Georgia Tech vs. Miami: Final Score & Recap
Final score, recap & advanced stats
GTTeam statsMIA
- Q4 0:01GTChristian Leary 44 Yd pass from Haynes King (Two-Point Run Conversion Failed)23–20
- Q4 6:23MIAAndres Borregales 39 Yd Field Goal 17–20
- Q4 9:55MIAHenry Parrish Jr. 3 Yd Run (Andres Borregales Kick)17–17
- Q4 12:11GTAidan Birr 27 Yd Field Goal 17–10
- Q3 1:09GTJamal Haynes 4 Yd Run (Aidan Birr Kick)14–10
- Q3 3:19GTHaynes King 6 Yd Run (Aidan Birr Kick)7–10
- Q3 6:37MIARiley Williams 22 Yd pass from Tyler Van Dyke (Andres Borregales Kick)0–10
- Q2 0:00MIAAndres Borregales 30 Yd Field Goal 0–3
How the model called it
- PassHaynes King 12/25, 151 YDS, 1 TD, 2 INT
- RushHaynes King 10 CAR, 46 YDS, 1 TD
- RecChristian Leary 1 REC, 44 YDS, 1 TD
- PassTyler Van Dyke 24/36, 288 YDS, 1 TD, 3 INT
- RushDon Chaney 24 CAR, 106 YDS
- RecXavier Restrepo 12 REC, 123 YDS
This exact spot, historically
empirical, no ratingsGT up 4 entering the 4th quarter. Across 1,446 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q4 0:01GT +98%
Georgia Tech Penalty, Delay Of Game (TEAM) to the MIA 8
- Q4 9:55MIA +40%
Henry Parrish Jr. run for 3 yds for a TD (Andres Borregales KICK)
- Q3 1:09GT +32%
Jamal Haynes run for 4 yds for a TD (Aidan Birr KICK)
- Q4 0:33MIA +29%
Donald Chaney Jr. run for 4 yds to the GT 26 fumbled, recovered by GT Kyle Kennard
- Q3 3:19GT +19%
Haynes King run for 6 yds for a TD (Aidan Birr KICK)
- Q4 8:22MIA +17%
Henry Parrish Jr. run for 3 yds to the GT 11
FAQ
What was the final score of Georgia Tech vs. Miami?
Georgia Tech 23, Miami 20.
Did Gridpex's model pick hit?
No — the model picked MIA, which didn't hit. We report the misses too.
| GT | MIA | |
|---|---|---|
| 250 | Total yards | 453 |
| 151 | Passing yards | 288 |
| 99 | Rushing yards | 165 |
| 13 | First downs | 23 |
| 5-13 | 3rd down | 8-16 |
| 0-0 | 4th down | 0-1 |
| 12/26 | Comp/Att | 24/36 |
| 5.8 | Yards per pass | 8.0 |
| 3.7 | Yards per rush | 3.5 |
| 2 | Turnovers | 5 |
| 11-67 | Penalties | 6-80 |
| 24:34 | Possession | 35:26 |
Costliest call
Q3 12:06 MIA punt on 4th & 3 at MIA 49. The model preferred go for it, a gap of 0.58 points.
Drive chart
every possession, start to finish- Q4 0:01GTChristian Leary 44 Yd pass from Haynes King (Two-Point Run Conversion Failed)23–20
- Q4 6:23MIAAndres Borregales 39 Yd Field Goal 17–20
- Q4 9:55MIAHenry Parrish Jr. 3 Yd Run (Andres Borregales Kick)17–17
- Q4 12:11GTAidan Birr 27 Yd Field Goal 17–10
- Q3 1:09GTJamal Haynes 4 Yd Run (Aidan Birr Kick)14–10
- Q3 3:19GTHaynes King 6 Yd Run (Aidan Birr Kick)7–10
- Q3 6:37MIARiley Williams 22 Yd pass from Tyler Van Dyke (Andres Borregales Kick)0–10
- Q2 0:00MIAAndres Borregales 30 Yd Field Goal 0–3
Model prediction
how the number is builtOur model simulates the game drive by drive from each side's opponent-adjusted efficiency (MIA Elo 1584, GT Elo 1349 for reference), with home-field advantage. That projects MIA -11.8 (79% to win) — 7.2 points clear of GT's market line of -19. 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 — 2023
nationally rankedThe matchup, in context
series history + adjusted profiles#46 of 117 in 2023 by biggest miss · #9 of 127 in 2023 by longest odds · #18 of 51 in 2023 by biggest poll gap.
The 2023 upset archive →Georgia Tech leads 15–14 · Georgia Tech has won 2 straight · 48% have been one-possession games
| GT | MIA | |
|---|---|---|
| +0.5 (#58) | CORE overall | +13.2 (#28) |
| +7 / +6 | offense / defense | +8 / -5 |
| 2.52 | points / drive | 2.54 |
| 2.72 | allowed / drive | 2.02 |
| 22% | three-and-outs | 22% |
| -7 | pass over expected | +1 |
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 →