UTSA

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−0.102nd
  Defense+0.1629th
• 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.
  Offense34.2%2nd
  Defense44.2%36th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.065th
  Defense+1.2626th
• Rushing EPA

  EPA per designed run.
  Offense−0.095th
  Defense−0.0282nd
• Passing EPA

  EPA per pass play.
  Offense−0.123rd
  Defense+0.385th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense39.2%4th
  Defense47.7%47th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense26.0%2nd
  Defense36.4%20th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.6219th
  Defense2.7078th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense22.8%16th
  Defense22.7%79th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense21.0%3rd
  Defense16.0%47th

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 UTSA 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
   ASU
2. L
   BAY
3. L
   KSU
4. W
   TXST
5. W
   UTEP
6. W
   RICE
7. L
   LT
8. L
   USM
9. L
   UAB
10. L
    FIU
11. L
    MRSH
12. L
    UNT

Bars above the line: better than expected for UTSA.

Players, 2018

1. Cordale GrundyQB211 plays · +0.167 pts/play · 116th of 225 QBs
   0.66WAR0.39 to 0.99
2. B.J. DanielsRB64 plays · +0.177 pts/play · 202nd of 351 RBs
   0.21WAR0.18 to 0.25
3. Bryce RiversQB47 plays · +0.207 pts/play · 185th of 225 QBs
   0.18WAR0.12 to 0.25
4. Yannis RoutsasP55 plays · +0.157 pts/play · 2nd of 91 punters
   0.16WAR0.08 to 0.24
5. Greg Campbell Jr.WR66 plays · +0.123 pts/play · 92nd of 434 WRs
   0.15WAR0.07 to 0.23
6. Jalen RhodesRB71 plays · +0.100 pts/play · 254th of 351 RBs
   0.13WAR0.08 to 0.19
7. Jared SackettPK15 plays · +0.404 pts/play · 46th of 112 kickers
   0.11WAR0.08 to 0.15
8. Gavin SharpTE16 plays · +0.053 pts/play · 117th of 204 TEs
   0.02WAR−0.01 to 0.04

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 UTSA'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.
  40540594th of 130Roster talent: 405, 94th of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  13613689th of 130Recruiting: 136, 89th of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  5%5%129th of 129Returning production: 5%, 129th of 129 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −22.1−22.1127th of 130SP+ rating: −22.1, 127th 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 UTSA's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 4 clear-cut ones account for 0.15 of the 0.20 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 UNTQ4 0:30 4th & 16 at UNT 42, down 3Went for it; the numbers favored a field goal−6.7 pts
2. vs TXSTQ4 2:59 4th & 2 at UTSA 45, up 2Punted; the numbers favored going for it−5.0 pts
3. at USMQ2 9:26 4th & 1 at USM 1, down 6Kicked a field goal; the numbers favored going for it−1.5 pts
4. at RICEQ4 11:14 4th & 7 at RICE 40, up 10Punted; the numbers favored going for it−1.3 pts
5. vs TXSTQ3 10:17 4th & 2 at UTSA 42, up 10Punted; the numbers favored going for it (close call)−0.7 pts
6. vs FIUQ2 7:28 4th & 1 at UTSA 45, down 14Punted; the numbers favored going for it (close call)−0.7 pts
7. vs LTQ4 12:25 4th & 10 at LT 27, down 21Went for it; the numbers favored a field goal (close call)−0.4 pts
8. vs LTQ2 5:46 4th & 1 at UTSA 31, down 10Punted; the numbers favored going for it (close call)−0.4 pts

Record vs. expectation, 2018

51st of 130 FBS teams at beating the model's pregame expectations

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

1. L

   ASU
2. L

   BAY
3. L

   KSU
4. W

   TXST
5. W

   UTEP
6. W

   RICE
7. L

   LT
8. L

   USM
9. L

   UAB
10. L

    FIU
11. L

    MRSH
12. L

    UNT

What moved it, 2018

Every game starts at UTSA'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−0.26
• Possession & field position−0.02
• Clock−0.03
• Timeouts+0.03
• Less the pregame edge, counted before kickoff+0.59

Game by game

• ASUL 7-49 at ASU9% → 0%Before kickoff −41 · On the field −9: Scoreboard −12
• BAYL 20-37 vs BAY9% → 1%Before kickoff −41 · On the field −8: Scoreboard −16, Clock −2
• KSUL 17-41 at KSU7% → 0%Before kickoff −43 · On the field −7: Scoreboard −10
• TXSTW 25-21 vs TXST67% → 91%Before kickoff +17 · On the field +24: Scoreboard +27, Timeouts +2
• UTEPW 30-21 vs UTEP74% → 96%Before kickoff +24 · On the field +22: Scoreboard +28, Possession & field position −1
• RICEW 20-3 at RICE43% → 99%Before kickoff −7 · On the field +56: Scoreboard +56, Clock +2
• LTL 3-31 vs LT16% → 0%Before kickoff −34 · On the field −16: Scoreboard −21
• USML 17-27 at USM13% → 2%Before kickoff −37 · On the field −11: Scoreboard −19
• UABL 3-52 at UAB6% → 0%Before kickoff −44 · On the field −6: Scoreboard −8
• FIUL 7-45 vs FIU22% → 0%Before kickoff −28 · On the field −22: Scoreboard −28, Clock −1
• MRSHL 0-23 at MRSH4% → 0%Before kickoff −46 · On the field −4: Scoreboard −7
• UNTL 21-24 vs UNT5% → 16%Before kickoff −45 · On the field +11: Scoreboard −16, Clock −2

Points of win probability, from UTSA's side.

Closest call

CCU 15-44 UTSA (2024) - UTSA dropped to a 0.0% win probability before pulling it out.