App State

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+0.1670th
  Defense−0.0290th
• 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.
  Offense46.4%78th
  Defense38.2%83rd
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.1733rd
  Defense+1.1378th
• Rushing EPA

  EPA per designed run.
  Offense+0.1987th
  Defense+0.1040th
• Passing EPA

  EPA per pass play.
  Offense+0.1647th
  Defense−0.1197th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense53.4%92nd
  Defense43.5%81st
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense29.8%18th
  Defense28.3%89th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.1372nd
  Defense3.0538th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense17.3%71st
  Defense18.8%46th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense14.0%81st
  Defense16.8%57th

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 App State 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
   TENN
2. W
   ODU
3. L
   MIA
4. W
   AKR
5. W
   GAST
6. W
   UL
7. W
   IDHO
8. W
   GASO
9. W
   TXST
10. L
    TROY
11. W
    ULM
12. W
    NMSU
13. W
    TOL

Bars above the line: better than expected for App State.

Players, 2016

1. Taylor LambQB281 plays · +0.290 pts/play · 46th of 218 QBs
   1.52WAR1.07 to 2.00
2. Jalin MooreRB175 plays · +0.159 pts/play · 48th of 347 RBs
   0.52WAR0.29 to 0.76
3. Marcus CoxRB122 plays · +0.171 pts/play · 82nd of 347 RBs
   0.39WAR0.26 to 0.51
4. Shaedon MeadorsWR34 plays · +0.189 pts/play · 178th of 417 WRs
   0.12WAR0.08 to 0.16
5. Michael RubinoPK17 plays · +0.289 pts/play · 61st of 116 kickers
   0.09WAR0.05 to 0.14
6. Bentlee CritcherP31 plays · +0.154 pts/play · 62nd of 82 punters
   0.09WAR0.04 to 0.14
7. Barrett BurnsTE20 plays · +0.077 pts/play · 32nd of 195 TEs
   0.03WAR0.00 to 0.06
8. Deltron HopkinsWR6 plays · +0.086 pts/play · 407th of 417 WRs
   0.01WAR0.00 to 0.02

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 App State'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.
  333333119th of 128Roster talent: 333, 119th of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  115115105th of 128Recruiting: 115, 105th of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  72%72%45th of 128Returning production: 72%, 45th of 128 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +9.2+9.243rd of 128SP+ rating: +9.2, 43rd 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 App State'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 0.17 of the 0.21 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 TOLQ4 5:14 4th & 1 at TOL 22, tiedKicked a field goal; the numbers favored going for it−8.2 pts
2. at TOLQ4 10:11 4th & 13 at TOL 21, tiedWent for it; the numbers favored a field goal−5.9 pts
3. at AKRQ4 2:19 4th & 5 at AKR 35, up 7Punted; the numbers favored going for it−1.8 pts
4. at TOLQ2 0:14 4th & 14 at TOL 43, tiedPunted; the numbers favored a field goal−1.1 pts
5. at TOLQ2 13:34 4th & 5 at TOL 35, tiedPunted; the numbers favored going for it (close call)−0.7 pts
6. at GASOQ4 7:22 4th & 9 at GASO 32, up 17Punted; the numbers favored a field goal (close call)−0.5 pts
7. at NMSUQ3 14:07 4th & 5 at APP 42, up 13Went for it; the numbers favored punting (close call)−0.4 pts
8. vs ODUQ2 14:49 4th & 3 at ODU 3, up 14Kicked a field goal; the numbers favored going for it (close call)−0.4 pts

Record vs. expectation, 2016

19th of 128 FBS teams at beating the model's pregame expectations

Expected wins adds up App State's chance of winning each game as the model saw it at kickoff - a 70% favorite counts 0.7. Based on 12 of 13 games; one has no play-by-play to score.

1. L

   TENN
2. W

   ODU
3. L

   MIA
4. W

   AKR
5. W

   GAST
6. W

   UL
7. W

   IDHO
8. W

   GASO
9. W

   TXST
10. L

    TROY
11. W

    ULM
12. W

    NMSU
13. W

    TOL

What moved it, 2016

Every game starts at App State'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+1.87
• Clock+0.04
• Timeouts+0.08
• Less the pregame edge, counted before kickoff−0.40

Game by game

• TENNL 13-20 at TENN6% → 10%Before kickoff −44 · On the field +4: Scoreboard −12, Timeouts +7
• ODUW 31-7 vs ODU89% → 100%Before kickoff +39 · On the field +10: Scoreboard +15
• MIAL 10-45 vs MIA32% → 0%Before kickoff −18 · On the field −32: Scoreboard −37, Clock −1
• AKRW 45-38 at AKR70% → 96%Before kickoff +20 · On the field +26: Scoreboard +37, Clock +2
• GASTW 17-3 vs GAST92% → 99%Before kickoff +42 · On the field +6: Scoreboard +12, Timeouts +1
• ULW 24-0 at UL76% → 99%Before kickoff +26 · On the field +23: Scoreboard +31, Clock +2
• IDHOW 37-19 vs IDHO93% → 99%Before kickoff +43 · On the field +7: Scoreboard +12
• GASOW 34-10 at GASO56% → 100%Before kickoff +6 · On the field +44: Scoreboard +48, Clock +2
• TXSTW 35-10 vs TXST97% → 100%Before kickoff +47 · On the field +3: Scoreboard +6
• ULMW 42-17 vs ULM95% → 100%Before kickoff +45 · On the field +5: Scoreboard +7
• NMSUW 37-7 at NMSU88% → 100%Before kickoff +38 · On the field +12: Scoreboard +17, Clock +1
• TOLW 31-28 at TOL44% → 95%Before kickoff −6 · On the field +51: Scoreboard +51, Clock +3

Points of win probability, from App State's side.

Closest call

MRSH 9-31 APP (2023) - App State dropped to a 4.5% win probability before pulling it out.