Pittsburgh

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+0.2590th
  Defense+0.1820th
• 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.
  Offense45.9%73rd
  Defense43.4%54th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.3496th
  Defense+1.359th
• Rushing EPA

  EPA per designed run.
  Offense+0.1676th
  Defense+0.0652nd
• Passing EPA

  EPA per pass play.
  Offense+0.3991st
  Defense+0.2814th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense51.4%79th
  Defense46.6%63rd
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense32.9%40th
  Defense37.1%14th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.9143rd
  Defense2.6975th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense20.9%27th
  Defense21.4%65th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense15.8%54th
  Defense15.6%41st

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 Pittsburgh 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
   VILL
2. W
   PSU
3. L
   OKST
4. L
   UNC
5. W
   MRSH
6. W
   GT
7. W
   UVA
8. L
   VT
9. L
   MIA
10. W
    CLEM
11. W
    DUKE
12. W
    SYR
13. L
    NU

Bars above the line: better than expected for Pittsburgh.

Players, 2016

1. Nathan PetermanQB316 plays · +0.290 pts/play · 35th of 218 QBs
   1.71WAR1.17 to 2.23
2. James ConnerRB211 plays · +0.134 pts/play · 46th of 347 RBs
   0.53WAR0.34 to 0.74
3. Jester WeahWR48 plays · +0.231 pts/play · 68th of 417 WRs
   0.21WAR0.13 to 0.29
4. Quadree HendersonWR90 plays · +0.113 pts/play · 84th of 417 WRs
   0.19WAR0.07 to 0.30
5. Ryan WinslowP47 plays · +0.087 pts/play · 69th of 82 punters
   0.08WAR0.00 to 0.15
6. Chris BlewittPK13 plays · +0.310 pts/play · 80th of 116 kickers
   0.08WAR0.03 to 0.12
7. Darrin HallRB28 plays · +0.138 pts/play · 250th of 347 RBs
   0.07WAR0.05 to 0.10
8. Qadree OllisonRB26 plays · +0.119 pts/play · 258th of 347 RBs
   0.06WAR0.03 to 0.08

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 Pittsburgh'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.
  65065035th of 128Roster talent: 650, 35th of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  19319342nd of 128Recruiting: 193, 42nd of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  69%69%57th of 128Returning production: 69%, 57th of 128 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +13.1+13.123rd of 128SP+ rating: +13.1, 23rd 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 Pittsburgh's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 8 clear-cut ones account for 0.21 of the 0.23 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 CLEMQ4 0:06 4th & 6 at PITT 35, up 1Went for it; the numbers favored punting−8.9 pts
2. at UVAQ3 1:00 4th & 1 at UVA 44, up 14Punted; the numbers favored going for it−3.5 pts
3. vs VTQ4 7:51 4th & 3 at PITT 27, down 3Punted; the numbers favored going for it−1.7 pts
4. at NUQ4 2:49 4th & 10 at NU 18, down 7Went for it; the numbers favored a field goal−1.7 pts
5. at CLEMQ2 0:00 4th & 2 at CLEM 35, down 1Kicked a field goal; the numbers favored going for it−1.6 pts
6. vs MRSHQ3 0:30 4th & 2 at MRSH 2, up 13Kicked a field goal; the numbers favored going for it−1.3 pts
7. at MIAQ4 9:41 4th & 1 at PITT 10, down 13Punted; the numbers favored going for it−1.2 pts
8. at OKSTQ4 12:55 4th & 3 at PITT 37, tiedPunted; the numbers favored going for it−1.2 pts

Record vs. expectation, 2016

47th of 128 FBS teams at beating the model's pregame expectations

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

1. W

   VILL
2. W

   PSU
3. L

   OKST
4. L

   UNC
5. W

   MRSH
6. W

   GT
7. W

   UVA
8. L

   VT
9. L

   MIA
10. W

    CLEM
11. W

    DUKE
12. W

    SYR
13. L

    NU

What moved it, 2016

Every game starts at Pittsburgh'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+0.46
• Possession & field position−0.04
• Clock+0.03
• Timeouts−0.04
• Less the pregame edge, counted before kickoff+0.12

Game by game

• VILLW 28-7 vs VILL97% → 100%Before kickoff +47 · On the field +3: Scoreboard +6
• PSUW 42-39 vs PSU62% → 90%Before kickoff +12 · On the field +29: Scoreboard +29, Timeouts +2
• OKSTL 38-45 at OKST35% → 3%Before kickoff −15 · On the field −31: Scoreboard −32, Timeouts −3
• UNCL 36-37 at UNC33% → 8%Before kickoff −17 · On the field −26: Scoreboard −29, Possession & field position +1
• MRSHW 43-27 vs MRSH83% → 99%Before kickoff +33 · On the field +16: Scoreboard +20, Possession & field position +1
• GTW 37-34 vs GT70% → 94%Before kickoff +20 · On the field +24: Scoreboard +30, Possession & field position −1
• UVAW 45-31 at UVA64% → 99%Before kickoff +14 · On the field +35: Scoreboard +44, Clock +1
• VTL 36-39 vs VT39% → 7%Before kickoff −11 · On the field −32: Scoreboard −43, Clock −3
• MIAL 28-51 at MIA30% → 0%Before kickoff −20 · On the field −30: Scoreboard −33, Clock +1
• CLEMW 43-42 at CLEM8% → 90%Before kickoff −42 · On the field +81: Scoreboard +46, Clock +3
• DUKEW 56-14 vs DUKE67% → 100%Before kickoff +17 · On the field +33: Scoreboard +34
• SYRW 76-61 vs SYR92% → 99%Before kickoff +42 · On the field +7: Scoreboard +13
• NUL 24-31 at NU59% → 3%Before kickoff +9 · On the field −56: Scoreboard −40, Timeouts −3

Points of win probability, from Pittsburgh's side.

Closest call

PITT 28-27 CIN (2024) - Pittsburgh dropped to a 4.3% win probability before pulling it out.