UCLA

Profile vs. FBS, 2023

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+0.1044th
  Defense−0.0495th
• 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.
  Offense41.9%48th
  Defense37.0%86th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2963rd
  Defense+1.1686th
• Rushing EPA

  EPA per designed run.
  Offense+0.1674th
  Defense−0.1499th
• Passing EPA

  EPA per pass play.
  Offense+0.0714th
  Defense+0.1186th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense46.2%36th
  Defense42.0%91st
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense32.5%58th
  Defense28.2%73rd
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.2976th
  Defense2.7091st
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense16.9%51st
  Defense24.5%97th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense16.7%41st
  Defense20.7%95th

Percentiles among the 133 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, 2023

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 UCLA 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
   CCU
2. W
   SDSU
3. W
   NCCU
4. L
   UTAH
5. W
   WSU
6. L
   ORST
7. W
   STAN
8. W
   COLO
9. L
   ARIZ
10. L
    ASU
11. W
    USC
12. L
    CAL
13. W
    BOIS

Bars above the line: better than expected for UCLA.

Players, 2023

1. Ethan GarbersQB164 plays · +0.262 pts/play · 105th of 250 QBs
   0.81WAR0.51 to 1.13
2. Carson SteeleRB162 plays · +0.142 pts/play · 30th of 383 RBs
   0.43WAR0.27 to 0.57
3. T.J. HardenRB151 plays · +0.138 pts/play · 41st of 383 RBs
   0.39WAR0.25 to 0.52
4. Collin SchleeQB67 plays · +0.263 pts/play · 154th of 250 QBs
   0.33WAR0.19 to 0.47
5. Logan LoyaWR58 plays · +0.161 pts/play · 92nd of 457 WRs
   0.18WAR0.04 to 0.33
6. Will PowersP43 plays · +0.129 pts/play · 40th of 103 punters
   0.10WAR0.06 to 0.15
7. Carsen RyanTE14 plays · +0.273 pts/play · 83rd of 212 TEs
   0.07WAR0.04 to 0.10
8. Moliki MatavaoTE13 plays · +0.284 pts/play · 89th of 212 TEs
   0.07WAR0.05 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 UCLA'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, 2023

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  75375325th of 130Roster talent: 753, 25th of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  19919938th of 130Recruiting: 199, 38th of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  28%28%110th of 128Returning production: 28%, 110th of 128 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +9.7+9.727th of 130SP+ rating: +9.7, 27th 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, 2023

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 UCLA's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 3 clear-cut ones account for 0.04 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 ARIZQ4 8:02 4th & 19 at ARIZ 28, down 14Went for it; the numbers favored a field goal1.6 pts
2. at ORSTQ4 5:45 4th & 18 at ORST 26, down 12Went for it; the numbers favored a field goal1.6 pts
3. vs CALQ2 6:58 4th & 2 at CAL 5, down 6Kicked a field goal; the numbers favored going for it1.1 pts
4. vs CALQ3 4:49 4th & 13 at CAL 36, down 14Went for it; the numbers favored a field goal (close call)0.8 pts
5. vs WSUQ2 5:16 4th & 2 at UCLA 20, up 3Punted; the numbers favored going for it (close call)0.8 pts
6. vs BOISQ2 0:04 4th & 11 at BOIS 40, down 9Went for it; the numbers favored punting (close call)0.8 pts
7. vs ASUQ4 2:25 4th & 10 at UCLA 25, down 10Went for it; the numbers favored punting (close call)0.6 pts
8. vs CALQ4 11:33 4th & 17 at CAL 46, down 23Went for it; the numbers favored punting (close call)0.5 pts

Record vs. expectation, 2023

78th of 133 FBS teams at beating the model's pregame expectations

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

1. W

   CCU
2. W

   SDSU
3. W

   NCCU
4. L

   UTAH
5. W

   WSU
6. L

   ORST
7. W

   STAN
8. W

   COLO
9. L

   ARIZ
10. L

    ASU
11. W

    USC
12. L

    CAL
13. W

    BOIS

What moved it, 2023

Every game starts at UCLA'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+0.05
• Possession & field position+0.01
• Clock+0.06
• Timeouts−0.03
• Other−0.01
• Less the pregame edge, counted before kickoff−0.50

Game by game

• CCUW 27-13 vs CCU82% → 99%Before kickoff +32 · On the field +17: Scoreboard +22, Timeouts +1
• SDSUW 35-10 at SDSU78% → 100%Before kickoff +28 · On the field +21: Scoreboard +27, Clock +1
• NCCUW 59-7 vs NCCU97% → 100%Before kickoff +47 · On the field +3: Scoreboard +4
• UTAHL 7-14 at UTAH33% → 3%Before kickoff −17 · On the field −30: Scoreboard −30, Timeouts −2
• WSUW 25-17 vs WSU54% → 97%Before kickoff +4 · On the field +43: Scoreboard +37, Timeouts +2
• ORSTL 24-36 at ORST37% → 2%Before kickoff −13 · On the field −35: Scoreboard −34, Timeouts −2
• STANW 42-7 at STAN85% → 100%Before kickoff +35 · On the field +14: Scoreboard +20, Clock +1
• COLOW 28-16 vs COLO85% → 97%Before kickoff +35 · On the field +13: Scoreboard +19, Clock +1
• ARIZL 10-27 at ARIZ48% → 1%Before kickoff −2 · On the field −47: Scoreboard −43
• ASUL 7-17 vs ASU81% → 3%Before kickoff +31 · On the field −78: Scoreboard −58, Clock −3
• USCW 38-20 at USC27% → 99%Before kickoff −23 · On the field +72: Scoreboard +63, Clock +3
• CALL 7-33 vs CAL74% → 0%Before kickoff +24 · On the field −74: Scoreboard −69, Clock +1
• BOISW 35-22 vs BOIS57% → 98%Before kickoff +7 · On the field +41: Scoreboard +45, Clock +3

Points of win probability, from UCLA's side.

Closest call

UCLA 67-63 WSU (2019) - UCLA dropped to a 0.4% win probability before pulling it out.