UAB vs. Middle Tennessee: Final Score & Recap
Final score, recap & advanced stats
UABTeam statsMTSU
- Q4 9:30MTSUZack Dobson 45 Yd Run (Crews Holt Kick)3–27
- Q3 4:40MTSUZack Dobson 12 Yd pass from Brent Stockstill (Crews Holt Kick)3–20
- Q2 2:35MTSUTy Lee 12 Yd pass from Brent Stockstill (Crews Holt Kick)3–13
- Q2 9:57MTSUCrews Holt 24 Yd Field Goal 3–6
- Q2 14:55MTSUCrews Holt 28 Yd Field Goal 3–3
- Q1 8:35UABNick Vogel 35 Yd Field Goal 3–0
How the model called it
What the numbers say
- MTSU lived on explosives rather than sustaining drives — a profile that vanished once those chunk plays were tackled. 15% explosive on a 37% success rate
- PassA.J. Erdely 9/20, 90 YDS, 1 INT
- RushJarrion Street 12 CAR, 40 YDS
- RecKailon Carter 2 REC, 49 YDS
- PassBrent Stockstill 22/29, 261 YDS, 2 TD
- RushChaton Mobley 14 CAR, 52 YDS
- RecTy Lee 7 REC, 100 YDS, 1 TD
This exact spot, historically
empirical, no ratingsMTSU up 17 entering the 4th quarter. Across 841 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q2 2:35MTSU +23%
Brent Stockstill pass complete to Ty Lee for 12 yds for a TD UAB Penalty, offside defense ( Yards) declined (Crews Holt KICK)
- Q3 4:40MTSU +15%
Brent Stockstill pass complete to Zack Dobson for 12 yds for a TD (Crews Holt KICK)
- Q2 9:57MTSU +12%
Crews Holt 24 yd FG GOOD
- Q2 14:55MTSU +10%
Crews Holt 28 yd FG GOOD
- Q3 10:31MTSU +5%
Tavares Thomas run for 4 yds to the MTnSt 30 for a 1ST down
FAQ
What was the final score of UAB vs. Middle Tennessee?
UAB 3, Middle Tennessee 27.
Did Gridpex's model pick hit?
No — the model picked UAB, which didn't hit. We report the misses too.
| UAB | MTSU | |
|---|---|---|
| 89 | Total yards | 394 |
| 90 | Passing yards | 261 |
| -1 | Rushing yards | 133 |
| 8 | First downs | 19 |
| 4-14 | 3rd down | 4-13 |
| 0-0 | 4th down | 0-0 |
| 9/24 | Comp/Att | 22/29 |
| 3.8 | Yards per pass | 9.0 |
| 0.0 | Yards per rush | 3.8 |
| 1 | Turnovers | 0 |
| 5-60 | Penalties | 4-45 |
| 25:16 | Possession | 34:44 |
Costliest call
Q4 14:12 MTSU punt on 4th & 1 at MTSU 49. The model preferred go for it, a gap of 1.43 points.
Drive chart
every possession, start to finish- Q4 9:30MTSUZack Dobson 45 Yd Run (Crews Holt Kick)3–27
- Q3 4:40MTSUZack Dobson 12 Yd pass from Brent Stockstill (Crews Holt Kick)3–20
- Q2 2:35MTSUTy Lee 12 Yd pass from Brent Stockstill (Crews Holt Kick)3–13
- Q2 9:57MTSUCrews Holt 24 Yd Field Goal 3–6
- Q2 14:55MTSUCrews Holt 28 Yd Field Goal 3–3
- Q1 8:35UABNick Vogel 35 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 (MTSU Elo 1437, UAB Elo 1580 for reference), with home-field advantage. That projects MTSU +3.3 (42% 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 — 2018
nationally rankedThe matchup, in context
series history + adjusted profiles#41 of 109 in 2018 by biggest miss · #92 of 122 in 2018 by longest odds.
The 2018 upset archive →UAB leads 5–3 · UAB has won 2 straight · 50% have been one-possession games
| UAB | MTSU | |
|---|---|---|
| +11.7 (#27) | CORE overall | -2.0 (#77) |
| +5 / -7 | offense / defense | -4 / -2 |
| 2.39 | points / drive | 1.99 |
| 1.49 | allowed / drive | 2.09 |
| 31% | three-and-outs | 25% |
| -7 | pass over expected | +6 |
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 →