Hawai'i

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−0.086th
  Defense+0.1914th
• 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.
  Offense36.9%10th
  Defense47.6%12th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2051st
  Defense+1.1568th
• Rushing EPA

  EPA per designed run.
  Offense−0.0221st
  Defense+0.0834th
• Passing EPA

  EPA per pass play.
  Offense−0.154th
  Defense+0.385th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense42.8%12th
  Defense50.9%19th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense25.8%7th
  Defense38.6%11th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.9463rd
  Defense3.0324th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense18.7%66th
  Defense18.4%30th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense3.1%10th
  Defense1.2%2nd

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 Hawai'i 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
   COLO
2. L
   OSU
3. W
   UCD
4. L
   WIS
5. L
   BOIS
6. L
   SDSU
7. L
   UNM
8. L
   NEV
9. L
   AF
10. L
    UNLV
11. L
    FRES
12. L
    SJSU
13. W
    ULM

Bars above the line: better than expected for Hawai'i.

Players, 2015

1. Paul HarrisRB146 plays · +0.148 pts/play · 38th of 333 RBs
   0.40WAR0.26 to 0.52
2. Max WittekQB144 plays · +0.124 pts/play · 152nd of 205 QBs
   0.33WAR0.13 to 0.55
3. Ikaika WoolseyQB141 plays · +0.121 pts/play · 158th of 205 QBs
   0.32WAR0.08 to 0.56
4. Dylan CollieWR35 plays · +0.100 pts/play · 292nd of 411 WRs
   0.07WAR0.02 to 0.11
5. Steven LakalakaRB30 plays · +0.094 pts/play · 239th of 333 RBs
   0.05WAR0.03 to 0.07
6. Marcus KempWR25 plays · +0.094 pts/play · 335th of 411 WRs
   0.04WAR0.01 to 0.08
7. Devan StubblefieldWR35 plays · +0.054 pts/play · 351st of 411 WRs
   0.04WAR0.00 to 0.07
8. Quinton PedrozaWR17 plays · +0.059 pts/play · 374th of 411 WRs
   0.02WAR−0.01 to 0.04

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 Hawai'i'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.
  38638695th of 128Roster talent: 386, 95th of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  103103114th of 128Recruiting: 103, 114th of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  75%75%39th of 127Returning production: 75%, 39th of 127 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −16.3−16.3117th of 128SP+ rating: −16.3, 117th 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 Hawai'i'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 0.02 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. vs SDSUQ3 4:33 4th & 2 at HAW 44, down 7Punted; the numbers favored going for it1.2 pts
2. vs SDSUQ3 11:30 4th & 4 at SDSU 42, down 14Punted; the numbers favored going for it1.1 pts
3. at UNLVQ2 1:01 4th & 3 at UNLV 44, down 7Punted; the numbers favored going for it (close call)1.0 pts
4. vs SDSUQ3 14:51 4th & 14 at SDSU 36, down 14Went for it; the numbers favored a field goal (close call)0.7 pts
5. vs ULMQ3 3:35 4th & 8 at ULM 39, up 8Punted; the numbers favored going for it (close call)0.6 pts
6. vs SJSUQ1 6:18 4th & 2 at HAW 29, down 14Punted; the numbers favored going for it (close call)0.4 pts
7. at UNMQ4 12:59 4th & 5 at UNM 30, up 3Kicked a field goal; the numbers favored going for it (close call)0.4 pts
8. vs FRESQ2 10:47 4th & 4 at HAW 19, down 7Punted; the numbers favored going for it (close call)0.3 pts

Record vs. expectation, 2015

125th of 128 FBS teams at beating the model's pregame expectations

Expected wins adds up Hawai'i's chance of winning each game as the model saw it at kickoff - a 70% favorite counts 0.7. Based on 12 of 13 games; one has no play-by-play to score.

1. W

   COLO
2. L

   OSU
3. W

   UCD
4. L

   WIS
5. L

   BOIS
6. L

   SDSU
7. L

   UNM
8. L

   NEV
9. L

   AF
10. L

    UNLV
11. L

    FRES
12. L

    SJSU
13. W

    ULM

What moved it, 2015

Every game starts at Hawai'i'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−2.59
• Clock−0.07
• Timeouts+0.04
• Less the pregame edge, counted before kickoff+0.24

Game by game

• OSUL 0-38 at OSU1% → 0%Before kickoff −49 · On the field −1: Scoreboard −2
• UCDW 47-27 vs UCD95% → 100%Before kickoff +45 · On the field +5: Scoreboard +8
• WISL 0-28 at WIS4% → 0%Before kickoff −46 · On the field −4: Scoreboard −6
• BOISL 0-55 at BOIS7% → 0%Before kickoff −43 · On the field −7: Scoreboard −10
• SDSUL 14-28 vs SDSU42% → 2%Before kickoff −8 · On the field −40: Scoreboard −46, Clock −3
• UNML 27-28 at UNM38% → 11%Before kickoff −12 · On the field −27: Scoreboard −30, Timeouts +5
• NEVL 20-30 at NEV34% → 4%Before kickoff −16 · On the field −30: Scoreboard −32, Timeouts −2
• AFL 7-58 vs AF31% → 0%Before kickoff −19 · On the field −31: Scoreboard −37
• UNLVL 21-41 at UNLV34% → 0%Before kickoff −16 · On the field −34: Scoreboard −34, Timeouts −1
• FRESL 14-42 vs FRES62% → 0%Before kickoff +12 · On the field −62: Scoreboard −59, Clock −2
• SJSUL 23-42 vs SJSU23% → 1%Before kickoff −27 · On the field −23: Scoreboard −31, Clock −1
• ULMW 28-26 vs ULM71% → 86%Before kickoff +21 · On the field +15: Scoreboard +20, Timeouts +1

Points of win probability, from Hawai'i's side.

Closest call

STAN 20-23 HAW (2025) - Hawai'i dropped to a 0.3% win probability before pulling it out.