Virginia Tech

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+0.0835th
  Defense+0.0761st
• 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.
  Offense43.1%46th
  Defense38.1%85th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.1424th
  Defense+1.377th
• Rushing EPA

  EPA per designed run.
  Offense0.0023rd
  Defense+0.0269th
• Passing EPA

  EPA per pass play.
  Offense+0.1651st
  Defense+0.1449th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense46.8%41st
  Defense42.0%90th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense35.3%58th
  Defense31.7%64th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.6420th
  Defense2.6472nd
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense19.9%47th
  Defense24.4%86th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense1.4%88th
  Defense2.0%54th

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 Virginia Tech 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
   OSU
2. W
   FUR
3. W
   PUR
4. L
   ECU
5. L
   PITT
6. W
   NCSU
7. L
   MIA
8. L
   DUKE
9. W
   BC
10. W
    GT
11. L
    UNC
12. W
    UVA
13. W
    TLSA

Bars above the line: better than expected for Virginia Tech.

Players, 2015

1. Michael BrewerQB223 plays · +0.173 pts/play · 110th of 205 QBs
   0.72WAR0.38 to 1.06
2. Brenden MotleyQB210 plays · +0.170 pts/play · 114th of 205 QBs
   0.67WAR0.29 to 1.07
3. Isaiah FordWR114 plays · +0.211 pts/play · 3rd of 411 WRs
   0.45WAR0.27 to 0.62
4. Travon McMillianRB174 plays · +0.136 pts/play · 28th of 333 RBs
   0.44WAR0.31 to 0.56
5. Joey SlyePK23 plays · +0.452 pts/play · 10th of 115 kickers
   0.19WAR0.13 to 0.26
6. Cam PhillipsWR55 plays · +0.148 pts/play · 124th of 411 WRs
   0.15WAR0.08 to 0.24
7. Sam RogersFB76 plays · +0.106 pts/play · 155th of 333 RBs
   0.15WAR0.10 to 0.20
8. A.J. HughesP59 plays · +0.130 pts/play · 20th of 92 punters
   0.14WAR0.05 to 0.24

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 Virginia Tech'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.
  65865832nd of 128Roster talent: 658, 32nd of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  21521526th of 128Recruiting: 215, 26th of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  89%89%11th of 127Returning production: 89%, 11th of 127 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +11.4+11.431st of 128SP+ rating: +11.4, 31st 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 Virginia Tech's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 9 clear-cut ones account for 0.15 of the 0.25 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 PITTQ4 2:28 4th & 25 at VT 23, down 4Went for it; the numbers favored punting−2.7 pts
2. at GTQ4 9:26 4th & 2 at VT 40, down 4Punted; the numbers favored going for it−2.2 pts
3. vs NCSUQ4 10:36 4th & 2 at VT 28, up 8Punted; the numbers favored going for it−2.0 pts
4. vs UNCQ4 2:54 4th & 7 at UNC 8, down 14Went for it; the numbers favored a field goal−1.7 pts
5. vs OSUQ3 11:23 4th & 4 at OSU 43, down 4Punted; the numbers favored going for it−1.4 pts
6. at PURQ3 9:30 4th & 2 at PUR 46, up 10Punted; the numbers favored going for it−1.3 pts
7. at MIAQ4 10:39 4th & 1 at VT 42, down 10Punted; the numbers favored going for it−1.3 pts
8. at BCQ2 9:57 4th & 4 at BC 42, up 17Punted; the numbers favored going for it−1.2 pts

Record vs. expectation, 2015

91st of 128 FBS teams at beating the model's pregame expectations

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

1. L

   OSU
2. W

   FUR
3. W

   PUR
4. L

   ECU
5. L

   PITT
6. W

   NCSU
7. L

   MIA
8. L

   DUKE
9. W

   BC
10. W

    GT
11. L

    UNC
12. W

    UVA
13. W

    TLSA

What moved it, 2015

Every game starts at Virginia Tech'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+0.10
• Possession & field position−0.08
• Clock+0.32
• Timeouts−0.35
• Less the pregame edge, counted before kickoff−0.58

Game by game

• OSUL 24-42 vs OSU17% → 1%Before kickoff −33 · On the field −16: Scoreboard −25, Clock −1
• FURW 42-3 vs FUR98% → 100%Before kickoff +48 · On the field +2: Scoreboard +3
• PURW 51-24 at PUR70% → 100%Before kickoff +20 · On the field +29: Scoreboard +34, Clock +1
• ECUL 28-35 at ECU77% → 7%Before kickoff +27 · On the field −69: Scoreboard −34, Timeouts −2
• PITTL 13-17 vs PITT66% → 4%Before kickoff +16 · On the field −61: Scoreboard −53, Clock −3
• NCSUW 28-13 vs NCSU56% → 99%Before kickoff +6 · On the field +44: Scoreboard +39, Timeouts +2
• MIAL 20-30 at MIA33% → 3%Before kickoff −17 · On the field −30: Scoreboard −30, Timeouts −2
• DUKEL 43-45 vs DUKE72% → 12%Before kickoff +22 · On the field −60: Scoreboard −43, Timeouts −20
• BCW 26-10 at BC62% → 98%Before kickoff +12 · On the field +36: Scoreboard +44, Clock +2
• GTW 23-21 at GT44% → 95%Before kickoff −6 · On the field +51: Scoreboard +50, Clock +3
• UNCL 27-30 vs UNC31% → 12%Before kickoff −19 · On the field −18: Scoreboard −34, Timeouts −15
• UVAW 23-20 at UVA66% → 90%Before kickoff +16 · On the field +24: Scoreboard +40, Clock +3
• TLSAW 55-52 vs TLSA85% → 96%Before kickoff +35 · On the field +11: Scoreboard +19, Timeouts +1

Points of win probability, from Virginia Tech's side.

Closest call

CAL 34-42 VT (2025) - Virginia Tech dropped to a 5.3% win probability before pulling it out.