UCLA

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+0.1247th
  Defense+0.1919th
• 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.
  Offense42.7%41st
  Defense47.6%14th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2568th
  Defense+1.1767th
• Rushing EPA

  EPA per designed run.
  Offense+0.1370th
  Defense+0.1522nd
• Passing EPA

  EPA per pass play.
  Offense+0.1234th
  Defense+0.2722nd
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense48.1%47th
  Defense50.6%22nd
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense32.2%41st
  Defense38.6%5th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.9757th
  Defense3.1119th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense18.9%57th
  Defense16.1%14th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense16.1%50th
  Defense13.4%9th

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 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. L
   CIN
2. L
   OU
3. L
   FRES
4. L
   COLO
5. L
   WASH
6. W
   CAL
7. W
   ARIZ
8. L
   UTAH
9. L
   ORE
10. L
    ASU
11. W
    USC
12. L
    STAN

Bars above the line: better than expected for UCLA.

Players, 2018

1. Joshua KelleyRB232 plays · +0.217 pts/play · 5th of 351 RBs
   0.94WAR0.79 to 1.10
2. Wilton SpeightQB210 plays · +0.193 pts/play · 105th of 225 QBs
   0.76WAR0.41 to 1.08
3. Dorian Thompson-RobinsonQB150 plays · +0.146 pts/play · 150th of 225 QBs
   0.41WAR0.12 to 0.67
4. Caleb WilsonTE69 plays · +0.155 pts/play · 2nd of 204 TEs
   0.20WAR0.08 to 0.33
5. JJ MolsonPK18 plays · +0.428 pts/play · 23rd of 112 kickers
   0.14WAR0.10 to 0.19
6. Theo HowardWR50 plays · +0.119 pts/play · 164th of 434 WRs
   0.11WAR0.04 to 0.18
7. Bolu OlorunfunmiRB19 plays · +0.170 pts/play · 281st of 351 RBs
   0.06WAR0.04 to 0.08
8. Stefan FlintoftP45 plays · +0.059 pts/play · 60th of 91 punters
   0.05WAR−0.02 to 0.12

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, 2018

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  75475419th of 130Roster talent: 754, 19th of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  24924917th of 130Recruiting: 249, 17th of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  34%34%109th of 129Returning production: 34%, 109th of 129 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −0.4−0.476th of 130SP+ rating: −0.4, 76th 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 UCLA'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 0.15 of the 0.21 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 USCQ4 6:19 4th & 2 at USC 2, up 1Kicked a field goal; the numbers favored going for it−5.2 pts
2. vs STANQ4 3:34 4th & 15 at STAN 24, down 7Went for it; the numbers favored a field goal−2.3 pts
3. vs USCQ3 7:04 4th & 4 at USC 41, down 6Punted; the numbers favored going for it−2.0 pts
4. vs USCQ4 2:36 4th & 4 at USC 31, up 4Kicked a field goal; the numbers favored going for it−1.7 pts
5. at ASUQ4 14:16 4th & 5 at ASU 40, down 3Punted; the numbers favored going for it−1.4 pts
6. at CALQ2 1:28 4th & 1 at UCLA 24, up 13Punted; the numbers favored going for it−1.4 pts
7. vs ARIZQ3 13:25 4th & 1 at UCLA 34, up 10Punted; the numbers favored going for it−1.1 pts
8. at OREQ3 15:00 4th & 11 at UCLA 39, down 14Went for it; the numbers favored punting (close call)−0.8 pts

Record vs. expectation, 2018

98th of 130 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. L

   CIN
2. L

   OU
3. L

   FRES
4. L

   COLO
5. L

   WASH
6. W

   CAL
7. W

   ARIZ
8. L

   UTAH
9. L

   ORE
10. L

    ASU
11. W

    USC
12. L

    STAN

What moved it, 2018

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−1.30
• Possession & field position+0.01
• Clock−0.09
• Timeouts+0.04
• Less the pregame edge, counted before kickoff+0.60

Game by game

• CINL 17-26 vs CIN81% → 5%Before kickoff +31 · On the field −76: Scoreboard −57, Clock −4
• OUL 21-49 at OU3% → 0%Before kickoff −47 · On the field −3: Scoreboard −5
• FRESL 14-38 vs FRES43% → 1%Before kickoff −7 · On the field −42: Scoreboard −47, Clock −1
• COLOL 16-38 at COLO25% → 0%Before kickoff −25 · On the field −25: Scoreboard −28
• WASHL 24-31 vs WASH7% → 4%Before kickoff −43 · On the field −3: Scoreboard −18, Clock −1
• CALW 37-7 at CAL28% → 99%Before kickoff −22 · On the field +71: Scoreboard +65, Clock +1
• ARIZW 31-30 vs ARIZ74% → 90%Before kickoff +24 · On the field +16: Scoreboard +21, Timeouts +2
• UTAHL 10-41 vs UTAH24% → 0%Before kickoff −26 · On the field −24: Scoreboard −30, Clock −1
• OREL 21-42 at ORE20% → 0%Before kickoff −30 · On the field −20: Scoreboard −24
• ASUL 28-31 at ASU19% → 18%Before kickoff −31 · On the field −1: Scoreboard −11, Possession & field position −2
• USCW 34-27 vs USC41% → 97%Before kickoff −9 · On the field +55: Scoreboard +41, Timeouts +2
• STANL 42-49 vs STAN29% → 5%Before kickoff −21 · On the field −25: Scoreboard −38, Clock −2

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.