Texas Tech

Profile vs. FBS, 2023

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+0.0837th
  Defense+0.0860th
• 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.
  Offense42.6%56th
  Defense40.7%62nd
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.1922nd
  Defense+1.2461st
• Rushing EPA

  EPA per designed run.
  Offense+0.1781st
  Defense+0.0942nd
• Passing EPA

  EPA per pass play.
  Offense+0.1020th
  Defense+0.1674th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense49.2%66th
  Defense46.2%62nd
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense27.4%27th
  Defense28.2%73rd
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.3689th
  Defense3.1440th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense15.0%70th
  Defense16.5%44th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense14.8%70th
  Defense15.0%23rd

Percentiles among the 133 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, 2023

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 Texas Tech 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. L
   ORE
3. W
   TAR
4. L
   WVU
5. W
   HOU
6. W
   BAY
7. L
   KSU
8. L
   BYU
9. W
   TCU
10. W
    KU
11. W
    UCF
12. L
    TEX
13. W
    CAL

Bars above the line: better than expected for Texas Tech.

Players, 2023

1. Tahj BrooksRB268 plays · +0.188 pts/play · 1st of 383 RBs
   0.94WAR0.71 to 1.16
2. Tyler ShoughQB123 plays · +0.221 pts/play · 126th of 250 QBs
   0.51WAR0.26 to 0.77
3. Behren MortonQB288 plays · +0.072 pts/play · 142nd of 250 QBs
   0.39WAR−0.13 to 0.98
4. Xavier WhiteWR38 plays · +0.232 pts/play · 102nd of 457 WRs
   0.17WAR0.08 to 0.27
5. Coy EakinWR42 plays · +0.184 pts/play · 118th of 457 WRs
   0.14WAR0.07 to 0.22
6. Jerand BradleyWR32 plays · +0.212 pts/play · 140th of 457 WRs
   0.13WAR0.06 to 0.19
7. Gino GarciaPK17 plays · +0.287 pts/play · 45th of 113 kickers
   0.09WAR0.05 to 0.14
8. Austin McNamaraP42 plays · +0.095 pts/play · 63rd of 103 punters
   0.07WAR0.01 to 0.14

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 Texas Tech'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, 2023

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  69469440th of 130Roster talent: 694, 40th of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  19219246th of 130Recruiting: 192, 46th of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  76%76%22nd of 128Returning production: 76%, 22nd 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+6.143rd of 130SP+ rating: +6.1, 43rd 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, 2023

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 Texas Tech'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 0.05 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. at KUQ3 6:45 4th & 2 at midfield, up 10Punted; the numbers favored going for it−2.1 pts
2. at WVUQ4 15:00 4th & 9 at TTU 44, down 10Went for it; the numbers favored punting−1.4 pts
3. at KUQ4 9:39 4th & 2 at TTU 43, up 6Punted; the numbers favored going for it−1.3 pts
4. at BYUQ3 11:51 4th & 4 at TTU 32, down 17Went for it; the numbers favored punting (close call)−0.8 pts
5. at WVUQ4 0:19 4th & 10 at WVU 11, down 7Went for it; the numbers favored a field goal (close call)−0.5 pts
6. vs TCUQ4 2:18 4th & 5 at TCU 46, up 7Punted; the numbers favored going for it (close call)−0.5 pts
7. vs TARQ3 10:50 4th & 2 at TTU 48, up 24Punted; the numbers favored going for it (close call)−0.1 pts
8. at WYOQ2 8:53 4th & 4 at TTU 46, up 7Punted; the numbers favored going for it (close call)−0.1 pts

Record vs. expectation, 2023

93rd of 133 FBS teams at beating the model's pregame expectations

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

1. L

   WYO
2. L

   ORE
3. W

   TAR
4. L

   WVU
5. W

   HOU
6. W

   BAY
7. L

   KSU
8. L

   BYU
9. W

   TCU
10. W

    KU
11. W

    UCF
12. L

    TEX
13. W

    CAL

What moved it, 2023

Every game starts at Texas Tech'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−0.13
• Possession & field position+0.05
• Clock−0.11
• Timeouts+0.22
• Other−0.01
• Less the pregame edge, counted before kickoff−0.71

Game by game

• WYOL 33-35 at WYO84% → 20%Before kickoff +34 · On the field −64: Scoreboard −35, Timeouts +24
• OREL 30-38 vs ORE31% → 7%Before kickoff −19 · On the field −24: Scoreboard −40, Clock −2
• TARW 41-3 vs TAR98% → 100%Before kickoff +48 · On the field +2: Scoreboard +3
• WVUL 13-20 at WVU70% → 4%Before kickoff +20 · On the field −65: Scoreboard −43, Timeouts −1
• HOUW 49-28 vs HOU78% → 100%Before kickoff +28 · On the field +21: Scoreboard +25, Clock +1
• BAYW 39-14 at BAY56% → 100%Before kickoff +6 · On the field +43: Scoreboard +49, Timeouts −1
• KSUL 21-38 vs KSU57% → 1%Before kickoff +7 · On the field −56: Scoreboard −55, Clock −3
• BYUL 14-27 at BYU66% → 2%Before kickoff +16 · On the field −64: Scoreboard −42, Timeouts −4
• TCUW 35-28 vs TCU62% → 96%Before kickoff +12 · On the field +34: Scoreboard +33, Timeouts +2
• KUW 16-13 at KU40% → 87%Before kickoff −10 · On the field +47: Scoreboard +42, Clock +4
• UCFW 24-23 vs UCF59% → 96%Before kickoff +9 · On the field +37: Scoreboard +32, Timeouts +3
• TEXL 7-57 at TEX15% → 0%Before kickoff −35 · On the field −15: Scoreboard −17
• CALW 34-14 vs CAL65% → 100%Before kickoff +15 · On the field +35: Scoreboard +35, Timeouts +1

Points of win probability, from Texas Tech's side.

Closest call

TTU 23-22 ISU (2024) - Texas Tech dropped to a 9.3% win probability before pulling it out.