Texas Tech

Profile vs. FBS, 2016

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+0.2993rd
  Defense+0.272nd
• 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.
  Offense48.4%88th
  Defense50.1%2nd
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.3495th
  Defense+1.2042nd
• Rushing EPA

  EPA per designed run.
  Offense+0.0745th
  Defense+0.1525th
• Passing EPA

  EPA per pass play.
  Offense+0.4295th
  Defense+0.431st
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense50.9%75th
  Defense53.2%9th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense42.9%97th
  Defense41.9%1st
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.9346th
  Defense3.1419th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense19.4%45th
  Defense17.7%33rd
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense13.5%86th
  Defense12.5%6th

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, 2016

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
   SFA
2. L
   ASU
3. W
   LT
4. W
   KU
5. L
   KSU
6. L
   WVU
7. L
   OU
8. W
   TCU
9. L
   TEX
10. L
    OKST
11. L
    ISU
12. W
    BAY

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

Players, 2016

1. Patrick MahomesQB597 plays · +0.327 pts/play · 1st of 218 QBs
   3.65WAR2.59 to 4.61
2. Jonathan GilesWR74 plays · +0.222 pts/play · 21st of 417 WRs
   0.31WAR0.21 to 0.41
3. Da'Leon WardRB97 plays · +0.133 pts/play · 153rd of 347 RBs
   0.24WAR0.17 to 0.31
4. Keke CouteeWR68 plays · +0.177 pts/play · 56th of 417 WRs
   0.23WAR0.13 to 0.32
5. Dylan CantrellWR71 plays · +0.136 pts/play · 92nd of 417 WRs
   0.18WAR0.11 to 0.25
6. Demarcus FeltonRB52 plays · +0.161 pts/play · 210th of 347 RBs
   0.16WAR0.11 to 0.20
7. Cameron BatsonWR67 plays · +0.120 pts/play · 132nd of 417 WRs
   0.15WAR0.05 to 0.25
8. Justin StocktonRB58 plays · +0.103 pts/play · 237th of 347 RBs
   0.11WAR0.06 to 0.17

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, 2016

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  60560546th of 128Roster talent: 605, 46th of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  19319343rd of 128Recruiting: 193, 43rd of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  71%71%50th of 128Returning production: 71%, 50th of 128 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +3.7+3.759th of 128SP+ rating: +3.7, 59th 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, 2016

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 0.07 of the 0.10 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 KSUQ3 5:17 4th & 1 at KSU 16, down 3Kicked a field goal; the numbers favored going for it−3.1 pts
2. at KSUQ4 12:44 4th & 1 at TTU 34, down 7Punted; the numbers favored going for it−2.1 pts
3. vs TEXQ3 11:57 4th & 8 at TTU 27, down 8Went for it; the numbers favored punting−1.3 pts
4. vs TEXQ4 14:49 4th & 10 at TEX 29, down 15Went for it; the numbers favored a field goal (close call)−0.9 pts
5. at KSUQ4 5:01 4th & 11 at TTU 21, down 10Went for it; the numbers favored punting (close call)−0.6 pts
6. at OKSTQ4 9:23 4th & 9 at OKST 9, down 10Kicked a field goal; the numbers favored going for it (close call)−0.5 pts
7. vs BAYQ3 1:05 4th & 1 at TTU 25, up 23Punted; the numbers favored going for it (close call)−0.4 pts
8. at TCUQ2 2:48 4th & 3 at TTU 20, tiedPunted; the numbers favored going for it (close call)−0.4 pts

Record vs. expectation, 2016

97th 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

   SFA
2. L

   ASU
3. W

   LT
4. W

   KU
5. L

   KSU
6. L

   WVU
7. L

   OU
8. W

   TCU
9. L

   TEX
10. L

    OKST
11. L

    ISU
12. W

    BAY

What moved it, 2016

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−1.41
• Possession & field position−0.06
• Clock−0.27
• Timeouts+0.24
• Less the pregame edge, counted before kickoff+0.49

Game by game

• SFAW 69-17 vs SFA99% → 100%Before kickoff +49 · On the field +1: Scoreboard +2
• ASUL 55-68 at ASU42% → 1%Before kickoff −8 · On the field −41: Scoreboard −41, Timeouts +1
• LTW 59-45 vs LT83% → 99%Before kickoff +33 · On the field +15: Scoreboard +21
• KUW 55-19 vs KU95% → 100%Before kickoff +45 · On the field +5: Scoreboard +7
• KSUL 38-44 at KSU30% → 12%Before kickoff −20 · On the field −18: Scoreboard −23, Timeouts −1
• WVUL 17-48 vs WVU54% → 0%Before kickoff +4 · On the field −54: Scoreboard −56
• OUL 59-66 vs OU18% → 5%Before kickoff −32 · On the field −13: Scoreboard −28, Clock −2
• TCUW 27-24 at TCU32% → 74%Before kickoff −18 · On the field +42: Scoreboard +40, Timeouts +22
• TEXL 37-45 vs TEX34% → 7%Before kickoff −16 · On the field −27: Scoreboard −42, Clock −3
• OKSTL 44-45 at OKST24% → 17%Before kickoff −26 · On the field −7: Scoreboard −16, Possession & field position −2
• ISUL 10-66 at ISU60% → 0%Before kickoff +10 · On the field −60: Scoreboard −55, Timeouts +1
• BAYW 54-35 vs BAY44% → 100%Before kickoff −6 · On the field +56: Scoreboard +50

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.