Central Michigan vs. Bowling Green: Final Score & Recap
Final score, recap & advanced stats
CMUTeam statsBGSU
- Q3 7:09CMUCade Graham 47 Yd Field Goal 27–6
- Q3 11:06CMUAngel Flores 3 Yd Run (Cade Graham Kick)24–6
- Q2 0:53BGSUJackson Kleather 49 Yd Field Goal 17–6
- Q2 3:48CMUCade Graham 38 Yd Field Goal 17–3
- Q2 8:04CMUAngel Flores 6 Yd Run (Cade Graham Kick)14–3
- Q2 13:39CMUAngel Flores 1 Yd Run (Cade Graham Kick)7–3
- Q1 10:43BGSUJackson Kleather 43 Yd Field Goal 0–3
How the model called it
What the numbers say
- BGSU lived on explosives rather than sustaining drives — a profile that vanished once those chunk plays were tackled. 14% explosive on a 37% success rate
- PassJoe Labas 2/4, 72 YDS
- RushAngel Flores 18 CAR, 72 YDS, 3 TD
- RecCollin Payne 1 REC, 63 YDS
- PassLucian Anderson III 17/25, 153 YDS, 2 INT
- RushLucian Anderson III 11 CAR, 53 YDS
- RecRJ Garcia II 3 REC, 60 YDS
This exact spot, historically
empirical, no ratingsCMU up 21 entering the 4th quarter. Across 671 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q3 11:06CMU +23%
Angel Flores run for 3 yds for a TD (Cade Graham KICK)
- Q2 8:04CMU +22%
Angel Flores run for 6 yds for a TD (Cade Graham KICK)
- Q2 13:39CMU +17%
Angel Flores run for 1 yd for a TD (Cade Graham KICK)
- Q2 3:48CMU +15%
Cade Graham 38 yd FG GOOD
- Q3 7:09CMU +9%
Cade Graham 47 yd FG GOOD
- Q2 0:53BGSU +8%
Jackson Kleather 49 yd FG GOOD
FAQ
What was the final score of Central Michigan vs. Bowling Green?
Central Michigan 27, Bowling Green 6.
Did Gridpex's model pick hit?
No — the model picked BGSU, which didn't hit. We report the misses too.
| CMU | BGSU | |
|---|---|---|
| 276 | Total yards | 310 |
| 73 | Passing yards | 153 |
| 203 | Rushing yards | 157 |
| 14 | First downs | 14 |
| 5-12 | 3rd down | 5-15 |
| 0-0 | 4th down | 1-4 |
| 3/5 | Comp/Att | 17/25 |
| 14.6 | Yards per pass | 6.1 |
| 4.4 | Yards per rush | 4.4 |
| 0 | Turnovers | 2 |
| 10-74 | Penalties | 15-125 |
| 31:20 | Possession | 28:40 |
Costliest call
Q4 5:17 CMU punt on 4th & 13 at BGSU 34. The model preferred field goal, a gap of 1.00 points.
Drive chart
every possession, start to finish- Q3 7:09CMUCade Graham 47 Yd Field Goal 27–6
- Q3 11:06CMUAngel Flores 3 Yd Run (Cade Graham Kick)24–6
- Q2 0:53BGSUJackson Kleather 49 Yd Field Goal 17–6
- Q2 3:48CMUCade Graham 38 Yd Field Goal 17–3
- Q2 8:04CMUAngel Flores 6 Yd Run (Cade Graham Kick)14–3
- Q2 13:39CMUAngel Flores 1 Yd Run (Cade Graham Kick)7–3
- Q1 10:43BGSUJackson Kleather 43 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 (BGSU Elo 1422, CMU Elo 1110 for reference), with home-field advantage. That projects BGSU -14.9 (84% to win) — 11.9 points clear of BGSU's market line of -3. 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 — 2025
nationally rankedThe matchup, in context
series history + adjusted profiles#42 of 112 in 2025 by biggest miss · #92 of 129 in 2025 by longest odds.
The 2025 upset archive →Central Michigan leads 17–16 · 42% have been one-possession games
| CMU | BGSU | |
|---|---|---|
| -6.9 (#87) | CORE overall | -18.8 (#122) |
| -4 / +3 | offense / defense | -16 / +3 |
| 1.94 | points / drive | 1.66 |
| 2.13 | allowed / drive | 2.20 |
| 31% | three-and-outs | 30% |
| -13 | pass over expected | -11 |
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 →