Tulsa

Profile vs. FBS, 2022

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+0.1560th
  Defense+0.1433rd
• 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.
  Offense41.6%45th
  Defense39.9%69th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.3382nd
  Defense+1.3418th
• Rushing EPA

  EPA per designed run.
  Offense+0.0947th
  Defense+0.1132nd
• Passing EPA

  EPA per pass play.
  Offense+0.2661st
  Defense+0.2632nd
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense46.9%42nd
  Defense45.1%73rd
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense30.1%42nd
  Defense30.1%55th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.1253rd
  Defense3.1338th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense16.1%61st
  Defense13.9%19th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense17.3%32nd
  Defense15.0%33rd

Percentiles among the 131 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, 2022

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. L
   WYO
2. W
   NIU
3. W
   JXST
4. L
   MISS
5. L
   CIN
6. L
   NAVY
7. W
   TEM
8. L
   SMU
9. L
   TULN
10. L
    MEM
11. W
    USF
12. W
    HOU

Bars above the line: better than expected for Tulsa.

Players, 2022

1. Davis BrinQB267 plays · +0.194 pts/play · 78th of 234 QBs
   0.97WAR0.37 to 1.58
2. Braylon BraxtonQB178 plays · +0.241 pts/play · 96th of 234 QBs
   0.80WAR0.45 to 1.19
3. Keylon StokesWR91 plays · +0.193 pts/play · 9th of 455 WRs
   0.33WAR0.17 to 0.49
4. Deneric PrinceRB124 plays · +0.117 pts/play · 108th of 384 RBs
   0.27WAR0.16 to 0.39
5. JuanCarlos SantanaWR76 plays · +0.112 pts/play · 96th of 455 WRs
   0.16WAR0.02 to 0.32
6. Steven AndersonRB78 plays · +0.109 pts/play · 189th of 384 RBs
   0.16WAR0.08 to 0.22
7. Isaiah EppsWR50 plays · +0.143 pts/play · 145th of 455 WRs
   0.13WAR0.05 to 0.23
8. Jordan FordRB51 plays · +0.136 pts/play · 227th of 384 RBs
   0.13WAR0.10 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 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, 2022

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  48648683rd of 129Roster talent: 486, 83rd of 129 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  121121116th of 129Recruiting: 121, 116th of 129 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  59%59%65th of 128Returning production: 59%, 65th of 128 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −6.1−6.186th of 129SP+ rating: −6.1, 86th of 129 in FBS

Ranks and bars among the 129 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, 2022

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 3 clear-cut ones account for 0.04 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 MEMQ3 8:05 4th & 1 at TLSA 19, down 17Punted; the numbers favored going for it−1.9 pts
2. vs TULNQ3 12:40 4th & 3 at TULN 48, down 7Punted; the numbers favored going for it−1.1 pts
3. at MISSQ3 10:16 4th & 2 at MISS 2, down 18Kicked a field goal; the numbers favored going for it−1.0 pts
4. at MEMQ4 5:39 4th & 10 at MEM 23, down 20Went for it; the numbers favored a field goal (close call)−0.7 pts
5. at MISSQ4 14:38 4th & 7 at MISS 17, down 15Went for it; the numbers favored a field goal (close call)−0.5 pts
6. vs USFQ4 1:17 4th & 6 at USF 41, up 6Punted; the numbers favored going for it (close call)−0.5 pts
7. vs NIUQ3 4:08 4th & 4 at NIU 22, up 3Kicked a field goal; the numbers favored going for it (close call)−0.4 pts
8. at MEMQ4 13:00 4th & 6 at MEM 20, down 20Went for it; the numbers favored a field goal (close call)−0.4 pts

Record vs. expectation, 2022

104th of 131 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. L

   WYO
2. W

   NIU
3. W

   JXST
4. L

   MISS
5. L

   CIN
6. L

   NAVY
7. W

   TEM
8. L

   SMU
9. L

   TULN
10. L

    MEM
11. W

    USF
12. W

    HOU

What moved it, 2022

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−0.91
• Possession & field position−0.03
• Clock−0.19
• Timeouts+0.24
• Less the pregame edge, counted before kickoff+0.03

Game by game

• WYOL 37-40 at WYO69% → 15%Before kickoff +19 · On the field −54: Scoreboard −25, Timeouts +21
• NIUW 38-35 vs NIU65% → 96%Before kickoff +15 · On the field +32: Scoreboard +31, Timeouts +2
• JXSTW 54-17 vs JXST83% → 100%Before kickoff +33 · On the field +17: Scoreboard +21
• MISSL 27-35 at MISS9% → 2%Before kickoff −41 · On the field −7: Scoreboard −14, Timeouts −1
• CINL 21-31 vs CIN26% → 5%Before kickoff −24 · On the field −21: Scoreboard −35, Clock −2
• NAVYL 21-53 at NAVY69% → 0%Before kickoff +19 · On the field −69: Scoreboard −62, Timeouts +2
• TEMW 27-16 at TEM80% → 97%Before kickoff +30 · On the field +17: Scoreboard +30, Clock +2
• SMUL 34-45 vs SMU45% → 3%Before kickoff −5 · On the field −42: Scoreboard −48, Clock −3
• TULNL 13-27 vs TULN28% → 1%Before kickoff −22 · On the field −27: Scoreboard −35, Clock −1
• MEML 10-26 at MEM29% → 1%Before kickoff −21 · On the field −28: Scoreboard −29, Timeouts −1
• USFW 48-42 vs USF82% → 97%Before kickoff +32 · On the field +15: Scoreboard +21, Timeouts +1
• HOUW 37-30 at HOU16% → 96%Before kickoff −34 · On the field +81: Scoreboard +56, Clock +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.