Arizona

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+0.2792nd
  Defense+0.0862nd
• 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.
  Offense50.6%96th
  Defense42.0%50th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2543rd
  Defense+1.2072nd
• Rushing EPA

  EPA per designed run.
  Offense+0.1676th
  Defense0.0083rd
• Passing EPA

  EPA per pass play.
  Offense+0.4392nd
  Defense+0.2251st
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense54.6%95th
  Defense47.2%53rd
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense40.8%97th
  Defense32.0%28th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.2267th
  Defense3.0259th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense20.4%14th
  Defense19.6%74th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense16.0%53rd
  Defense18.0%75th

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 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
   NAU
2. L
   MSST
3. W
   UTEP
4. W
   STAN
5. L
   WASH
6. L
   USC
7. W
   WSU
8. W
   ORST
9. W
   UCLA
10. W
    COLO
11. W
    UTAH
12. W
    ASU
13. W
    OU

Bars above the line: better than expected for Arizona.

Players, 2023

1. Noah FifitaQB323 plays · +0.283 pts/play · 38th of 250 QBs
   1.71WAR1.01 to 2.44
2. Tetairoa McMillanWR88 plays · +0.284 pts/play · 2nd of 457 WRs
   0.47WAR0.29 to 0.65
3. Jonah ColemanRB133 plays · +0.133 pts/play · 56th of 383 RBs
   0.33WAR0.22 to 0.45
4. Jayden de LauraQB107 plays · +0.155 pts/play · 159th of 250 QBs
   0.31WAR0.08 to 0.50
5. Michael WileyRB74 plays · +0.167 pts/play · 113th of 383 RBs
   0.23WAR0.15 to 0.30
6. Tanner McLachlanTE42 plays · +0.256 pts/play · 10th of 212 TEs
   0.20WAR0.12 to 0.29
7. Jacob CowingWR80 plays · +0.118 pts/play · 90th of 457 WRs
   0.18WAR0.01 to 0.34
8. DJ WilliamsRB65 plays · +0.137 pts/play · 172nd of 383 RBs
   0.17WAR0.11 to 0.22

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, 2023

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  68768742nd of 130Roster talent: 687, 42nd of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  18918951st of 130Recruiting: 189, 51st of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  85%85%10th of 128Returning production: 85%, 10th of 128 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +14.1+14.118th of 130SP+ rating: +14.1, 18th 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 Arizona's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 2 clear-cut ones account for 0.03 of the 0.07 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 COLOQ4 7:06 4th & 2 at ARIZ 16, tiedPunted; the numbers favored going for it−1.6 pts
2. at WSUQ3 10:49 4th & 3 at WSU 4, up 14Kicked a field goal; the numbers favored going for it−1.3 pts
3. vs UTAHQ3 0:29 4th & 4 at UTAH 41, up 18Punted; the numbers favored going for it (close call)−0.7 pts
4. at USCQ4 2:08 4th & 7 at USC 33, tiedKicked a field goal; the numbers favored going for it (close call)−0.7 pts
5. at OUQ3 11:11 4th & 4 at ARIZ 47, down 8Punted; the numbers favored going for it (close call)−0.6 pts
6. at USCQ3 10:20 4th & 4 at USC 5, up 3Kicked a field goal; the numbers favored going for it (close call)−0.6 pts
7. vs ORSTQ1 1:34 4th & 5 at ORST 34, down 7Kicked a field goal; the numbers favored going for it (close call)−0.4 pts
8. vs UTAHQ2 5:42 4th & 4 at UTAH 48, up 28Punted; the numbers favored going for it (close call)−0.4 pts

Record vs. expectation, 2023

9th of 133 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

   NAU
2. L

   MSST
3. W

   UTEP
4. W

   STAN
5. L

   WASH
6. L

   USC
7. W

   WSU
8. W

   ORST
9. W

   UCLA
10. W

    COLO
11. W

    UTAH
12. W

    ASU
13. W

    OU

What moved it, 2023

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+2.68
• Clock−0.08
• Timeouts+0.30
• Less the pregame edge, counted before kickoff+0.01

Game by game

• NAUW 38-3 vs NAU96% → 100%Before kickoff +46 · On the field +4: Scoreboard +6
• MSSTL 24-31 at MSST29% → 12%Before kickoff −21 · On the field −17: Scoreboard −27, Timeouts +16
• UTEPW 31-10 vs UTEP92% → 100%Before kickoff +42 · On the field +8: Scoreboard +12
• STANW 21-20 at STAN84% → 93%Before kickoff +34 · On the field +9: Scoreboard +28, Clock +2
• WASHL 24-31 vs WASH11% → 5%Before kickoff −39 · On the field −6: Scoreboard −23, Clock −1
• USCL 41-43 at USC8% → 15%Before kickoff −42 · On the field +6: Scoreboard −19, Timeouts +11
• WSUW 44-6 at WSU33% → 100%Before kickoff −17 · On the field +67: Scoreboard +63, Clock +2
• ORSTW 27-24 vs ORST47% → 96%Before kickoff −3 · On the field +49: Scoreboard +37, Timeouts +1
• UCLAW 27-10 vs UCLA52% → 99%Before kickoff +2 · On the field +47: Scoreboard +43
• COLOW 34-31 at COLO76% → 94%Before kickoff +26 · On the field +17: Scoreboard +34, Clock +2
• UTAHW 42-18 vs UTAH55% → 100%Before kickoff +5 · On the field +45: Scoreboard +41, Timeouts +1
• ASUW 59-23 at ASU83% → 100%Before kickoff +33 · On the field +17: Scoreboard +23, Clock +1
• OUW 38-24 at OU54% → 98%Before kickoff +4 · On the field +44: Scoreboard +49, Clock +3

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.