USC

Profile vs. FBS, 2018

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+0.1043rd
  Defense+0.1250th
• 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.
  Offense43.3%47th
  Defense39.3%78th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.1834th
  Defense+1.3019th
• Rushing EPA

  EPA per designed run.
  Offense+0.0227th
  Defense+0.0750th
• Passing EPA

  EPA per pass play.
  Offense+0.1950th
  Defense+0.1748th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense48.0%46th
  Defense44.8%71st
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense32.9%46th
  Defense29.6%80th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.9454th
  Defense2.7667th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense19.5%48th
  Defense22.7%79th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense18.9%12th
  Defense18.4%80th

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, 2018

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
   UNLV
2. L
   STAN
3. L
   TEX
4. W
   WSU
5. W
   ARIZ
6. W
   COLO
7. L
   UTAH
8. L
   ASU
9. W
   ORST
10. L
    CAL
11. L
    UCLA
12. L
    ND

Bars above the line: better than expected for USC.

Players, 2018

1. JT DanielsQB361 plays · +0.162 pts/play · 77th of 225 QBs
   1.09WAR0.55 to 1.72
2. Aca'Cedric Ware?119 plays · +0.218 pts/play
   0.49WAR0.37 to 0.61
3. Tyler VaughnsWR88 plays · +0.189 pts/play · 11th of 434 WRs
   0.31WAR0.19 to 0.43
4. Vavae MalepeaiRB95 plays · +0.150 pts/play · 161st of 351 RBs
   0.27WAR0.20 to 0.33
5. Stephen CarrRB78 plays · +0.142 pts/play · 207th of 351 RBs
   0.21WAR0.14 to 0.27
6. Amon-Ra St. BrownWR68 plays · +0.152 pts/play · 44th of 434 WRs
   0.19WAR0.11 to 0.28
7. Michael Pittman Jr.WR59 plays · +0.149 pts/play · 75th of 434 WRs
   0.16WAR0.07 to 0.25
8. Velus Jones Jr.WR30 plays · +0.091 pts/play · 315th of 434 WRs
   0.05WAR0.02 to 0.08

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, 2018

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  9349344th of 130Roster talent: 934, 4th of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  2932934th of 130Recruiting: 293, 4th of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  29%29%117th of 129Returning production: 29%, 117th of 129 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +9.7+9.734th of 130SP+ rating: +9.7, 34th 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, 2018

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 7 clear-cut ones account for 0.13 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 ASUQ4 3:53 4th & 3 at USC 24, down 3Punted; the numbers favored going for it−3.2 pts
2. at UCLAQ3 7:04 4th & 3 at UCLA 3, up 3Kicked a field goal; the numbers favored going for it−2.1 pts
3. vs NDQ3 11:28 4th & 1 at USC 35, up 3Punted; the numbers favored going for it−2.1 pts
4. at ARIZQ3 1:39 4th & 1 at USC 36, up 17Punted; the numbers favored going for it−1.9 pts
5. vs CALQ3 3:03 4th & 2 at USC 44, down 1Punted; the numbers favored going for it−1.4 pts
6. vs CALQ2 11:19 4th & 1 at USC 38, up 7Punted; the numbers favored going for it−1.2 pts
7. vs NDQ2 7:01 4th & 2 at USC 47, up 10Punted; the numbers favored going for it−1.1 pts
8. vs COLOQ3 11:59 4th & 2 at COLO 47, up 14Punted; the numbers favored going for it (close call)−0.9 pts

Record vs. expectation, 2018

120th of 130 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

   UNLV
2. L

   STAN
3. L

   TEX
4. W

   WSU
5. W

   ARIZ
6. W

   COLO
7. L

   UTAH
8. L

   ASU
9. W

   ORST
10. L

    CAL
11. L

    UCLA
12. L

    ND

What moved it, 2018

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−1.12
• Possession & field position−0.03
• Clock−0.04
• Timeouts−0.04
• Less the pregame edge, counted before kickoff−0.13

Game by game

• UNLVW 43-21 vs UNLV94% → 100%Before kickoff +44 · On the field +6: Scoreboard +9
• STANL 3-17 at STAN35% → 1%Before kickoff −15 · On the field −35: Scoreboard −34, Timeouts −1
• TEXL 14-37 at TEX35% → 0%Before kickoff −15 · On the field −35: Scoreboard −36
• WSUW 39-36 vs WSU62% → 96%Before kickoff +12 · On the field +34: Scoreboard +32, Timeouts +2
• ARIZW 24-20 at ARIZ58% → 95%Before kickoff +8 · On the field +37: Scoreboard +46, Clock +3
• COLOW 31-20 vs COLO67% → 98%Before kickoff +17 · On the field +31: Scoreboard +34, Timeouts −1
• UTAHL 28-41 at UTAH33% → 2%Before kickoff −17 · On the field −31: Scoreboard −32, Timeouts −2
• ASUL 35-38 vs ASU56% → 20%Before kickoff +6 · On the field −36: Scoreboard −37, Clock −3
• ORSTW 38-21 at ORST85% → 98%Before kickoff +35 · On the field +14: Scoreboard +25
• CALL 14-15 vs CAL61% → 5%Before kickoff +11 · On the field −55: Scoreboard −51, Clock −3
• UCLAL 27-34 at UCLA59% → 3%Before kickoff +9 · On the field −55: Scoreboard −41, Timeouts −2
• NDL 17-24 vs ND16% → 5%Before kickoff −34 · On the field −10: Scoreboard −27, Clock −2

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.