Tulsa

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+0.0521st
  Defense+0.0857th
• 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.
  Offense43.2%44th
  Defense44.4%35th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.099th
  Defense+1.0694th
• Rushing EPA

  EPA per designed run.
  Offense+0.0850th
  Defense+0.1034th
• Passing EPA

  EPA per pass play.
  Offense+0.0318th
  Defense+0.0773rd
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense47.1%38th
  Defense49.1%34th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense35.0%64th
  Defense34.0%38th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.9247th
  Defense3.1416th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense18.4%66th
  Defense15.8%10th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense19.1%11th
  Defense14.1%15th

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 Tulsa 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
   CARK
2. L
   TEX
3. L
   ARST
4. L
   TEM
5. L
   HOU
6. L
   USF
7. L
   ARK
8. L
   TULN
9. W
   CONN
10. L
    MEM
11. L
    NAVY
12. W
    SMU

Bars above the line: better than expected for Tulsa.

Players, 2018

1. Shamari BrooksRB188 plays · +0.169 pts/play · 38th of 351 RBs
   0.60WAR0.44 to 0.76
2. Corey Taylor IIRB132 plays · +0.223 pts/play · 47th of 351 RBs
   0.55WAR0.43 to 0.66
3. Seth BoomerQB209 plays · +0.120 pts/play · 143rd of 225 QBs
   0.47WAR0.14 to 0.84
4. Luke SkipperQB97 plays · +0.149 pts/play · 170th of 225 QBs
   0.27WAR0.09 to 0.46
5. Keylon StokesWR60 plays · +0.129 pts/play · 107th of 434 WRs
   0.14WAR0.09 to 0.21
6. Nathan WalkerPK15 plays · +0.300 pts/play · 78th of 112 kickers
   0.08WAR0.05 to 0.12
7. Justin HobbsWR50 plays · +0.055 pts/play · 311th of 434 WRs
   0.05WAR−0.01 to 0.13
8. Thomas BennettP42 plays · +0.041 pts/play · 71st of 91 punters
   0.03WAR−0.02 to 0.08

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 Tulsa'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.
  368368108th of 130Roster talent: 368, 108th of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  12912993rd of 130Recruiting: 129, 93rd of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  74%74%46th of 129Returning production: 74%, 46th of 129 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −11.2−11.2107th of 130SP+ rating: −11.2, 107th 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 Tulsa's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 1 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 CARKQ3 1:25 4th & 2 at CARK 22, up 1Kicked a field goal; the numbers favored going for it−1.9 pts
2. vs SMUQ4 8:36 4th & 3 at TLSA 40, up 7Punted; the numbers favored going for it (close call)−0.8 pts
3. at NAVYQ3 10:06 4th & 12 at NAVY 33, down 11Went for it; the numbers favored a field goal (close call)−0.7 pts
4. at TEMQ3 8:52 4th & 4 at TEM 30, down 18Kicked a field goal; the numbers favored going for it (close call)−0.7 pts
5. vs ARSTQ2 9:38 4th & 2 at TLSA 28, up 4Punted; the numbers favored going for it (close call)−0.6 pts
6. vs CARKQ2 12:56 4th & 1 at TLSA 16, up 1Punted; the numbers favored going for it (close call)−0.5 pts
7. at HOUQ4 10:43 4th & 3 at TLSA 33, up 2Punted; the numbers favored going for it (close call)−0.5 pts
8. vs SMUQ1 1:54 4th & 4 at SMU 25, up 7Kicked a field goal; the numbers favored going for it (close call)−0.3 pts

Record vs. expectation, 2018

125th of 130 FBS teams at beating the model's pregame expectations

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

1. W

   CARK
2. L

   TEX
3. L

   ARST
4. L

   TEM
5. L

   HOU
6. L

   USF
7. L

   ARK
8. L

   TULN
9. W

   CONN
10. L

    MEM
11. L

    NAVY
12. W

    SMU

What moved it, 2018

Every game starts at Tulsa'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−2.23
• Possession & field position−0.02
• Clock−0.09
• Timeouts−0.03
• Less the pregame edge, counted before kickoff+0.52

Game by game

• CARKW 38-27 vs CARK82% → 96%Before kickoff +32 · On the field +14: Scoreboard +21, Timeouts +1
• TEXL 21-28 at TEX7% → 3%Before kickoff −43 · On the field −4: Scoreboard −12, Timeouts −1
• ARSTL 20-29 vs ARST53% → 7%Before kickoff +3 · On the field −45: Scoreboard −48, Possession & field position −1
• TEML 17-31 at TEM34% → 2%Before kickoff −16 · On the field −33: Scoreboard −33, Timeouts −1
• HOUL 26-41 at HOU14% → 1%Before kickoff −36 · On the field −13: Scoreboard −19, Timeouts −1
• USFL 24-25 vs USF30% → 5%Before kickoff −20 · On the field −26: Scoreboard −36, Clock −2
• ARKL 0-23 at ARK34% → 0%Before kickoff −16 · On the field −33: Scoreboard −34, Timeouts −1
• TULNL 17-24 vs TULN56% → 6%Before kickoff +6 · On the field −50: Scoreboard −51, Clock −3
• CONNW 49-19 vs CONN90% → 100%Before kickoff +40 · On the field +10: Scoreboard +13
• MEML 21-47 at MEM17% → 0%Before kickoff −33 · On the field −17: Scoreboard −20
• NAVYL 29-37 at NAVY36% → 3%Before kickoff −14 · On the field −33: Scoreboard −33, Timeouts −2
• SMUW 27-24 vs SMU44% → 88%Before kickoff −6 · On the field +44: Scoreboard +31, Timeouts +3

Points of win probability, from Tulsa's side.

Closest call

UTSA 45-46 TLSA (2024) - Tulsa dropped to a 1.6% win probability before pulling it out.