Clemson vs. Georgia Tech: Final Score & Recap
Final score, recap & advanced stats
CLEMTeam statsGT
- Q4 8:25GTHarrison Butker 41 Yd Field Goal 6–28
- Q3 1:23GTChris Milton 62 Yd Interception Return (Two-Point Run Conversion Failed)6–25
- Q3 5:47CLEMAmmon Lakip 32 Yd Field Goal 6–19
- Q3 9:14GTHarrison Butker 32 Yd Field Goal 3–19
- Q3 12:45GTDeAndre Smelter 5 Yd pass from Justin Thomas (Harrison Butker Kick)3–16
- Q2 9:07GTHarrison Butker 25 Yd Field Goal 3–9
- Q1 0:22GTJamal Golden 85 Yd Interception Return (Two-Point Run Conversion Failed)3–6
- Q1 6:30CLEMAmmon Lakip 27 Yd Field Goal 3–0
How the model called it
What the numbers say
- GT played behind the sticks — third downs that long convert rarely, and CLEM did not face the same ones. 3rd & 8.1 vs 3rd & 6.0
- GT lived on explosives rather than sustaining drives — a profile that vanished once those chunk plays were tackled. 17% explosive on a 38% success rate
- PassDeshaun Watson 4/6, 21 YDS
- RushWayne Gallman 15 CAR, 88 YDS
- RecArtavis Scott 3 REC, 19 YDS
- PassJustin Thomas 8/11, 102 YDS, 1 TD
- RushSynjyn Days 20 CAR, 89 YDS
- RecDeAndre Smelter 5 REC, 77 YDS, 1 TD
This exact spot, historically
empirical, no ratingsGT up 19 entering the 4th quarter. Across 1,041 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q3 12:45GT +16%
Justin Thomas pass complete to DeAndre Smelter for 5 yds for a TD, (Harrison Butker KICK)
- Q1 0:22GT +15%
Jamal Golden 85 Yd Interception Return (Two-Point Run Conversion Failed)
- Q2 9:07GT +9%
Harrison Butker 25 yd FG GOOD
- Q1 6:30CLEM +8%
Ammon Lakip 27 yd FG GOOD
- Q3 1:23GT +6%
Chris Milton 62 Yd Interception Return (Two-Point Run Conversion Failed)
FAQ
What was the final score of Clemson vs. Georgia Tech?
Clemson 6, Georgia Tech 28.
Did Gridpex's model pick hit?
Yes — the model's pick (GT) was correct.
| CLEM | GT | |
|---|---|---|
| 190 | Total yards | 353 |
| 59 | Passing yards | 102 |
| 131 | Rushing yards | 251 |
| 10 | First downs | 16 |
| 3-13 | 3rd down | 7-14 |
| 0-0 | 4th down | 0-1 |
| 11/21 | Comp/Att | 8/11 |
| 2.8 | Yards per pass | 9.3 |
| 4.0 | Yards per rush | 5.0 |
| 3 | Turnovers | 2 |
| 3-21 | Penalties | 2-10 |
| 24:37 | Possession | 34:55 |
Costliest call
Q2 0:01 GT go for it on 4th & 14 at GT 27. The model preferred punt, a gap of 1.14 points.
Drive chart
every possession, start to finish- Q4 8:25GTHarrison Butker 41 Yd Field Goal 6–28
- Q3 1:23GTChris Milton 62 Yd Interception Return (Two-Point Run Conversion Failed)6–25
- Q3 5:47CLEMAmmon Lakip 32 Yd Field Goal 6–19
- Q3 9:14GTHarrison Butker 32 Yd Field Goal 3–19
- Q3 12:45GTDeAndre Smelter 5 Yd pass from Justin Thomas (Harrison Butker Kick)3–16
- Q2 9:07GTHarrison Butker 25 Yd Field Goal 3–9
- Q1 0:22GTJamal Golden 85 Yd Interception Return (Two-Point Run Conversion Failed)3–6
- Q1 6:30CLEMAmmon Lakip 27 Yd Field Goal 3–0
Model prediction
how the number is builtOur model simulates the game drive by drive from each side's opponent-adjusted efficiency (GT Elo 1791, CLEM Elo 1817 for reference), with home-field advantage. That projects GT -1.4 (55% to win) — 3.4 points clear of GT's market line of +2. That is a disagreement, not a betting edge — sides we favour have not covered at better than breakeven.
Why that percentage is worth reading: across 604 graded in-season games, the calls this model put near 58% came in at 58.2%. The full calibration table is published, bin by bin. Early in the season the cold-start path runs instead and calibrates less well (Brier 0.2028 against 0.1889).
Model as of Sep 1 · through week 1 · drive simulation
Season form — 2014
nationally rankedThe matchup, in context
series history + adjusted profiles#52 of 94 in 2014 by biggest miss · #86 of 94 in 2014 by longest odds.
The 2014 upset archive →Georgia Tech leads 52–34–2 · 38% have been one-possession games
| CLEM | GT | |
|---|---|---|
| 1.77 | points / drive | 3.47 |
| 1.07 | allowed / drive | 2.23 |
| 37% | three-and-outs | 13% |
Bold is the side ahead. CORE strips the situation from every play and solves the schedule out across the league, so these compare two teams that never met.
Key matchups
The analyst read: each team's offense splits crossed against the opponent's defense, with the edges called out.
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Where this number comes from. Every projection on this page is produced by the same model, run before kickoff on opponent-adjusted efficiency, power ratings and situational data — walk-forward validated on eleven seasons and never adjusted after the fact. How the model works →