Georgia Tech

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+0.1875th
  Defense+0.1725th
• 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.
  Offense44.2%57th
  Defense47.6%13th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2468th
  Defense+1.1280th
• Rushing EPA

  EPA per designed run.
  Offense+0.1056th
  Defense+0.1524th
• Passing EPA

  EPA per pass play.
  Offense+0.4897th
  Defense+0.2036th
• 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%72nd
  Defense52.7%10th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense31.0%28th
  Defense35.4%30th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.9952nd
  Defense3.308th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense17.3%72nd
  Defense14.1%8th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense15.2%64th
  Defense12.0%3rd

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 Georgia 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. W
   BC
2. W
   MER
3. W
   VAN
4. L
   CLEM
5. L
   MIA
6. L
   PITT
7. W
   GASO
8. W
   DUKE
9. L
   UNC
10. W
    VT
11. W
    UVA
12. W
    UGA
13. W
    UK

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

Players, 2016

1. Justin ThomasQB244 plays · +0.170 pts/play · 104th of 218 QBs
   0.78WAR0.27 to 1.24
2. Dedrick MillsRB135 plays · +0.176 pts/play · 65th of 347 RBs
   0.44WAR0.31 to 0.59
3. Clinton Lynch?45 plays · +0.294 pts/play
   0.25WAR0.20 to 0.30
4. Marcus Marshall?78 plays · +0.162 pts/play
   0.24WAR0.12 to 0.35
5. Harrison ButkerPK15 plays · +0.477 pts/play · 34th of 116 kickers
   0.13WAR0.09 to 0.18
6. Ryan RodwellP40 plays · +0.168 pts/play · 51st of 82 punters
   0.13WAR0.07 to 0.19
7. Matthew JordanQB38 plays · +0.132 pts/play · 193rd of 218 QBs
   0.09WAR−0.04 to 0.21
8. Ricky JeuneWR37 plays · +0.112 pts/play · 271st of 417 WRs
   0.08WAR0.03 to 0.13

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 Georgia 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, 2016

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  58358350th of 128Roster talent: 583, 50th of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  17617651st of 128Recruiting: 176, 51st of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  88%88%21st of 128Returning production: 88%, 21st of 128 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +7.8+7.848th of 128SP+ rating: +7.8, 48th 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 Georgia Tech's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 2 clear-cut ones account for 0.02 of the 0.07 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 BCQ4 2:30 4th & 19 at GT 32, down 4Went for it; the numbers favored punting−1.2 pts
2. at VTQ2 2:51 4th & 4 at GT 40, up 13Punted; the numbers favored going for it−1.0 pts
3. at BCQ2 7:06 4th & 1 at GT 34, up 7Punted; the numbers favored going for it (close call)−1.0 pts
4. vs UVAQ3 15:00 4th & 4 at midfield, down 3Punted; the numbers favored going for it (close call)−0.7 pts
5. vs MIAQ4 3:44 4th & 10 at MIA 39, down 14Went for it; the numbers favored a field goal (close call)−0.6 pts
6. at UKQ2 0:06 4th & 10 at UK 44, up 14Went for it; the numbers favored a field goal (close call)−0.6 pts
7. at VTQ4 11:01 4th & 4 at VT 18, up 13Kicked a field goal; the numbers favored going for it (close call)−0.5 pts
8. vs UVAQ4 1:55 4th & 16 at UVA 33, up 14Went for it; the numbers favored a field goal (close call)−0.3 pts

Record vs. expectation, 2016

4th of 128 FBS teams at beating the model's pregame expectations

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

1. W

   BC
2. W

   MER
3. W

   VAN
4. L

   CLEM
5. L

   MIA
6. L

   PITT
7. W

   GASO
8. W

   DUKE
9. L

   UNC
10. W

    VT
11. W

    UVA
12. W

    UGA
13. W

    UK

What moved it, 2016

Every game starts at Georgia 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+1.90
• Clock+0.08
• Timeouts+0.01
• Less the pregame edge, counted before kickoff+0.12

Game by game

• BCW 17-14 at BC58% → 95%Before kickoff +8 · On the field +37: Scoreboard +44, Clock +3
• MERW 35-10 vs MER74% → 100%Before kickoff +24 · On the field +26: Scoreboard +27, Clock +2
• VANW 38-7 vs VAN73% → 100%Before kickoff +23 · On the field +27: Scoreboard +29
• CLEML 7-26 vs CLEM19% → 1%Before kickoff −31 · On the field −18: Scoreboard −26, Clock −1
• MIAL 21-35 vs MIA33% → 2%Before kickoff −17 · On the field −31: Scoreboard −40, Clock −2
• PITTL 34-37 at PITT30% → 6%Before kickoff −20 · On the field −24: Scoreboard −30, Possession & field position +1
• GASOW 35-24 vs GASO70% → 98%Before kickoff +20 · On the field +28: Scoreboard +30, Timeouts +1
• DUKEW 38-35 vs DUKE72% → 87%Before kickoff +22 · On the field +15: Scoreboard +25, Timeouts −1
• UNCL 20-48 at UNC28% → 0%Before kickoff −22 · On the field −28: Scoreboard −29
• VTW 30-20 at VT17% → 94%Before kickoff −33 · On the field +77: Scoreboard +58, Possession & field position −3
• UVAW 31-17 vs UVA77% → 98%Before kickoff +27 · On the field +21: Scoreboard +26, Possession & field position −1
• UGAW 28-27 at UGA34% → 79%Before kickoff −16 · On the field +45: Scoreboard +34, Possession & field position +3
• UKW 33-18 at UK62% → 99%Before kickoff +12 · On the field +37: Scoreboard +43, Clock +2

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

Closest call

GT 28-27 VT (2022) - Georgia Tech dropped to a 3.3% win probability before pulling it out.