California

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+0.0832nd
  Defense+0.0771st
• 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.
  Offense39.3%17th
  Defense42.8%50th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2877th
  Defense+1.1087th
• Rushing EPA

  EPA per designed run.
  Offense+0.0750th
  Defense+0.0457th
• Passing EPA

  EPA per pass play.
  Offense+0.0924th
  Defense+0.1069th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense41.5%4th
  Defense46.9%57th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense35.0%57th
  Defense34.3%37th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.8241st
  Defense2.9936th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense21.0%32nd
  Defense16.1%16th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense19.3%52nd
  Defense20.4%55th

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 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
   UCD
2. W
   WASH
3. W
   UNT
4. W
   MISS
5. L
   ASU
6. L
   ORE
7. L
   ORST
8. L
   UTAH
9. W
   WSU
10. L
    USC
11. W
    STAN
12. W
    UCLA
13. W
    ILL

Bars above the line: better than expected for California.

Players, 2019

1. Chase GarbersQB262 plays · +0.249 pts/play · 66th of 228 QBs
   1.22WAR0.73 to 1.68
2. Christopher Brown Jr.RB186 plays · +0.149 pts/play · 53rd of 349 RBs
   0.52WAR0.39 to 0.65
3. Devon ModsterQB151 plays · +0.158 pts/play · 135th of 228 QBs
   0.45WAR0.21 to 0.71
4. Marcel DancyRB71 plays · +0.123 pts/play · 225th of 349 RBs
   0.16WAR0.11 to 0.21
5. Jordan DuncanWR35 plays · +0.155 pts/play · 202nd of 439 WRs
   0.10WAR0.06 to 0.14
6. Greg ThomasPK13 plays · +0.385 pts/play · 81st of 114 kickers
   0.09WAR0.06 to 0.13
7. Nikko RemigioWR53 plays · +0.091 pts/play · 231st of 439 WRs
   0.09WAR0.04 to 0.15
8. Trevon ClarkWR37 plays · +0.083 pts/play · 341st of 439 WRs
   0.06WAR0.02 to 0.09

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, 2019

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  61261250th of 130Roster talent: 612, 50th of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  19019044th of 130Recruiting: 190, 44th of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  55%55%78th of 130Returning production: 55%, 78th of 130 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −2.6−2.674th of 130SP+ rating: −2.6, 74th 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 California's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 8 clear-cut ones account for 0.14 of the 0.20 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. vs ASUQ3 2:18 4th & 1 at CAL 42, tiedPunted; the numbers favored going for it2.7 pts
2. at MISSQ4 15:00 4th & 1 at CAL 20, up 15Punted; the numbers favored going for it2.4 pts
3. at MISSQ4 2:51 4th & 1 at CAL 47, up 8Punted; the numbers favored going for it2.2 pts
4. at OREQ2 0:00 4th & 17 at ORE 42, up 7Went for it; the numbers favored punting1.9 pts
5. at MISSQ3 3:42 4th & 5 at MISS 38, up 15Punted; the numbers favored going for it1.3 pts
6. at ILLQ3 5:34 4th & 1 at CAL 21, up 15Punted; the numbers favored going for it1.3 pts
7. vs ORSTQ3 4:01 4th & 2 at CAL 43, down 4Punted; the numbers favored going for it1.2 pts
8. at UCLAQ3 15:00 4th & 2 at CAL 47, up 4Punted; the numbers favored going for it1.1 pts

Record vs. expectation, 2019

12th of 130 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

   UCD
2. W

   WASH
3. W

   UNT
4. W

   MISS
5. L

   ASU
6. L

   ORE
7. L

   ORST
8. L

   UTAH
9. W

   WSU
10. L

    USC
11. W

    STAN
12. W

    UCLA
13. W

    ILL

What moved it, 2019

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+1.55
• Possession & field position−0.01
• Clock+0.02
• Timeouts+0.01
• Less the pregame edge, counted before kickoff+0.15

Game by game

• UCDW 27-13 vs UCD86% → 99%Before kickoff +36 · On the field +12: Scoreboard +18, Timeouts +1
• WASHW 20-19 at WASH17% → 80%Before kickoff −33 · On the field +63: Scoreboard +34, Clock +3
• UNTW 23-17 vs UNT80% → 95%Before kickoff +30 · On the field +15: Scoreboard +23, Timeouts +1
• MISSW 28-20 at MISS42% → 91%Before kickoff −8 · On the field +50: Scoreboard +51, Clock +1
• ASUL 17-24 vs ASU60% → 4%Before kickoff +10 · On the field −55: Scoreboard −52, Clock −3
• OREL 7-17 at ORE6% → 3%Before kickoff −44 · On the field −3: Scoreboard −12, Timeouts −1
• ORSTL 17-21 vs ORST74% → 16%Before kickoff +24 · On the field −58: Scoreboard −39, Possession & field position −4
• UTAHL 0-35 at UTAH7% → 0%Before kickoff −43 · On the field −7: Scoreboard −10
• WSUW 33-20 vs WSU30% → 99%Before kickoff −20 · On the field +69: Scoreboard +49, Timeouts +2
• USCL 17-41 vs USC33% → 0%Before kickoff −17 · On the field −33: Scoreboard −38, Clock −2
• STANW 24-20 at STAN43% → 78%Before kickoff −7 · On the field +35: Scoreboard +36, Possession & field position +3
• UCLAW 28-18 at UCLA45% → 96%Before kickoff −5 · On the field +51: Scoreboard +54, Clock +3
• ILLW 35-20 at ILL65% → 99%Before kickoff +15 · On the field +34: Scoreboard +41, Clock +2

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.