Before kickoff −38 · On the field +65: Scoreboard +20, Timeouts −4
• MIAL 7-42 at MIA4% → 0%Before kickoff −46 · On the field −4: Scoreboard −6
• PITTL 20-35 vs PITT16% → 1%Before kickoff −34 · On the field −15: Scoreboard −25, Clock −1
• UNCL 15-20 at UNC29% → 92%Before kickoff −21 · On the field +63: Scoreboard +55, Clock +3
• CALW 31-10 vs CAL41% → 100%Before kickoff −9 · On the field +59: Scoreboard +53, Clock −2
• NDL 20-49 vs ND2% → 0%Before kickoff −48 · On the field −2: Scoreboard −5

Points of win probability, from Stanford's side.

Closest call

STAN 46-43 COLO (2023) - Stanford dropped to a 0.9% win probability before pulling it out.