Texas Tech

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+0.1457th
  Defense+0.1822nd
• 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.
  Offense48.9%90th
  Defense44.6%33rd
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.078th
  Defense+1.2244th
• Rushing EPA

  EPA per designed run.
  Offense0.0024th
  Defense+0.0747th
• Passing EPA

  EPA per pass play.
  Offense+0.2468th
  Defense+0.2918th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense54.1%93rd
  Defense50.5%24th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense37.8%84th
  Defense32.1%58th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.5916th
  Defense3.0922nd
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense22.4%21st
  Defense18.3%35th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense13.6%78th
  Defense16.1%50th

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 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
   MISS
2. W
   LAM
3. W
   HOU
4. W
   OKST
5. L
   WVU
6. W
   TCU
7. W
   KU
8. L
   ISU
9. L
   OU
10. L
    TEX
11. L
    KSU
12. L
    BAY

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

Players, 2018

1. Alan BowmanQB292 plays · +0.268 pts/play · 54th of 225 QBs
   1.46WAR0.99 to 1.94
2. Jett DuffeyQB186 plays · +0.204 pts/play · 109th of 225 QBs
   0.71WAR0.36 to 1.07
3. Antoine WesleyWR109 plays · +0.158 pts/play · 8th of 434 WRs
   0.32WAR0.18 to 0.48
4. Da'Leon WardRB109 plays · +0.119 pts/play · 183rd of 351 RBs
   0.24WAR0.18 to 0.30
5. Ta'Zhawn HenryRB82 plays · +0.130 pts/play · 211th of 351 RBs
   0.20WAR0.15 to 0.25
6. Ja'Deion HighWR66 plays · +0.157 pts/play · 43rd of 434 WRs
   0.19WAR0.11 to 0.29
7. T.J. VasherWR71 plays · +0.144 pts/play · 45th of 434 WRs
   0.19WAR0.09 to 0.31
8. McLane CarterQB54 plays · +0.178 pts/play · 186th of 225 QBs
   0.18WAR0.10 to 0.27

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, 2018

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  56256259th of 130Roster talent: 562, 59th of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  18518546th of 130Recruiting: 185, 46th of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  16%16%127th of 129Returning production: 16%, 127th of 129 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +8.7+8.737th of 130SP+ rating: +8.7, 37th 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 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 0.06 of the 0.09 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 TCUQ4 14:16 4th & 3 at midfield, up 3Punted; the numbers favored going for it−2.4 pts
2. at OKSTQ4 11:31 4th & 1 at OKST 14, up 17Kicked a field goal; the numbers favored going for it−1.8 pts
3. at ISUQ4 13:37 4th & 20 at ISU 34, down 7Punted; the numbers favored a field goal−1.7 pts
4. vs MISSQ4 9:11 4th & 14 at MISS 14, down 17Went for it; the numbers favored a field goal (close call)−0.7 pts
5. vs HOUQ2 15:00 4th & 13 at HOU 35, down 7Punted; the numbers favored a field goal (close call)−0.5 pts
6. vs KUQ2 11:54 4th & 1 at TTU 12, up 7Punted; the numbers favored going for it (close call)−0.5 pts
7. vs MISSQ4 0:12 4th & 5 at MISS 5, down 20Went for it; the numbers favored a field goal (close call)−0.3 pts
8. at ISUQ1 1:28 4th & 4 at ISU 9, up 7Kicked a field goal; the numbers favored going for it (close call)−0.2 pts

Record vs. expectation, 2018

80th of 130 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

   MISS
2. W

   LAM
3. W

   HOU
4. W

   OKST
5. L

   WVU
6. W

   TCU
7. W

   KU
8. L

   ISU
9. L

   OU
10. L

    TEX
11. L

    KSU
12. L

    BAY

What moved it, 2018

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−0.96
• Possession & field position−0.02
• Clock−0.04
• Timeouts−0.01
• Less the pregame edge, counted before kickoff+0.90

Game by game

• MISSL 27-47 vs MISS40% → 0%Before kickoff −10 · On the field −40: Scoreboard −45, Clock −2
• LAMW 77-0 vs LAM100% → 100%Before kickoff +50 · On the field 0: Scoreboard +1
• HOUW 63-49 vs HOU54% → 98%Before kickoff +4 · On the field +45: Scoreboard +39, Timeouts +1
• OKSTW 41-17 at OKST15% → 99%Before kickoff −35 · On the field +84: Scoreboard +66, Clock +2
• WVUL 34-42 vs WVU34% → 11%Before kickoff −16 · On the field −23: Scoreboard −43, Possession & field position +4
• TCUW 17-14 at TCU27% → 94%Before kickoff −23 · On the field +68: Scoreboard +54, Clock +3
• KUW 48-16 vs KU83% → 100%Before kickoff +33 · On the field +17: Scoreboard +19
• ISUL 31-40 at ISU31% → 3%Before kickoff −19 · On the field −28: Scoreboard −29, Timeouts −1
• OUL 46-51 vs OU14% → 15%Before kickoff −36 · On the field +2: Scoreboard −24, Possession & field position −2
• TEXL 34-41 vs TEX33% → 11%Before kickoff −17 · On the field −22: Scoreboard −36, Clock −3
• KSUL 6-21 at KSU63% → 2%Before kickoff +13 · On the field −61: Scoreboard −46, Timeouts −2
• BAYL 24-35 vs BAY58% → 3%Before kickoff +8 · On the field −55: Scoreboard −53, Clock −3

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.