Clemson vs. North Carolina: Final Score & Recap
Final score, recap & advanced stats
CLEMTeam statsUNC
- Q4 10:25UNCBenjamin Hall 11 Yd Run (Rece Verhoff Kick)38–10
- Q4 13:20CLEMNolan Hauser 27 Yd Field Goal 38–3
- Q2 2:02CLEMChristian Bentancur 8 Yd pass from Cade Klubnik (Nolan Hauser Kick)35–3
- Q1 0:01CLEMAdam Randall 23 Yd pass from Cade Klubnik (Nolan Hauser Kick)28–3
- Q1 4:15CLEMChristian Bentancur 45 Yd pass from Cade Klubnik (Nolan Hauser Kick)21–3
- Q1 8:54CLEMAdam Randall 35 Yd pass from Cade Klubnik (Nolan Hauser Kick)14–3
- Q1 10:02UNCRece Verhoff 35 Yd Field Goal 7–3
- Q1 14:49CLEMT.J. Moore 75 Yd pass from Antonio Williams (Nolan Hauser Kick)7–0
How the model called it
What the numbers say
- CLEM lived on explosives rather than sustaining drives — a profile that vanished once those chunk plays were tackled. 13% explosive on a 39% success rate
- PassCade Klubnik 22/24, 254 YDS, 4 TD
- RushAdam Randall 8 CAR, 30 YDS
- RecT.J. Moore 5 REC, 108 YDS, 1 TD
- PassMax Johnson 26/42, 208 YDS
- RushBenjamin Hall 5 CAR, 24 YDS, 1 TD
- RecJordan Shipp 5 REC, 41 YDS
This exact spot, historically
empirical, no ratingsCLEM up 32 entering the 4th quarter. Across 373 historically comparable game states (within ±2 pts and ±3 min, from 3,056 games):
- Q1 8:54CLEM +12%
Cade Klubnik pass complete to Adam Randall for 35 yds for a TD (Nolan Hauser KICK)
- Q1 4:15CLEM +7%
Cade Klubnik pass complete to Christian Bentancur for 45 yds for a TD (Nolan Hauser KICK)
- Q1 10:02UNC +6%
Rece Verhoff 35 yd FG GOOD
FAQ
What was the final score of Clemson vs. North Carolina?
Clemson 38, North Carolina 10.
Did Gridpex's model pick hit?
Yes — the model's pick (CLEM) was correct.
| CLEM | UNC | |
|---|---|---|
| 488 | Total yards | 265 |
| 399 | Passing yards | 208 |
| 89 | Rushing yards | 57 |
| 23 | First downs | 19 |
| 4-12 | 3rd down | 2-11 |
| 3-4 | 4th down | 0-1 |
| 30/39 | Comp/Att | 26/42 |
| 10.2 | Yards per pass | 5.0 |
| 2.9 | Yards per rush | 3.2 |
| 1 | Turnovers | 0 |
| 7-85 | Penalties | 8-75 |
| 32:25 | Possession | 27:35 |
Costliest call
Q1 10:02 UNC field goal on 4th & 1 at CLEM 16. The model preferred go for it, a gap of 0.92 points.
Drive chart
every possession, start to finish- Q4 10:25UNCBenjamin Hall 11 Yd Run (Rece Verhoff Kick)38–10
- Q4 13:20CLEMNolan Hauser 27 Yd Field Goal 38–3
- Q2 2:02CLEMChristian Bentancur 8 Yd pass from Cade Klubnik (Nolan Hauser Kick)35–3
- Q1 0:01CLEMAdam Randall 23 Yd pass from Cade Klubnik (Nolan Hauser Kick)28–3
- Q1 4:15CLEMChristian Bentancur 45 Yd pass from Cade Klubnik (Nolan Hauser Kick)21–3
- Q1 8:54CLEMAdam Randall 35 Yd pass from Cade Klubnik (Nolan Hauser Kick)14–3
- Q1 10:02UNCRece Verhoff 35 Yd Field Goal 7–3
- Q1 14:49CLEMT.J. Moore 75 Yd pass from Antonio Williams (Nolan Hauser Kick)7–0
Model prediction
how the number is builtOur model simulates the game drive by drive from each side's opponent-adjusted efficiency (UNC Elo 1388, CLEM Elo 1642 for reference), with home-field advantage. That projects UNC +7.8 (31% to win) — 7.2 points clear of UNC's market line of +15. 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 15 · through week 2 · drive simulation
Season form — 2025
nationally rankedThe matchup, in context
series history + adjusted profilesClemson leads 40–18–1 · Clemson has won 7 straight · 41% have been one-possession games
| CLEM | UNC | |
|---|---|---|
| +4.9 (#56) | CORE overall | -10.5 (#97) |
| +2 / -3 | offense / defense | -8 / +3 |
| 2.25 | points / drive | 1.67 |
| 1.84 | allowed / drive | 2.43 |
| 26% | three-and-outs | 37% |
| +9 | 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 →