Vegas dominated possession but Montreal won the one that mattered: goaltending. The Canadiens prevailed 4–1 despite expected goals splitting 4.11–4.47, a near-even game that the Golden Knights lost 3.1 goals' worth on execution.

The shot volume belonged to Vegas—31 attempts to Montreal's 19. Yet Montreal squeezed greater danger into fewer looks, recording 0.109 expected goals per shot versus Vegas's 0.055. That efficiency gap proved decisive.

S. Montembeault stopped 30 of 31 shots and saved 3.11 goals above what the model predicted—a performance that transformed a statistically close game into a rout. A. Schmid, meanwhile, conceded 1.47 more goals than expected, meaning the narrative was written as much by save percentages (Montembeault 0.968, Schmid 0.833) as by play quality.

High-danger chances tilted Montreal's way, 11 to 8. Montreal also capitalized on transition, netting three times on 22 rush chances—a conversion rate that punished Vegas for surrendering odd-man situations. Vegas created seven rebound chances without converting any; Montreal generated three without scoring. Neither team profited from net-front chaos, but Montreal's discipline elsewhere compensated.

J. Slafkovský's wrist shot from the slot at 18:03 was the turning point. Montreal's shot quality edge proved insurmountable thereafter.

Vegas owns this matchup on paper. The model projects a 2.3–2.7 game in favor of the Golden Knights, who sit at 58% win probability.

The underlying numbers explain the lean. Vegas controls the territorial game at 54.0% 5v5 xG versus Montreal's 48.0%, a meaningful edge in shot quality that compounds across 60 minutes. That advantage widens on shot volume: the Knights drive Corsi at 52.0% to Montreal's 49.0%, meaning Vegas will likely tilt the ice their direction.

But PDO complicates the picture. Vegas is running cold at 0.983, which suggests positive regression ahead—the puck has gone against them more than underlying play warrants. Montreal sits at the opposite extreme: 1.018 PDO means they've been fortunate, which typically means some regression is coming. This divergence matters. If Vegas regresses upward and Montreal regresses downward simultaneously, the model's projection could understate the gap.

Goaltending adds another layer of uncertainty. Both A. Schmid and J. Dobes play on back-to-backs, which raises the specter of backup appearances or fatigued starters. That unpredictability could swing expected value either way.

Montreal's recent form underscores their need to win. The Canadiens sit at -11 goal differential over their last 10 games, a troubling stretch that compounds the challenge of facing an opponent that controls play the way Vegas does.

The individual matchups favor Vegas, though Montreal has standout talent. Cole Caufield leads the Canadiens at 0.97 xG per 60 minutes with 33 goals and 16 assists, posting a 20.0% shooting percentage and 1 high-danger goal. Oliver Kapanen adds secondary punch at 0.83 xG/60 with 19 goals, 12 assists, 4 high-danger goals, and a 17.8% shot rate.

Vegas counters with Brandon Saad, who generates 0.91 xG/60 despite his modest 3 goals and 6 assists on a 4.1% shooting percentage—a mismatch between underlying play and results that fits the PDO regression narrative. Tomas Hertl rounds out the Knights' forward advantage at 0.88 xG/60 with 5 goals, 17 assists, and 1 high-danger goal on a 4.3% shot rate.

Defensively, Mike Matheson represents Montreal's weak link, while Rasmus Andersson carries similar responsibility for Vegas. Both sides will target these vulnerabilities, though Vegas' superior puck possession should generate more scoring chances regardless.