Georgia Tech vs. Pittsburgh: Final Score & Recap
Final score, recap & advanced stats
GTTeam statsPITT
- Q4 0:16PITTJaden Bradley 18 Yd pass from Kedon Slovis (Ben Sauls Kick)26–21
- Q4 1:25GTJeff Sims 18 Yd Run (Gavin Stewart Kick)26–14
- Q4 1:57PITTJaden Bradley 26 Yd pass from Kedon Slovis (Ben Sauls Kick)19–14
- Q4 10:30GTE.J. Jenkins 21 Yd pass from Jeff Sims (Gavin Stewart Kick)19–7
- Q4 12:40GTGavin Stewart 30 Yd Field Goal 12–7
- Q3 8:36GTGavin Stewart 40 Yd Field Goal 9–7
- Q2 1:04PITTGavin Bartholomew 29 Yd pass from Kedon Slovis (Ben Sauls Kick)6–7
- Q2 2:50GTGavin Stewart 33 Yd Field Goal 6–0
- Q1 11:14GTGavin Stewart 37 Yd Field Goal 3–0
How the model called it
- PassJeff Sims 11/26, 102 YDS, 1 TD
- RushHassan Hall 20 CAR, 157 YDS
- RecE.J. Jenkins 2 REC, 54 YDS, 1 TD
- PassKedon Slovis 26/45, 305 YDS, 3 TD, 1 INT
- RushVincent Davis Jr. 15 CAR, 80 YDS
- RecJared Wayne 6 REC, 89 YDS
This exact spot, historically
empirical, no ratingsGT up 2 entering the 4th quarter. Across 1,937 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q4 10:30GT +32%
Jeff Sims pass complete to E.J. Jenkins for 21 yds for a TD, (Gavin Stewart KICK)
- Q4 1:40GT +28%
Hassan Hall run for 63 yds to the Pitt 10 for a 1ST down
- Q4 12:40GT +20%
Gavin Stewart 30 yd FG GOOD
- Q2 1:04PITT +19%
Kedon Slovis pass complete to Gavin Bartholomew for 29 yds for a TD, (Ben Sauls KICK)
- Q4 1:57PITT +16%
Kedon Slovis pass complete to Jaden Bradley for 26 yds for a TD, (Ben Sauls KICK)
- Q2 2:50GT +15%
Gavin Stewart 33 yd FG GOOD
FAQ
What was the final score of Georgia Tech vs. Pittsburgh?
Georgia Tech 26, Pittsburgh 21.
Did Gridpex's model pick hit?
No — the model picked PITT, which didn't hit. We report the misses too.
| GT | PITT | |
|---|---|---|
| 334 | Total yards | 411 |
| 102 | Passing yards | 305 |
| 232 | Rushing yards | 106 |
| 17 | First downs | 25 |
| 5-17 | 3rd down | 2-12 |
| 0-1 | 4th down | 1-2 |
| 11/27 | Comp/Att | 26/45 |
| 3.8 | Yards per pass | 6.8 |
| 5.3 | Yards per rush | 3.4 |
| 0 | Turnovers | 3 |
| 4-43 | Penalties | 12-75 |
| 31:04 | Possession | 28:56 |
Costliest call
Q2 2:50 GT field goal on 4th & 1 at PITT 16. The model preferred go for it, a gap of 0.92 points.
Drive chart
every possession, start to finish- Q4 0:16PITTJaden Bradley 18 Yd pass from Kedon Slovis (Ben Sauls Kick)26–21
- Q4 1:25GTJeff Sims 18 Yd Run (Gavin Stewart Kick)26–14
- Q4 1:57PITTJaden Bradley 26 Yd pass from Kedon Slovis (Ben Sauls Kick)19–14
- Q4 10:30GTE.J. Jenkins 21 Yd pass from Jeff Sims (Gavin Stewart Kick)19–7
- Q4 12:40GTGavin Stewart 30 Yd Field Goal 12–7
- Q3 8:36GTGavin Stewart 40 Yd Field Goal 9–7
- Q2 1:04PITTGavin Bartholomew 29 Yd pass from Kedon Slovis (Ben Sauls Kick)6–7
- Q2 2:50GTGavin Stewart 33 Yd Field Goal 6–0
- Q1 11:14GTGavin Stewart 37 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 (PITT Elo 1695, GT Elo 1235 for reference), with home-field advantage. That projects PITT -20.8 (91% to win), essentially in line with the market.
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 — 2022
nationally rankedThe matchup, in context
series history + adjusted profiles#34 of 108 in 2022 by biggest miss · #6 of 132 in 2022 by longest odds · #58 of 62 in 2022 by biggest poll gap.
The 2022 upset archive →Pittsburgh leads 12–6 · 39% have been one-possession games
| GT | PITT | |
|---|---|---|
| -5.7 (#87) | CORE overall | +16.4 (#14) |
| -10 / -4 | offense / defense | +1 / -15 |
| 1.22 | points / drive | 2.08 |
| 2.26 | allowed / drive | 1.56 |
| 35% | three-and-outs | 23% |
| -1 | pass over expected | -2 |
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 →