Maryland vs. Michigan State: Final Score & Recap
Final score, recap & advanced stats


MDTeam statsMSU
- Q4 3:18MDOctavian Smith Jr. 31 Yd pass from Taulia Tagovailoa (Jack Howes Kick)31–9
- Q4 11:00MDJack Howes 48 Yd Field Goal 24–9
- Q3 3:44MSUTyrell Henry 9 Yd pass from Noah Kim (Two-Point Pass Conversion Failed)21–9
- Q2 3:39MSUJonathan Kim 37 Yd Field Goal 21–3
- Q2 8:39MDTaulia Tagovailoa 1 Yd Run (Jack Howes Kick)21–0
- Q2 11:28MDTyrese Chambers 12 Yd pass from Taulia Tagovailoa (Jack Howes Kick)14–0
- Q1 7:52MDSean Greeley 1 Yd pass from Taulia Tagovailoa (Jack Howes Kick)7–0
How the model called it
- PassTaulia Tagovailoa 21/36, 223 YDS, 3 TD, 1 INT
- RushColby McDonald 5 CAR, 38 YDS
- RecTai Felton 3 REC, 67 YDS
- PassNoah Kim 18/32, 190 YDS, 1 TD, 2 INT
- RushNathan Carter 19 CAR, 97 YDS
- RecMontorie Foster Jr. 6 REC, 67 YDS
This exact spot, historically
empirical, no ratingsMD up 12 entering the 4th quarter. Across 1,516 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q1 7:52MD +17%
Taulia Tagovailoa pass complete to Sean Greeley for 1 yd for a TD (Jack Howes KICK)
- Q2 11:28MD +14%
Taulia Tagovailoa pass complete to Tyrese Chambers for 12 yds for a TD (Jack Howes KICK)
- Q2 8:39MD +7%
Taulia Tagovailoa run for 1 yd for a TD (Jack Howes KICK)
- Q3 3:44MSU +7%
Tyrell Henry 9 Yd pass from Noah Kim (Two-Point Pass Conversion Failed)
FAQ
What was the final score of Maryland vs. Michigan State?
Maryland 31, Michigan State 9.
Did Gridpex's model pick hit?
Yes — the model's pick (MD) was correct.
| MD | MSU | |
|---|---|---|
| 362 | Total yards | 376 |
| 223 | Passing yards | 274 |
| 139 | Rushing yards | 102 |
| 18 | First downs | 26 |
| 6-15 | 3rd down | 5-13 |
| 2-2 | 4th down | 3-4 |
| 21/36 | Comp/Att | 26/44 |
| 6.2 | Yards per pass | 6.2 |
| 4.5 | Yards per rush | 3.3 |
| 1 | Turnovers | 5 |
| 4-50 | Penalties | 6-70 |
| 28:36 | Possession | 31:24 |
Costliest call
Q3 15:00 MD go for it on 4th & 10 at MD 25. The model preferred punt, a gap of 1.00 points.
Drive chart
every possession, start to finish- Q4 3:18MDOctavian Smith Jr. 31 Yd pass from Taulia Tagovailoa (Jack Howes Kick)31–9
- Q4 11:00MDJack Howes 48 Yd Field Goal 24–9
- Q3 3:44MSUTyrell Henry 9 Yd pass from Noah Kim (Two-Point Pass Conversion Failed)21–9
- Q2 3:39MSUJonathan Kim 37 Yd Field Goal 21–3
- Q2 8:39MDTaulia Tagovailoa 1 Yd Run (Jack Howes Kick)21–0
- Q2 11:28MDTyrese Chambers 12 Yd pass from Taulia Tagovailoa (Jack Howes Kick)14–0
- Q1 7:52MDSean Greeley 1 Yd pass from Taulia Tagovailoa (Jack Howes Kick)7–0
Model prediction
how the number is builtOur model simulates the game drive by drive from each side's opponent-adjusted efficiency (MSU Elo 1509, MD Elo 1646 for reference), with home-field advantage. That projects MSU +3.1 (43% to win) — 4.4 points clear of MSU's market line of +7.5. 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 profilesMichigan State leads 12–4 · Michigan State has won 2 straight · 25% have been one-possession games
| MD | MSU | |
|---|---|---|
| +16.7 (#17) | CORE overall | -14.5 (#108) |
| +8 / -9 | offense / defense | -10 / +4 |
| 2.35 | points / drive | 0.94 |
| 2.03 | allowed / drive | 2.40 |
| 24% | three-and-outs | 38% |
| +11 | pass over expected | +4 |
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 →
