Tulsa

Profile vs. FBS, 2014

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+0.1232nd
  Defense+0.294th
• 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%37th
  Defense44.4%30th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.1013th
  Defense+1.471st
• Rushing EPA

  EPA per designed run.
  Offense+0.0530th
  Defense+0.2013th
• Passing EPA

  EPA per pass play.
  Offense+0.2048th
  Defense+0.388th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense47.4%47th
  Defense48.2%41st
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense30.2%21st
  Defense36.5%20th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.0563rd
  Defense2.8453rd
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense16.3%81st
  Defense24.0%90th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense2.9%10th
  Defense1.4%13th

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, 2014

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
   TULN
2. L
   OU
3. L
   FAU
4. L
   TXST
5. L
   CSU
6. L
   TEM
7. L
   USF
8. L
   MEM
9. W
   SMU
10. L
    UCF
11. L
    HOU
12. L
    ECU

Bars above the line: better than expected for Tulsa.

Players, 2014

1. Dane EvansQB401 plays · +0.261 pts/play · 29th of 199 QBs
   1.96WAR1.29 to 2.63
2. Keevan LucasWR121 plays · +0.140 pts/play · 24th of 469 WRs
   0.32WAR0.14 to 0.52
3. Zack LangerRB161 plays · +0.076 pts/play · 99th of 350 RBs
   0.23WAR0.08 to 0.38
4. James FlandersRB86 plays · +0.103 pts/play · 140th of 350 RBs
   0.17WAR0.10 to 0.23
5. Keyarris GarrettWR68 plays · +0.129 pts/play · 108th of 469 WRs
   0.16WAR0.03 to 0.28
6. Dalton ParksP56 plays · +0.104 pts/play · 38th of 94 punters
   0.11WAR−0.01 to 0.23
7. Carl SalazarPK14 plays · +0.307 pts/play · 84th of 114 kickers
   0.08WAR0.04 to 0.12
8. Joshua AtkinsonWR44 plays · +0.087 pts/play · 275th of 469 WRs
   0.07WAR0.03 to 0.12

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

Fourth-down calls vs. the numbers, 2014

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 5 clear-cut ones account for 0.09 of the 0.15 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 USFQ2 0:00 4th & 2 at USF 2, up 17Kicked a field goal; the numbers favored going for it−3.8 pts
2. at TEMQ4 8:34 4th & 2 at TLSA 29, down 4Punted; the numbers favored going for it−1.6 pts
3. vs USFQ2 6:36 4th & 3 at TLSA 48, up 17Punted; the numbers favored going for it−1.4 pts
4. vs TXSTQ3 5:56 4th & 3 at TXST 3, down 14Kicked a field goal; the numbers favored going for it−1.3 pts
5. vs TULNQ2 5:26 4th & 1 at TLSA 35, down 14Punted; the numbers favored going for it−1.2 pts
6. at MEMQ4 12:06 4th & 19 at MEM 35, down 12Went for it; the numbers favored a field goal (close call)−1.0 pts
7. vs ECUQ3 7:07 4th & 12 at ECU 31, down 11Went for it; the numbers favored a field goal (close call)−0.9 pts
8. vs TULNQ1 1:00 4th & 2 at TULN 6, down 7Kicked a field goal; the numbers favored going for it (close call)−0.9 pts

Record vs. expectation, 2014

112th 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

   TULN
2. L

   OU
3. L

   FAU
4. L

   TXST
5. L

   CSU
6. L

   TEM
7. L

   USF
8. L

   MEM
9. W

   SMU
10. L

    UCF
11. L

    HOU
12. L

    ECU

What moved it, 2014

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−1.92
• Possession & field position−0.03
• Clock+0.24
• Timeouts−0.39
• Less the pregame edge, counted before kickoff+0.50

Game by game

• TULNW 38-31 vs TULN60% → 82%Before kickoff +10 · On the field +22: Scoreboard +29, Timeouts −20
• OUL 7-52 vs OU6% → 0%Before kickoff −44 · On the field −6: Scoreboard −10
• FAUL 21-50 at FAU55% → 0%Before kickoff +5 · On the field −55: Scoreboard −50, Possession & field position +1
• TXSTL 34-37 vs TXST61% → 11%Before kickoff +11 · On the field −50: Scoreboard −43, Timeouts −19
• CSUL 17-42 at CSU15% → 0%Before kickoff −35 · On the field −15: Scoreboard −18, Clock −1
• TEML 24-35 at TEM16% → 1%Before kickoff −34 · On the field −15: Scoreboard −21
• USFL 30-38 vs USF37% → 3%Before kickoff −13 · On the field −34: Scoreboard −44, Clock −3
• MEML 20-40 at MEM7% → 0%Before kickoff −43 · On the field −7: Scoreboard −11
• SMUW 38-28 vs SMU76% → 96%Before kickoff +26 · On the field +20: Scoreboard +26, Timeouts +1
• UCFL 7-31 at UCF11% → 0%Before kickoff −39 · On the field −10: Scoreboard −16
• HOUL 28-38 at HOU7% → 4%Before kickoff −43 · On the field −3: Scoreboard −14
• ECUL 32-49 vs ECU11% → 1%Before kickoff −39 · On the field −9: Scoreboard −20, Clock −1

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.