Stanford

Profile vs. FBS, 2019

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.
  Offense+0.1141st
  Defense+0.2016th
• 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.
  Offense43.0%45th
  Defense48.3%6th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.1633rd
  Defense+1.2151st
• Rushing EPA

  EPA per designed run.
  Offense+0.0231st
  Defense+0.1034th
• Passing EPA

  EPA per pass play.
  Offense+0.1742nd
  Defense+0.3016th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense47.0%38th
  Defense51.6%16th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense34.2%48th
  Defense40.3%5th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.0567th
  Defense3.0429th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense16.1%84th
  Defense20.7%63rd
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense22.0%24th
  Defense18.3%28th

Percentiles among the 130 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, 2019

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. W
   NU
2. L
   USC
3. L
   UCF
4. L
   ORE
5. W
   ORST
6. W
   WASH
7. L
   UCLA
8. W
   ARIZ
9. L
   COLO
10. L
    WSU
11. L
    CAL
12. L
    ND

Bars above the line: better than expected for Stanford.

Players, 2019

1. Davis MillsQB239 plays · +0.228 pts/play · 79th of 228 QBs
   1.02WAR0.61 to 1.41
2. K.J. CostelloQB145 plays · +0.244 pts/play · 107th of 228 QBs
   0.66WAR0.42 to 0.92
3. Cameron ScarlettRB219 plays · +0.136 pts/play · 39th of 349 RBs
   0.56WAR0.41 to 0.72
4. Michael WilsonWR63 plays · +0.130 pts/play · 112th of 439 WRs
   0.15WAR0.09 to 0.22
5. Simi FehokoWR39 plays · +0.182 pts/play · 147th of 439 WRs
   0.13WAR0.08 to 0.19
6. Connor WedingtonWR50 plays · +0.109 pts/play · 202nd of 439 WRs
   0.10WAR0.05 to 0.15
7. Jet TonerPK14 plays · +0.379 pts/play · 77th of 114 kickers
   0.10WAR0.06 to 0.14
8. Osiris St. BrownWR37 plays · +0.098 pts/play · 300th of 439 WRs
   0.07WAR0.03 to 0.10

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, 2019

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  78878820th of 130Roster talent: 788, 20th of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  23423421st of 130Recruiting: 234, 21st of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  60%60%65th of 130Returning production: 60%, 65th of 130 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −4.7−4.788th of 130SP+ rating: −4.7, 88th of 130 in FBS

Ranks and bars among the 130 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, 2019

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 6 clear-cut ones account for 0.13 of the 0.22 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 COLOQ4 7:34 4th & 1 at STAN 34, tiedPunted; the numbers favored going for it−4.3 pts
2. vs CALQ4 2:23 4th & 3 at CAL 26, tiedKicked a field goal; the numbers favored going for it−3.0 pts
3. vs ARIZQ4 6:18 4th & 3 at ARIZ 3, up 7Kicked a field goal; the numbers favored going for it−1.7 pts
4. vs WASHQ3 10:26 4th & 2 at STAN 46, up 3Punted; the numbers favored going for it−1.3 pts
5. vs NDQ3 10:45 4th & 1 at STAN 34, down 4Punted; the numbers favored going for it−1.3 pts
6. vs NUQ4 0:30 4th & 3 at midfield, up 3Punted; the numbers favored going for it−1.2 pts
7. vs WASHQ2 2:04 4th & 5 at WASH 40, up 3Punted; the numbers favored going for it (close call)−1.0 pts
8. vs NDQ2 6:16 4th & 1 at STAN 24, up 10Punted; the numbers favored going for it (close call)−0.9 pts

Record vs. expectation, 2019

101st of 130 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. W

   NU
2. L

   USC
3. L

   UCF
4. L

   ORE
5. W

   ORST
6. W

   WASH
7. L

   UCLA
8. W

   ARIZ
9. L

   COLO
10. L

    WSU
11. L

    CAL
12. L

    ND

What moved it, 2019

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−1.25
• Possession & field position−0.04
• Clock−0.04
• Timeouts+0.04
• Less the pregame edge, counted before kickoff+0.26

Game by game

• NUW 17-7 vs NU72% → 97%Before kickoff +22 · On the field +25: Scoreboard +28, Timeouts +2
• USCL 20-45 at USC41% → 0%Before kickoff −9 · On the field −41: Scoreboard −39, Possession & field position −1
• UCFL 27-45 at UCF23% → 1%Before kickoff −27 · On the field −22: Scoreboard −25, Timeouts −1
• OREL 6-21 vs ORE17% → 1%Before kickoff −33 · On the field −16: Scoreboard −25, Clock −1
• ORSTW 31-28 at ORST59% → 94%Before kickoff +9 · On the field +34: Scoreboard +46, Clock +2
• WASHW 23-13 vs WASH21% → 97%Before kickoff −29 · On the field +76: Scoreboard +44, Possession & field position +2
• UCLAL 16-34 vs UCLA65% → 1%Before kickoff +15 · On the field −64: Scoreboard −60, Clock −3
• ARIZW 41-31 vs ARIZ59% → 96%Before kickoff +9 · On the field +37: Scoreboard +35, Timeouts +2
• COLOL 13-16 at COLO60% → 4%Before kickoff +10 · On the field −56: Scoreboard −40, Possession & field position −1
• WSUL 22-49 at WSU28% → 0%Before kickoff −22 · On the field −28: Scoreboard −31, Timeouts +1
• CALL 20-24 vs CAL57% → 22%Before kickoff +7 · On the field −35: Scoreboard −36, Possession & field position −3
• NDL 24-45 vs ND13% → 1%Before kickoff −37 · On the field −12: Scoreboard −21, Clock −1

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.