California

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.
  Offense+0.0942nd
  Defense+0.1241st
• 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.
  Offense40.6%30th
  Defense42.3%42nd
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2559th
  Defense+1.1782nd
• Rushing EPA

  EPA per designed run.
  Offense−0.066th
  Defense+0.189th
• Passing EPA

  EPA per pass play.
  Offense+0.1853rd
  Defense+0.0971st
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense44.0%16th
  Defense49.7%24th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense33.2%77th
  Defense26.3%84th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.6412th
  Defense3.325th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense18.1%58th
  Defense12.8%1st
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense16.4%33rd
  Defense15.1%41st

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 California 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
   ORST
2. W
   TXSO
3. W
   MINN
4. L
   SDSU
5. W
   BC
6. L
   DUKE
7. W
   UNC
8. L
   VT
9. L
   UVA
10. W
    LOU
11. L
    STAN
12. W
    SMU
13. L
    HAW

Bars above the line: better than expected for California.

Players, 2025

1. Jaron-Keawe SagapoluteleQB475 plays · +0.234 pts/play · 11th of 231 QBs
   2.08WAR1.21 to 2.85
2. Kendrick RaphaelRB245 plays · +0.088 pts/play · 15th of 365 RBs
   0.41WAR0.26 to 0.56
3. Trond GrizzellWR78 plays · +0.137 pts/play · 70th of 451 WRs
   0.20WAR0.08 to 0.32
4. Mason MiniTE40 plays · +0.133 pts/play · 30th of 213 TEs
   0.10WAR0.03 to 0.17
5. Jordan KingWR29 plays · +0.176 pts/play · 196th of 451 WRs
   0.10WAR0.05 to 0.14
6. LJ Johnson Jr.RB32 plays · +0.068 pts/play · 282nd of 365 RBs
   0.04WAR0.02 to 0.06
7. Jacob De JesusWR65 plays · +0.024 pts/play · 364th of 451 WRs
   0.03WAR−0.08 to 0.14
8. Brandon High Jr.RB17 plays · +0.085 pts/play · 292nd of 365 RBs
   0.03WAR0.02 to 0.04

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 California'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.
  72672636th of 134Roster talent: 726, 36th of 134 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  17717769th of 134Recruiting: 177, 69th of 134 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  6%6%131st of 132Returning production: 6%, 131st of 132 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −3.2−3.279th of 134SP+ rating: −3.2, 79th 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 California's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 5 clear-cut ones account for 0.10 of the 0.11 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 ORSTQ4 6:10 4th & 2 at ORST 45, up 7Punted; the numbers favored going for it−2.3 pts
2. at HAWQ4 8:56 4th & 4 at HAW 4, tiedKicked a field goal; the numbers favored going for it−2.3 pts
3. at LOUQ4 6:20 4th & 2 at CAL 27, tiedPunted; the numbers favored going for it−1.8 pts
4. at BCQ3 13:11 4th & 3 at BC 42, down 6Punted; the numbers favored going for it−1.7 pts
5. at ORSTQ2 0:00 4th & 2 at ORST 30, up 7Kicked a field goal; the numbers favored going for it−1.6 pts
6. at STANQ3 9:48 4th & 2 at CAL 28, down 4Punted; the numbers favored going for it (close call)−0.9 pts
7. at STANQ4 0:40 4th & 3 at STAN 19, down 21Went for it; the numbers favored a field goal (close call)−0.3 pts
8. at ORSTQ2 2:09 4th & 7 at CAL 40, up 7Punted; the numbers favored going for it (close call)−0.2 pts

Record vs. expectation, 2025

42nd of 136 FBS teams at beating the model's pregame expectations

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

1. W

   ORST
2. W

   TXSO
3. W

   MINN
4. L

   SDSU
5. W

   BC
6. L

   DUKE
7. W

   UNC
8. L

   VT
9. L

   UVA
10. W

    LOU
11. L

    STAN
12. W

    SMU
13. L

    HAW

What moved it, 2025

Every game starts at California'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+0.88
• Possession & field position−0.04
• Clock−0.33
• Timeouts+0.38
• Other+0.01
• Less the pregame edge, counted before kickoff+0.75

Game by game

• ORSTW 34-15 at ORST47% → 91%Before kickoff −3 · On the field +44: Scoreboard +45, Clock +3
• TXSOW 35-3 vs TXSO99% → 100%Before kickoff +49 · On the field +1: Scoreboard +1
• MINNW 27-14 vs MINN37% → 97%Before kickoff −13 · On the field +60: Scoreboard +76, Timeouts −24
• SDSUL 0-34 at SDSU82% → 0%Before kickoff +32 · On the field −82: Scoreboard −66, Clock +1
• BCW 28-24 at BC28% → 98%Before kickoff −22 · On the field +71: Scoreboard +36, Timeouts +24
• DUKEL 21-45 vs DUKE38% → 0%Before kickoff −12 · On the field −37: Scoreboard −43, Clock −2
• UNCW 21-18 vs UNC69% → 89%Before kickoff +19 · On the field +20: Scoreboard +21, Possession & field position +2
• VTL 34-42 at VT29% → 94%Before kickoff −21 · On the field +64: Scoreboard +58, Clock −13
• UVAL 21-31 vs UVA32% → 3%Before kickoff −18 · On the field −30: Scoreboard −39, Clock −2
• LOUW 29-26 at LOU11% → 72%Before kickoff −39 · On the field +61: Scoreboard +33, Clock −20
• STANL 10-31 at STAN59% → 0%Before kickoff +9 · On the field −59: Scoreboard −53, Clock +2
• SMUW 38-35 vs SMU16% → 96%Before kickoff −34 · On the field +80: Scoreboard +41, Timeouts +2
• HAWL 31-35 at HAW45% → 17%Before kickoff −5 · On the field −28: Scoreboard −23, Timeouts +4

Points of win probability, from California's side.

Closest call

VT 20-25 CAL (2026) - California dropped to a 1.5% win probability before pulling it out.