Tulsa

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+0.2185th
  Defense+0.0574th
• 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.
  Offense47.2%84th
  Defense37.2%87th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.1845th
  Defense+1.2720th
• Rushing EPA

  EPA per designed run.
  Offense+0.1779th
  Defense+0.0269th
• Passing EPA

  EPA per pass play.
  Offense+0.3082nd
  Defense+0.1069th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense51.2%78th
  Defense41.8%89th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense38.0%83rd
  Defense29.2%87th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.2080th
  Defense2.8462nd
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense15.6%90th
  Defense19.8%54th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense12.6%93rd
  Defense16.0%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, 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 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
   SJSU
2. L
   OSU
3. W
   NCAT
4. W
   FRES
5. W
   SMU
6. L
   HOU
7. W
   TULN
8. W
   MEM
9. W
   ECU
10. L
    NAVY
11. W
    UCF
12. W
    CIN
13. W
    CMU

Bars above the line: better than expected for Tulsa.

Players, 2016

1. Dane EvansQB376 plays · +0.243 pts/play · 36th of 218 QBs
   1.71WAR1.02 to 2.36
2. James FlandersRB210 plays · +0.208 pts/play · 11th of 347 RBs
   0.82WAR0.59 to 1.04
3. D'Angelo BrewerRB203 plays · +0.180 pts/play · 22nd of 347 RBs
   0.68WAR0.47 to 0.89
4. Josh AtkinsonWR91 plays · +0.177 pts/play · 24th of 417 WRs
   0.30WAR0.17 to 0.43
5. Keevan LucasWR107 plays · +0.121 pts/play · 49th of 417 WRs
   0.24WAR0.09 to 0.39
6. Justin HobbsWR59 plays · +0.191 pts/play · 65th of 417 WRs
   0.21WAR0.13 to 0.29
7. Dalton ParksP45 plays · +0.207 pts/play · 27th of 82 punters
   0.17WAR0.06 to 0.29
8. Redford JonesPK20 plays · +0.342 pts/play · 37th of 116 kickers
   0.13WAR0.06 to 0.19

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, 2016

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  40940991st of 128Roster talent: 409, 91st of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  12512590th of 128Recruiting: 125, 90th of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  66%66%64th of 128Returning production: 66%, 64th of 128 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +7.4+7.450th of 128SP+ rating: +7.4, 50th 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 Tulsa'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 0.08 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 FRESQ2 15:00 4th & 1 at TLSA 30, down 21Punted; the numbers favored going for it−1.6 pts
2. at MEMQ3 6:21 4th & 3 at midfield, up 8Punted; the numbers favored going for it−1.3 pts
3. at FRESQ4 8:20 4th & 4 at FRES 20, up 1Kicked a field goal; the numbers favored going for it−1.3 pts
4. vs TULNQ2 7:05 4th & 2 at TULN 2, up 14Kicked a field goal; the numbers favored going for it−1.2 pts
5. at MEMQ2 11:16 4th & 3 at TLSA 47, up 7Punted; the numbers favored going for it (close call)−0.6 pts
6. at HOUQ3 13:07 4th & 4 at HOU 49, tiedPunted; the numbers favored going for it (close call)−0.4 pts
7. vs CINQ3 7:03 4th & 5 at midfield, down 3Punted; the numbers favored going for it (close call)−0.3 pts
8. at OSUQ2 14:48 4th & 1 at TLSA 44, tiedPunted; the numbers favored going for it (close call)−0.2 pts

Record vs. expectation, 2016

6th of 128 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

   SJSU
2. L

   OSU
3. W

   NCAT
4. W

   FRES
5. W

   SMU
6. L

   HOU
7. W

   TULN
8. W

   MEM
9. W

   ECU
10. L

    NAVY
11. W

    UCF
12. W

    CIN
13. W

    CMU

What moved it, 2016

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+2.84
• Possession & field position+0.03
• Clock+0.04
• Timeouts−0.20
• Less the pregame edge, counted before kickoff−0.53

Game by game

• SJSUW 45-10 vs SJSU67% → 100%Before kickoff +17 · On the field +33: Scoreboard +35, Timeouts −1
• OSUL 3-48 at OSU3% → 0%Before kickoff −47 · On the field −3: Scoreboard −6
• NCATW 58-21 vs NCAT95% → 100%Before kickoff +45 · On the field +5: Scoreboard +8
• FRESW 48-41 at FRES78% → 85%Before kickoff +28 · On the field +7: Scoreboard +28, Timeouts +13
• SMUW 43-40 vs SMU74% → 85%Before kickoff +24 · On the field +11: Scoreboard +31, Timeouts −18
• HOUL 31-38 at HOU6% → 16%Before kickoff −44 · On the field +10: Scoreboard −12, Possession & field position +2
• TULNW 50-27 vs TULN77% → 100%Before kickoff +27 · On the field +23: Scoreboard +26
• MEMW 59-30 at MEM32% → 100%Before kickoff −18 · On the field +68: Scoreboard +66, Possession & field position −1
• ECUW 45-24 vs ECU76% → 100%Before kickoff +26 · On the field +24: Scoreboard +27, Timeouts +1
• NAVYL 40-42 at NAVY53% → 14%Before kickoff +3 · On the field −39: Scoreboard −25, Timeouts −2
• UCFW 35-20 at UCF41% → 99%Before kickoff −9 · On the field +58: Scoreboard +58, Clock +3
• CINW 40-37 vs CIN88% → 86%Before kickoff +38 · On the field −2: Scoreboard +22, Timeouts −13
• CMUW 55-10 vs CMU76% → 100%Before kickoff +26 · On the field +24: Scoreboard +26

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.