North Texas

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+0.0726th
  Defense+0.1630th
• 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.
  Offense42.3%39th
  Defense42.8%50th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2567th
  Defense+1.2818th
• Rushing EPA

  EPA per designed run.
  Offense−0.105th
  Defense+0.1423rd
• Passing EPA

  EPA per pass play.
  Offense+0.2051st
  Defense+0.2140th
• 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
  Defense46.8%58th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense31.7%33rd
  Defense35.3%28th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.6519th
  Defense2.9444th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense23.1%16th
  Defense17.5%27th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense21.5%29th
  Defense18.4%30th

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 North Texas 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
   ACU
2. L
   SMU
3. L
   CAL
4. W
   UTSA
5. L
   HOU
6. L
   USM
7. W
   MTSU
8. L
   CLT
9. W
   UTEP
10. L
    LT
11. L
    RICE
12. L
    UAB

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

Players, 2019

1. Mason FineQB364 plays · +0.211 pts/play · 43rd of 228 QBs
   1.44WAR0.86 to 2.12
2. Tre SiggersRB129 plays · +0.191 pts/play · 74th of 349 RBs
   0.46WAR0.35 to 0.57
3. Jaelon DardenWR77 plays · +0.142 pts/play · 66th of 439 WRs
   0.20WAR0.09 to 0.31
4. DeAndre TorreyRB74 plays · +0.137 pts/play · 202nd of 349 RBs
   0.19WAR0.12 to 0.24
5. Ethan MooneyPK14 plays · +0.438 pts/play · 63rd of 114 kickers
   0.11WAR0.08 to 0.15
6. Michael LawrenceWR47 plays · +0.120 pts/play · 192nd of 439 WRs
   0.11WAR0.05 to 0.17
7. Loren EaslyRB34 plays · +0.164 pts/play · 261st of 349 RBs
   0.10WAR0.08 to 0.13
8. Alvin KenworthyP42 plays · +0.102 pts/play · 32nd of 100 punters
   0.08WAR0.04 to 0.12

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 North Texas'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.
  45745788th of 130Roster talent: 457, 88th of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  13013098th of 130Recruiting: 130, 98th of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  84%84%14th of 130Returning production: 84%, 14th of 130 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −6.1−6.193rd of 130SP+ rating: −6.1, 93rd 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 North Texas'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 0.08 of the 0.15 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 RICEQ4 7:32 4th & 12 at RICE 15, down 6Went for it; the numbers favored a field goal−5.5 pts
2. vs MTSUQ2 4:28 4th & 2 at MTSU 9, down 6Kicked a field goal; the numbers favored going for it−1.2 pts
3. at CALQ4 2:59 4th & 7 at CAL 18, down 13Went for it; the numbers favored a field goal−1.1 pts
4. at CLTQ2 10:13 4th & 3 at UNT 48, up 7Punted; the numbers favored going for it (close call)−0.6 pts
5. at USMQ1 3:53 4th & 1 at UNT 28, up 1Punted; the numbers favored going for it (close call)−0.6 pts
6. vs HOUQ4 13:35 4th & 3 at UNT 8, down 13Punted; the numbers favored going for it (close call)−0.6 pts
7. at CLTQ4 1:12 4th & 6 at CLT 34, up 2Kicked a field goal; the numbers favored going for it (close call)−0.6 pts
8. at SMUQ3 2:28 4th & 3 at SMU 19, down 18Kicked a field goal; the numbers favored going for it (close call)−0.6 pts

Record vs. expectation, 2019

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

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

1. W

   ACU
2. L

   SMU
3. L

   CAL
4. W

   UTSA
5. L

   HOU
6. L

   USM
7. W

   MTSU
8. L

   CLT
9. W

   UTEP
10. L

    LT
11. L

    RICE
12. L

    UAB

What moved it, 2019

Every game starts at North Texas'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−2.41
• Possession & field position+0.01
• Clock−0.05
• Timeouts−0.01
• Less the pregame edge, counted before kickoff−0.58

Game by game

• ACUW 51-31 vs ACU92% → 100%Before kickoff +42 · On the field +7: Scoreboard +11
• SMUL 27-49 at SMU43% → 0%Before kickoff −7 · On the field −43: Scoreboard −41, Timeouts −1
• CALL 17-23 at CAL20% → 5%Before kickoff −30 · On the field −15: Scoreboard −23, Timeouts −1
• UTSAW 45-3 vs UTSA90% → 100%Before kickoff +40 · On the field +10: Scoreboard +13
• HOUL 25-46 vs HOU72% → 0%Before kickoff +22 · On the field −71: Scoreboard −64, Clock −3
• USML 27-45 at USM41% → 2%Before kickoff −9 · On the field −39: Scoreboard −38, Timeouts +1
• MTSUW 33-30 vs MTSU74% → 96%Before kickoff +24 · On the field +21: Scoreboard +26, Possession & field position +1
• CLTL 38-39 at CLT64% → 31%Before kickoff +14 · On the field −32: Scoreboard −8, Possession & field position +1
• UTEPW 52-26 vs UTEP94% → 100%Before kickoff +44 · On the field +6: Scoreboard +9
• LTL 17-52 at LT36% → 0%Before kickoff −14 · On the field −36: Scoreboard −36
• RICEL 14-20 at RICE73% → 5%Before kickoff +23 · On the field −68: Scoreboard −41, Timeouts −3
• UABL 21-26 vs UAB46% → 1%Before kickoff −4 · On the field −45: Scoreboard −49, Clock −2

Points of win probability, from North Texas's side.

Closest call

UNT 33-30 WMU (2025) - North Texas dropped to a 1.3% win probability before pulling it out.