Pittsburgh

Profile vs. FBS, 2015

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+0.1359th
  Defense+0.1138th
• 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%75th
  Defense40.5%66th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.1013th
  Defense+1.3213th
• Rushing EPA

  EPA per designed run.
  Offense+0.1061st
  Defense+0.1320th
• Passing EPA

  EPA per pass play.
  Offense+0.1959th
  Defense+0.1256th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense50.7%80th
  Defense42.6%88th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense34.0%50th
  Defense36.6%22nd
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.9361st
  Defense2.6176th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense17.5%79th
  Defense20.5%54th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense3.4%4th
  Defense1.4%12th

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, 2015

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
   YSU
2. W
   AKR
3. L
   IOWA
4. W
   VT
5. W
   UVA
6. W
   GT
7. W
   SYR
8. L
   UNC
9. L
   ND
10. W
    DUKE
11. W
    LOU
12. L
    MIA
13. L
    NAVY

Bars above the line: better than expected for Pittsburgh.

Players, 2015

1. Nathan PetermanQB376 plays · +0.203 pts/play · 64th of 205 QBs
   1.43WAR0.80 to 2.06
2. Tyler BoydWR162 plays · +0.136 pts/play · 8th of 411 WRs
   0.41WAR0.23 to 0.61
3. Qadree OllisonRB201 plays · +0.107 pts/play · 39th of 333 RBs
   0.40WAR0.24 to 0.55
4. Chris BlewittPK20 plays · +0.363 pts/play · 39th of 115 kickers
   0.14WAR0.08 to 0.20
5. Darrin HallRB65 plays · +0.101 pts/play · 180th of 333 RBs
   0.12WAR0.08 to 0.16
6. Dontez FordWR38 plays · +0.126 pts/play · 235th of 411 WRs
   0.09WAR0.04 to 0.15
7. Chad VoytikQB23 plays · +0.185 pts/play · 192nd of 205 QBs
   0.08WAR0.03 to 0.13
8. Ryan WinslowP52 plays · +0.078 pts/play · 55th of 92 punters
   0.08WAR0.00 to 0.14

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, 2015

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  61161142nd of 128Roster talent: 611, 42nd of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  18518545th of 128Recruiting: 185, 45th of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  84%84%22nd of 127Returning production: 84%, 22nd of 127 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +11.1+11.133rd of 128SP+ rating: +11.1, 33rd 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, 2015

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 0.13 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 LOUQ4 5:25 4th & 1 at LOU 1, up 8Kicked a field goal; the numbers favored going for it−2.4 pts
2. vs UNCQ4 14:07 4th & 1 at PITT 29, down 10Punted; the numbers favored going for it−2.1 pts
3. at GTQ4 13:28 4th & 4 at GT 45, tiedPunted; the numbers favored going for it−2.0 pts
4. at VTQ4 8:30 4th & 8 at VT 36, up 4Punted; the numbers favored going for it−1.8 pts
5. at IOWAQ2 0:04 4th & 12 at PITT 37, down 10Went for it; the numbers favored punting−1.6 pts
6. vs MIAQ4 4:22 4th & 7 at MIA 29, down 11Kicked a field goal; the numbers favored going for it−1.4 pts
7. vs UVAQ2 4:57 4th & 1 at PITT 36, up 7Punted; the numbers favored going for it−1.2 pts
8. at AKRQ3 12:41 4th & 2 at PITT 46, up 3Punted; the numbers favored going for it−1.1 pts

Record vs. expectation, 2015

40th 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

   YSU
2. W

   AKR
3. L

   IOWA
4. W

   VT
5. W

   UVA
6. W

   GT
7. W

   SYR
8. L

   UNC
9. L

   ND
10. W

    DUKE
11. W

    LOU
12. L

    MIA
13. L

    NAVY

What moved it, 2015

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+0.80
• Possession & field position+0.08
• Clock+0.06
• Timeouts−0.01
• Other+0.01
• Less the pregame edge, counted before kickoff−0.34

Game by game

• YSUW 45-37 vs YSU88% → 96%Before kickoff +38 · On the field +8: Scoreboard +16, Possession & field position +2
• AKRW 24-7 at AKR84% → 99%Before kickoff +34 · On the field +15: Scoreboard +24, Clock +1
• IOWAL 24-27 at IOWA47% → 6%Before kickoff −3 · On the field −42: Scoreboard −34, Timeouts −3
• VTW 17-13 at VT34% → 96%Before kickoff −16 · On the field +61: Scoreboard +53, Clock +3
• UVAW 26-19 vs UVA78% → 97%Before kickoff +28 · On the field +18: Scoreboard +24, Timeouts +1
• GTW 31-28 at GT46% → 82%Before kickoff −4 · On the field +36: Scoreboard +37, Clock +4
• SYRW 23-20 at SYR69% → 96%Before kickoff +19 · On the field +27: Scoreboard +37, Clock +2
• UNCL 19-26 vs UNC40% → 5%Before kickoff −10 · On the field −35: Scoreboard −44, Clock −3
• NDL 30-42 vs ND29% → 2%Before kickoff −21 · On the field −27: Scoreboard −38, Clock −2
• DUKEW 31-13 at DUKE43% → 99%Before kickoff −7 · On the field +56: Scoreboard +55, Clock +3
• LOUW 45-34 vs LOU55% → 97%Before kickoff +5 · On the field +41: Scoreboard +35, Timeouts +2
• MIAL 24-29 vs MIA67% → 9%Before kickoff +17 · On the field −58: Scoreboard −47, Clock −4
• NAVYL 28-44 at NAVY41% → 1%Before kickoff −9 · On the field −41: Scoreboard −38, Timeouts −1

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.