Arizona

Profile vs. FBS, 2015

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+0.1672nd
  Defense+0.1913th
• 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.
  Offense45.6%71st
  Defense45.1%31st
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2883rd
  Defense+1.2046th
• Rushing EPA

  EPA per designed run.
  Offense+0.0960th
  Defense+0.1127th
• Passing EPA

  EPA per pass play.
  Offense+0.2365th
  Defense+0.3113th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense48.7%61st
  Defense49.8%28th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense38.5%81st
  Defense34.4%38th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.8142nd
  Defense2.8846th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense19.8%50th
  Defense17.2%20th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense2.4%24th
  Defense1.9%47th

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, 2015

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 Arizona 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
   UTSA
2. W
   NEV
3. W
   NAU
4. L
   UCLA
5. L
   STAN
6. W
   ORST
7. W
   COLO
8. L
   WSU
9. L
   WASH
10. L
    USC
11. W
    UTAH
12. L
    ASU
13. W
    UNM

Bars above the line: better than expected for Arizona.

Players, 2015

1. Anu SolomonQB319 plays · +0.218 pts/play · 73rd of 205 QBs
   1.30WAR0.88 to 1.81
2. Jerrard RandallQB109 plays · +0.231 pts/play · 136th of 205 QBs
   0.47WAR0.27 to 0.68
3. Jared BakerRB119 plays · +0.164 pts/play · 48th of 333 RBs
   0.37WAR0.28 to 0.46
4. Nick WilsonRB102 plays · +0.164 pts/play · 61st of 333 RBs
   0.31WAR0.22 to 0.40
5. Cayleb JonesWR72 plays · +0.150 pts/play · 79th of 411 WRs
   0.20WAR0.09 to 0.33
6. Johnny JacksonWR43 plays · +0.188 pts/play · 125th of 411 WRs
   0.15WAR0.10 to 0.20
7. Casey SkowronPK18 plays · +0.395 pts/play · 44th of 115 kickers
   0.13WAR0.08 to 0.19
8. Drew RigglemanP42 plays · +0.123 pts/play · 43rd of 92 punters
   0.10WAR0.03 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 Arizona'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, 2015

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  60760745th of 128Roster talent: 607, 45th of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  20020036th of 128Recruiting: 200, 36th of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  88%88%16th of 127Returning production: 88%, 16th of 127 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +4.7+4.757th of 128SP+ rating: +4.7, 57th 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, 2015

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 Arizona's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 4 clear-cut ones account for 0.05 of the 0.09 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 COLOQ2 1:02 4th & 3 at COLO 41, tiedPunted; the numbers favored going for it−1.5 pts
2. at COLOQ3 11:44 4th & 6 at COLO 40, down 7Punted; the numbers favored going for it−1.3 pts
3. at ASUQ2 4:00 4th & 1 at ARIZ 34, down 18Punted; the numbers favored going for it−1.1 pts
4. at ASUQ2 5:47 4th & 2 at ASU 5, down 14Kicked a field goal; the numbers favored going for it−1.0 pts
5. vs UCLAQ4 9:32 4th & 11 at UCLA 12, down 26Went for it; the numbers favored a field goal (close call)−0.5 pts
6. vs UCLAQ1 7:21 4th & 1 at ARIZ 46, down 7Punted; the numbers favored going for it (close call)−0.5 pts
7. vs ORSTQ3 9:25 4th & 3 at ORST 3, up 27Kicked a field goal; the numbers favored going for it (close call)−0.4 pts
8. at UNMQ4 1:32 4th & 3 at UNM 20, up 5Kicked a field goal; the numbers favored going for it (close call)−0.4 pts

Record vs. expectation, 2015

80th of 128 FBS teams at beating the model's pregame expectations

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

1. W

   UTSA
2. W

   NEV
3. W

   NAU
4. L

   UCLA
5. L

   STAN
6. W

   ORST
7. W

   COLO
8. L

   WSU
9. L

   WASH
10. L

    USC
11. W

    UTAH
12. L

    ASU
13. W

    UNM

What moved it, 2015

Every game starts at Arizona'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−0.44
• Possession & field position+0.04
• Clock+0.16
• Timeouts−0.18
• Other−0.01
• Less the pregame edge, counted before kickoff−0.28

Game by game

• UTSAW 42-32 vs UTSA97% → 97%Before kickoff +47 · On the field 0: Scoreboard +8
• NEVW 44-20 at NEV79% → 100%Before kickoff +29 · On the field +20: Scoreboard +28, Clock +2
• NAUW 77-13 vs NAU98% → 100%Before kickoff +48 · On the field +2: Scoreboard +3
• UCLAL 30-56 vs UCLA37% → 0%Before kickoff −13 · On the field −37: Scoreboard −42, Clock −1
• STANL 17-55 at STAN17% → 0%Before kickoff −33 · On the field −17: Scoreboard −20
• ORSTW 44-7 vs ORST84% → 100%Before kickoff +34 · On the field +16: Scoreboard +20
• COLOW 38-31 at COLO68% → 92%Before kickoff +18 · On the field +23: Scoreboard +37, Clock +2
• WSUL 42-45 vs WSU75% → 5%Before kickoff +25 · On the field −69: Scoreboard −53, Clock −3
• WASHL 3-49 at WASH38% → 0%Before kickoff −12 · On the field −38: Scoreboard −39
• USCL 30-38 at USC12% → 3%Before kickoff −38 · On the field −9: Scoreboard −17
• UTAHW 37-30 vs UTAH39% → 92%Before kickoff −11 · On the field +53: Scoreboard +34, Timeouts −17
• ASUL 37-52 at ASU32% → 1%Before kickoff −18 · On the field −31: Scoreboard −32, Timeouts −1
• UNMW 45-37 at UNM80% → 97%Before kickoff +30 · On the field +16: Scoreboard +30, Clock +2

Points of win probability, from Arizona's side.

Closest call

NIU 17-42 ARIZ (2026) - Arizona dropped to a 1.4% win probability before pulling it out.