Texas Tech

Profile vs. FBS, 2015

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+0.2594th
  Defense+0.293rd
• 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.
  Offense49.3%91st
  Defense50.5%2nd
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2783rd
  Defense+1.2620th
• Rushing EPA

  EPA per designed run.
  Offense+0.2394th
  Defense+0.283rd
• Passing EPA

  EPA per pass play.
  Offense+0.2976th
  Defense+0.3111th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense53.2%89th
  Defense55.1%3rd
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense41.0%91st
  Defense39.0%10th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.4698th
  Defense3.422nd
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense14.5%95th
  Defense17.3%23rd
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense2.0%48th
  Defense1.6%25th

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, 2015

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. W
   SHSU
2. W
   UTEP
3. W
   ARK
4. L
   TCU
5. L
   BAY
6. W
   ISU
7. W
   KU
8. L
   OU
9. L
   OKST
10. L
    WVU
11. W
    KSU
12. W
    TEX
13. L
    LSU

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

Players, 2015

1. Patrick MahomesQB575 plays · +0.270 pts/play · 8th of 205 QBs
   2.91WAR2.05 to 3.81
2. DeAndre WashingtonRB242 plays · +0.125 pts/play · 13th of 333 RBs
   0.57WAR0.37 to 0.77
3. Jakeem GrantWR114 plays · +0.105 pts/play · 62nd of 411 WRs
   0.22WAR0.04 to 0.42
4. Devin LauderdaleWR48 plays · +0.188 pts/play · 104th of 411 WRs
   0.17WAR0.08 to 0.26
5. Ian SadlerWR50 plays · +0.175 pts/play · 112th of 411 WRs
   0.16WAR0.09 to 0.24
6. Justin StocktonRB63 plays · +0.118 pts/play · 168th of 333 RBs
   0.14WAR0.08 to 0.20
7. Clayton HatfieldPK13 plays · +0.498 pts/play · 51st of 115 kickers
   0.12WAR0.09 to 0.15
8. Reginald Davis IIIWR52 plays · +0.118 pts/play · 172nd of 411 WRs
   0.11WAR0.04 to 0.18

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, 2015

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  64164135th of 128Roster talent: 641, 35th of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  19819838th of 128Recruiting: 198, 38th of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  82%82%26th of 127Returning production: 82%, 26th of 127 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +4.5+4.560th of 128SP+ rating: +4.5, 60th 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, 2015

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 1 clear-cut ones account for 0.01 of the 0.05 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 OKSTQ3 11:11 4th & 7 at TTU 41, up 10Went for it; the numbers favored punting−1.4 pts
2. at KUQ4 6:20 4th & 15 at KU 37, up 3Punted; the numbers favored a field goal (close call)−0.8 pts
3. at TEXQ2 6:15 4th & 7 at TEX 40, up 7Punted; the numbers favored going for it (close call)−0.7 pts
4. vs LSUQ4 13:00 4th & 15 at LSU 36, down 22Went for it; the numbers favored a field goal (close call)−0.6 pts
5. vs OKSTQ3 8:51 4th & 3 at TTU 27, up 10Punted; the numbers favored going for it (close call)−0.3 pts
6. at ARKQ4 1:44 4th & 4 at ARK 4, up 11Kicked a field goal; the numbers favored going for it (close call)−0.2 pts
7. at BAYQ3 2:35 4th & 17 at BAY 43, down 28Went for it; the numbers favored punting (close call)−0.2 pts
8. at WVUQ3 14:53 4th & 10 at WVU 37, down 3Punted; the numbers favored going for it (close call)−0.1 pts

Record vs. expectation, 2015

52nd of 128 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. W

   SHSU
2. W

   UTEP
3. W

   ARK
4. L

   TCU
5. L

   BAY
6. W

   ISU
7. W

   KU
8. L

   OU
9. L

   OKST
10. L

    WVU
11. W

    KSU
12. W

    TEX
13. L

    LSU

What moved it, 2015

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+0.24
• Possession & field position+0.02
• Clock+0.03
• Timeouts+0.01
• Less the pregame edge, counted before kickoff+0.25

Game by game

• SHSUW 59-45 vs SHSU75% → 99%Before kickoff +25 · On the field +23: Scoreboard +26, Timeouts +1
• UTEPW 69-20 vs UTEP91% → 100%Before kickoff +41 · On the field +9: Scoreboard +11
• ARKW 35-24 at ARK22% → 98%Before kickoff −28 · On the field +76: Scoreboard +61, Clock +4
• TCUL 52-55 vs TCU26% → 17%Before kickoff −24 · On the field −9: Scoreboard −31, Clock −3
• BAYL 35-63 at BAY16% → 0%Before kickoff −34 · On the field −16: Scoreboard −19
• ISUW 66-31 vs ISU80% → 100%Before kickoff +30 · On the field +20: Scoreboard +23
• KUW 30-20 at KU96% → 96%Before kickoff +46 · On the field 0: Scoreboard +12, Clock +1
• OUL 27-63 at OU15% → 0%Before kickoff −35 · On the field −15: Scoreboard −18
• OKSTL 53-70 vs OKST49% → 2%Before kickoff −1 · On the field −48: Scoreboard −52, Clock −1
• WVUL 26-31 at WVU36% → 5%Before kickoff −14 · On the field −31: Scoreboard −30, Timeouts −2
• KSUW 59-44 vs KSU74% → 99%Before kickoff +24 · On the field +25: Scoreboard +27, Timeouts +1
• TEXW 48-45 at TEX46% → 95%Before kickoff −4 · On the field +49: Scoreboard +49, Clock +3
• LSUL 27-56 vs LSU29% → 0%Before kickoff −21 · On the field −29: Scoreboard −34, Clock −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.