USC

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+0.2894th
  Defense+0.0853rd
• 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.
  Offense48.9%93rd
  Defense45.4%13th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.3278th
  Defense+1.1590th
• Rushing EPA

  EPA per designed run.
  Offense+0.1573rd
  Defense+0.0938th
• Passing EPA

  EPA per pass play.
  Offense+0.4899th
  Defense+0.0973rd
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense53.1%92nd
  Defense50.3%19th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense37.3%93rd
  Defense33.5%15th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.1679th
  Defense3.298th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense16.4%73rd
  Defense17.6%37th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense13.2%77th
  Defense15.9%54th

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 USC 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
   MOST
2. W
   GASO
3. W
   PUR
4. W
   MSU
5. L
   ILL
6. W
   MICH
7. L
   ND
8. W
   NEB
9. W
   NU
10. W
    IOWA
11. L
    ORE
12. W
    UCLA
13. L
    TCU

Bars above the line: better than expected for USC.

Players, 2025

1. Jayden MaiavaQB378 plays · +0.212 pts/play · 41st of 231 QBs
   1.50WAR0.75 to 2.21
2. King MillerRB154 plays · +0.104 pts/play · 42nd of 365 RBs
   0.30WAR0.22 to 0.39
3. Makai LemonWR87 plays · +0.147 pts/play · 42nd of 451 WRs
   0.24WAR0.04 to 0.42
4. Ja'Kobi LaneWR60 plays · +0.188 pts/play · 59th of 451 WRs
   0.21WAR0.05 to 0.36
5. Tanook HinesWR39 plays · +0.269 pts/play · 74th of 451 WRs
   0.20WAR0.11 to 0.28
6. Waymond JordanRB72 plays · +0.095 pts/play · 201st of 365 RBs
   0.13WAR0.09 to 0.16
7. Ryon SayeriP19 plays · +0.288 pts/play · 10th of 100 punters
   0.10WAR0.06 to 0.14
8. Lake McReeTE42 plays · +0.093 pts/play · 53rd of 213 TEs
   0.07WAR−0.01 to 0.15

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 USC'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.
  84884817th of 134Roster talent: 848, 17th of 134 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  23923919th of 134Recruiting: 239, 19th of 134 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  37%37%63rd of 132Returning production: 37%, 63rd of 132 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +16.9+16.916th of 134SP+ rating: +16.9, 16th 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 USC's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 2 clear-cut ones account for 0.02 of the 0.05 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 NDQ3 6:19 4th & 3 at ND 26, down 8Kicked a field goal; the numbers favored going for it−1.0 pts
2. at ILLQ4 9:54 4th & 8 at ILL 19, down 14Went for it; the numbers favored a field goal−1.0 pts
3. at PURQ4 8:24 4th & 3 at PUR 19, up 13Kicked a field goal; the numbers favored going for it (close call)−0.6 pts
4. at PURQ4 1:10 4th & 2 at PUR 2, up 13Kicked a field goal; the numbers favored going for it (close call)−0.5 pts
5. at OREQ4 2:24 4th & 10 at ORE 26, down 15Went for it; the numbers favored a field goal (close call)−0.4 pts
6. at OREQ3 11:36 4th & 10 at ORE 45, down 20Went for it; the numbers favored punting (close call)−0.3 pts
7. vs NUQ4 4:40 4th & 3 at NU 3, up 18Kicked a field goal; the numbers favored going for it (close call)−0.3 pts
8. at NEBQ2 6:07 4th & 6 at NEB 32, down 4Kicked a field goal; the numbers favored going for it (close call)−0.3 pts

Record vs. expectation, 2025

78th of 136 FBS teams at beating the model's pregame expectations

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

1. W

   MOST
2. W

   GASO
3. W

   PUR
4. W

   MSU
5. L

   ILL
6. W

   MICH
7. L

   ND
8. W

   NEB
9. W

   NU
10. W

    IOWA
11. L

    ORE
12. W

    UCLA
13. L

    TCU

What moved it, 2025

Every game starts at USC'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+0.49
• Possession & field position+0.03
• Clock−0.05
• Timeouts+0.30
• Other−0.01
• Less the pregame edge, counted before kickoff−0.77

Game by game

• MOSTW 73-13 vs MOST99% → 100%Before kickoff +49 · On the field +1: Scoreboard +3
• GASOW 59-20 vs GASO97% → 100%Before kickoff +47 · On the field +3: Scoreboard +5
• PURW 33-17 at PUR92% → 99%Before kickoff +42 · On the field +7: Scoreboard +16, Clock +1
• MSUW 45-31 vs MSU89% → 99%Before kickoff +39 · On the field +9: Scoreboard +14, Timeouts +1
• ILLL 32-34 at ILL68% → 5%Before kickoff +18 · On the field −63: Scoreboard −42, Possession & field position +1
• MICHW 31-13 vs MICH57% → 100%Before kickoff +7 · On the field +43: Scoreboard +41, Possession & field position +1
• NDL 24-34 at ND23% → 1%Before kickoff −27 · On the field −22: Scoreboard −26, Timeouts −1
• NEBW 21-17 at NEB60% → 95%Before kickoff +10 · On the field +35: Scoreboard +47, Clock +3
• NUW 38-17 vs NU86% → 100%Before kickoff +36 · On the field +14: Scoreboard +18
• IOWAW 26-21 vs IOWA70% → 93%Before kickoff +20 · On the field +24: Scoreboard +25, Timeouts +4
• OREL 27-42 at ORE22% → 1%Before kickoff −28 · On the field −21: Scoreboard −24, Timeouts −1
• UCLAW 29-10 vs UCLA93% → 99%Before kickoff +43 · On the field +6: Scoreboard +11, Timeouts +1
• TCUL 27-30 at TCU62% → 24%Before kickoff +12 · On the field −38: Scoreboard −38, Timeouts +27

Points of win probability, from USC's side.

Closest call

SJSU 28-56 USC (2023) - USC dropped to a 2.6% win probability before pulling it out.