Charlotte

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+0.0218th
  Defense+0.1246th
• 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.
  Offense38.3%8th
  Defense44.0%45th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2360th
  Defense+1.1855th
• Rushing EPA

  EPA per designed run.
  Offense+0.1259th
  Defense+0.0464th
• Passing EPA

  EPA per pass play.
  Offense−0.076th
  Defense+0.1941st
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense42.0%5th
  Defense48.0%50th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense31.1%30th
  Defense34.8%37th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.0359th
  Defense2.6678th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense19.6%42nd
  Defense21.0%63rd
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense16.5%41st
  Defense14.8%24th

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 Charlotte 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
   LOU
2. W
   ELON
3. L
   EMU
4. L
   TEM
5. L
   ODU
6. W
   FAU
7. L
   FIU
8. W
   MRSH
9. W
   USM
10. L
    RICE
11. L
    MTSU
12. L
    UTSA

Bars above the line: better than expected for Charlotte.

Players, 2016

1. Hasaan KlughQB276 plays · +0.230 pts/play · 68th of 218 QBs
   1.19WAR0.67 to 1.64
2. Kalif PhillipsRB172 plays · +0.175 pts/play · 39th of 347 RBs
   0.56WAR0.39 to 0.72
3. Robert WashingtonRB72 plays · +0.142 pts/play · 183rd of 347 RBs
   0.19WAR0.12 to 0.26
4. Kevin OlsenQB57 plays · +0.170 pts/play · 167th of 218 QBs
   0.18WAR0.11 to 0.26
5. Workpeh KofaWR35 plays · +0.178 pts/play · 187th of 417 WRs
   0.12WAR0.07 to 0.17
6. Arthur HartP43 plays · +0.096 pts/play · 68th of 82 punters
   0.08WAR0.01 to 0.15
7. Austin DukeWR75 plays · +0.037 pts/play · 336th of 417 WRs
   0.05WAR−0.05 to 0.15
8. Matt JohnsonRB13 plays · +0.171 pts/play · 268th of 347 RBs
   0.04WAR0.03 to 0.06

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 Charlotte'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.
  331331120th of 128Roster talent: 331, 120th of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  9494124th of 128Recruiting: 94, 124th of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  86%86%26th of 128Returning production: 86%, 26th of 128 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −20.9−20.9126th of 128SP+ rating: −20.9, 126th 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 Charlotte's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 5 clear-cut ones account for 0.10 of the 0.16 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 FAUQ4 9:28 4th & 1 at CLT 34, up 5Punted; the numbers favored going for it−3.9 pts
2. vs MTSUQ3 9:15 4th & 1 at CLT 47, down 11Punted; the numbers favored going for it−2.1 pts
3. at USMQ3 9:29 4th & 2 at USM 4, up 14Kicked a field goal; the numbers favored going for it−2.0 pts
4. vs MTSUQ2 0:59 4th & 13 at MTSU 32, down 15Went for it; the numbers favored a field goal−1.1 pts
5. vs MTSUQ2 12:52 4th & 11 at MTSU 20, down 8Went for it; the numbers favored a field goal−1.0 pts
6. at USMQ4 4:00 4th & 6 at USM 36, up 11Punted; the numbers favored going for it (close call)−0.9 pts
7. at MRSHQ2 3:20 4th & 2 at MRSH 49, down 7Punted; the numbers favored going for it (close call)−0.8 pts
8. vs RICEQ4 2:53 4th & 9 at CLT 25, down 1Went for it; the numbers favored punting (close call)−0.7 pts

Record vs. expectation, 2016

52nd of 128 FBS teams at beating the model's pregame expectations

Expected wins adds up Charlotte's chance of winning each game as the model saw it at kickoff - a 70% favorite counts 0.7. Based on 11 of 12 games; one has no play-by-play to score.

1. L

   LOU
2. W

   ELON
3. L

   EMU
4. L

   TEM
5. L

   ODU
6. W

   FAU
7. L

   FIU
8. W

   MRSH
9. W

   USM
10. L

    RICE
11. L

    MTSU
12. L

    UTSA

What moved it, 2016

Every game starts at Charlotte'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−0.32
• Possession & field position−0.03
• Clock−0.01
• Less the pregame edge, counted before kickoff+0.85

Game by game

• LOUL 14-70 at LOU1% → 0%Before kickoff −49 · On the field −1: Scoreboard −2
• ELONW 47-14 vs ELON76% → 100%Before kickoff +26 · On the field +24: Scoreboard +26
• EMUL 19-37 vs EMU49% → 0%Before kickoff −1 · On the field −49: Scoreboard −51, Clock −2
• TEML 20-48 at TEM3% → 0%Before kickoff −47 · On the field −3: Scoreboard −6
• FAUW 28-23 at FAU19% → 88%Before kickoff −31 · On the field +69: Scoreboard +45, Clock +3
• FIUL 26-27 vs FIU45% → 8%Before kickoff −5 · On the field −36: Scoreboard −46, Clock −2
• MRSHW 27-24 at MRSH13% → 86%Before kickoff −37 · On the field +73: Scoreboard +46, Clock +3
• USMW 38-27 at USM12% → 95%Before kickoff −38 · On the field +83: Scoreboard +56, Clock +4
• RICEL 21-22 vs RICE79% → 27%Before kickoff +29 · On the field −52: Scoreboard −29, Clock −5
• MTSUL 31-38 vs MTSU32% → 5%Before kickoff −18 · On the field −28: Scoreboard −39, Clock −2
• UTSAL 14-33 at UTSA33% → 1%Before kickoff −17 · On the field −32: Scoreboard −33, Clock −1

Points of win probability, from Charlotte's side.

Closest call

CLT 42-41 GAST (2022) - Charlotte dropped to a 3.9% win probability before pulling it out.