Houston

Profile vs. FBS, 2019

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+0.1144th
  Defense+0.2211th
• 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.
  Offense42.4%40th
  Defense45.3%30th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2670th
  Defense+1.361st
• Rushing EPA

  EPA per designed run.
  Offense+0.1373rd
  Defense+0.0940th
• Passing EPA

  EPA per pass play.
  Offense+0.1128th
  Defense+0.349th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense47.7%47th
  Defense49.2%35th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense32.3%38th
  Defense37.7%13th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.0671st
  Defense2.7072nd
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense19.7%45th
  Defense25.8%95th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense23.3%15th
  Defense20.2%52nd

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, 2019

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 Houston 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
   OU
2. W
   PV
3. L
   WSU
4. L
   TULN
5. W
   UNT
6. L
   CIN
7. W
   CONN
8. L
   SMU
9. L
   UCF
10. L
    MEM
11. W
    TLSA
12. L
    NAVY

Bars above the line: better than expected for Houston.

Players, 2019

1. D'Eriq KingQB112 plays · +0.335 pts/play · 102nd of 228 QBs
   0.70WAR0.47 to 0.91
2. Clayton TuneQB208 plays · +0.160 pts/play · 110th of 228 QBs
   0.62WAR0.21 to 1.11
3. Kyle PorterRB112 plays · +0.172 pts/play · 114th of 349 RBs
   0.36WAR0.28 to 0.44
4. Patrick CarrRB70 plays · +0.163 pts/play · 186th of 349 RBs
   0.21WAR0.16 to 0.27
5. Marquez StevensonWR79 plays · +0.141 pts/play · 60th of 439 WRs
   0.21WAR0.08 to 0.33
6. Dalton WitherspoonPK21 plays · +0.470 pts/play · 16th of 114 kickers
   0.18WAR0.13 to 0.24
7. Mulbah CarRB43 plays · +0.201 pts/play · 228th of 349 RBs
   0.16WAR0.13 to 0.20
8. Dane RoyP42 plays · +0.150 pts/play · 10th of 100 punters
   0.12WAR0.07 to 0.16

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 Houston'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, 2019

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  59859855th of 130Roster talent: 598, 55th of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  17417464th of 130Recruiting: 174, 64th of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  88%88%6th of 130Returning production: 88%, 6th of 130 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −4.3−4.382nd of 130SP+ rating: −4.3, 82nd 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, 2019

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 Houston'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 0.04 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. vs WSUQ3 5:48 4th & 2 at HOU 39, down 7Punted; the numbers favored going for it−1.4 pts
2. vs SMUQ3 7:30 4th & 12 at SMU 49, down 11Went for it; the numbers favored punting−1.2 pts
3. at TLSAQ4 12:40 4th & 4 at TLSA 47, up 10Punted; the numbers favored going for it−1.0 pts
4. vs SMUQ4 14:10 4th & 2 at SMU 23, down 11Kicked a field goal; the numbers favored going for it (close call)−0.9 pts
5. vs NAVYQ4 5:50 4th & 9 at NAVY 22, down 15Went for it; the numbers favored a field goal (close call)−0.8 pts
6. vs MEMQ3 2:09 4th & 2 at HOU 28, down 22Punted; the numbers favored going for it (close call)−0.6 pts
7. at TULNQ3 10:07 4th & 10 at TULN 36, up 7Punted; the numbers favored a field goal (close call)−0.6 pts
8. at TLSAQ4 0:30 4th & 4 at TLSA 20, up 10Went for it; the numbers favored a field goal (close call)−0.5 pts

Record vs. expectation, 2019

85th of 130 FBS teams at beating the model's pregame expectations

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

1. L

   OU
2. W

   PV
3. L

   WSU
4. L

   TULN
5. W

   UNT
6. L

   CIN
7. W

   CONN
8. L

   SMU
9. L

   UCF
10. L

    MEM
11. W

    TLSA
12. L

    NAVY

What moved it, 2019

Every game starts at Houston'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−1.00
• Clock−0.03
• Timeouts−0.02
• Less the pregame edge, counted before kickoff+0.74

Game by game

• OUL 31-49 at OU9% → 1%Before kickoff −41 · On the field −8: Scoreboard −13
• PVW 37-17 vs PV98% → 99%Before kickoff +48 · On the field +1: Scoreboard +4
• WSUL 24-31 vs WSU30% → 4%Before kickoff −20 · On the field −26: Scoreboard −37, Clock −2
• TULNL 31-38 at TULN41% → 4%Before kickoff −9 · On the field −37: Scoreboard −35, Possession & field position +1
• UNTW 46-25 at UNT28% → 100%Before kickoff −22 · On the field +71: Scoreboard +64, Clock +3
• CINL 23-38 vs CIN27% → 1%Before kickoff −23 · On the field −25: Scoreboard −36, Clock −2
• CONNW 24-17 at CONN94% → 96%Before kickoff +44 · On the field +2: Scoreboard +15, Clock +1
• SMUL 31-34 vs SMU22% → 17%Before kickoff −28 · On the field −4: Scoreboard −29, Clock −3
• UCFL 29-44 at UCF8% → 1%Before kickoff −42 · On the field −7: Scoreboard −13
• MEML 27-45 vs MEM28% → 2%Before kickoff −22 · On the field −26: Scoreboard −35, Clock −1
• TLSAW 24-14 at TLSA36% → 96%Before kickoff −14 · On the field +60: Scoreboard +55, Clock +3
• NAVYL 41-56 vs NAVY32% → 1%Before kickoff −18 · On the field −30: Scoreboard −40, Clock −1

Points of win probability, from Houston's side.

Closest call

HOU 35-34 PITT (2014) - Houston dropped to a 0.7% win probability before pulling it out.