UCLA

Profile vs. FBS, 2016

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+0.0625th
  Defense0.0085th
• 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.
  Offense38.8%12th
  Defense41.0%70th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2675th
  Defense+1.0398th
• Rushing EPA

  EPA per designed run.
  Offense−0.111st
  Defense+0.0461st
• Passing EPA

  EPA per pass play.
  Offense+0.1854th
  Defense−0.0394th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense41.4%3rd
  Defense45.2%73rd
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense34.2%54th
  Defense31.2%73rd
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.455th
  Defense2.8364th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense27.4%1st
  Defense17.3%27th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense20.3%5th
  Defense16.7%55th

Percentiles among the 128 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, 2016

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
   TA&M
2. W
   UNLV
3. W
   BYU
4. L
   STAN
5. W
   ARIZ
6. L
   ASU
7. L
   WSU
8. L
   UTAH
9. L
   COLO
10. W
    ORST
11. L
    USC
12. L
    CAL

Bars above the line: better than expected for UCLA.

Players, 2016

1. Josh RosenQB237 plays · +0.234 pts/play · 82nd of 218 QBs
   1.04WAR0.68 to 1.43
2. Mike FafaulQB239 plays · +0.198 pts/play · 93rd of 218 QBs
   0.89WAR0.48 to 1.30
3. Nate StarksRB94 plays · +0.120 pts/play · 173rd of 347 RBs
   0.21WAR0.13 to 0.29
4. Jordan LasleyWR59 plays · +0.176 pts/play · 76th of 417 WRs
   0.19WAR0.11 to 0.29
5. Darren AndrewsWR67 plays · +0.146 pts/play · 90th of 417 WRs
   0.18WAR0.09 to 0.28
6. Bolu OlorunfunmiRB70 plays · +0.122 pts/play · 208th of 347 RBs
   0.16WAR0.11 to 0.21
7. Soso JamaboRB92 plays · +0.090 pts/play · 211th of 347 RBs
   0.15WAR0.07 to 0.25
8. JJ MolsonPK20 plays · +0.229 pts/play · 69th of 116 kickers
   0.09WAR0.02 to 0.16

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, 2016

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  81981912th of 128Roster talent: 819, 12th of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  25625614th of 128Recruiting: 256, 14th of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  54%54%91st of 128Returning production: 54%, 91st of 128 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +9.1+9.144th of 128SP+ rating: +9.1, 44th of 128 in FBS

Ranks and bars among the 128 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, 2016

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 11 clear-cut ones account for 0.23 of the 0.31 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 UTAHQ4 10:39 4th & 1 at UCLA 19, down 7Punted; the numbers favored going for it−4.9 pts
2. vs STANQ4 6:32 4th & 2 at STAN 18, up 1Kicked a field goal; the numbers favored going for it−3.6 pts
3. vs STANQ4 2:05 4th & 2 at UCLA 46, up 4Punted; the numbers favored going for it−3.1 pts
4. at ASUQ3 6:02 4th & 2 at ASU 2, down 10Kicked a field goal; the numbers favored going for it−2.7 pts
5. vs USCQ3 7:35 4th & 1 at UCLA 47, down 16Punted; the numbers favored going for it−1.7 pts
6. vs STANQ3 12:53 4th & 2 at STAN 48, up 7Punted; the numbers favored going for it−1.6 pts
7. at TA&MQ3 13:18 4th & 2 at TA&M 47, down 1Punted; the numbers favored going for it−1.5 pts
8. vs UTAHQ4 13:44 4th & 2 at UTAH 22, down 10Kicked a field goal; the numbers favored going for it−1.2 pts

Record vs. expectation, 2016

124th of 128 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

   TA&M
2. W

   UNLV
3. W

   BYU
4. L

   STAN
5. W

   ARIZ
6. L

   ASU
7. L

   WSU
8. L

   UTAH
9. L

   COLO
10. W

    ORST
11. L

    USC
12. L

    CAL

What moved it, 2016

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−1.87
• Possession & field position−0.08
• Clock−0.20
• Timeouts+0.14
• Less the pregame edge, counted before kickoff−0.52

Game by game

• TA&ML 24-31 at TA&M49% → 11%Before kickoff −1 · On the field −38: Scoreboard −31, Timeouts +18
• UNLVW 42-21 vs UNLV95% → 100%Before kickoff +45 · On the field +5: Scoreboard +8
• BYUW 17-14 at BYU63% → 94%Before kickoff +13 · On the field +31: Scoreboard +41, Clock +3
• STANL 13-22 vs STAN47% → 5%Before kickoff −3 · On the field −43: Scoreboard −49, Clock −2
• ARIZW 45-24 vs ARIZ48% → 100%Before kickoff −2 · On the field +52: Scoreboard +47, Possession & field position +1
• ASUL 20-23 at ASU66% → 11%Before kickoff +16 · On the field −55: Scoreboard −27, Possession & field position −4
• WSUL 21-27 at WSU45% → 3%Before kickoff −5 · On the field −42: Scoreboard −36, Timeouts −2
• UTAHL 45-52 vs UTAH73% → 11%Before kickoff +23 · On the field −63: Scoreboard −47, Clock −2
• COLOL 10-20 at COLO27% → 1%Before kickoff −23 · On the field −26: Scoreboard −30
• ORSTW 38-24 vs ORST77% → 100%Before kickoff +27 · On the field +23: Scoreboard +25
• USCL 14-36 vs USC25% → 0%Before kickoff −25 · On the field −25: Scoreboard −32, Clock −2
• CALL 10-36 at CAL71% → 0%Before kickoff +21 · On the field −71: Scoreboard −57, Possession & field position −1

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.