Calgary's goaltending was decisive. D. Cooley saved 2.9 goals above expected, suppressing Utah's xG advantage (4.86–3.43, 59–41%) enough to make this a 3–1 game instead of a rout.

Utah's control was thorough. They held 62% of shot attempts (32–20), won the high-danger chances (7–4), and scored twice on 34 rush chances.

But they also wasted chances. Utah underperformed their xG by 1.86 goals. Calgary underperformed by 2.43—an underperformance that would have been crippling without Cooley.

Kevin Stenlund's snap shot from the slot (P3, 19:37) was the turning point. K. Vejmelka (19/20 saves, +2.43 vs expected) was equally sharp, and Calgary's net crashing (3 rebound opportunities, 1 converted) provided what little resistance Utah's dominance allowed.

Three Stars

• #4 R. Andersson — 1G in 23:23
• #8 N. Schmaltz — 1A in 19:52
• #91 N. Kadri — 1A in 19:46

The model projects a 2.4–2.8 Utah victory with the Jazz at 57% win probability. The thesis is straightforward: Utah dominates the underlying play. The Jazz own 52.0% expected goals share at 5v5 against Calgary's 47.0%, a five-point gap that manifests as territorial control. They drive Corsi at 53.0%, meaning the puck lives on the Flames' side of the ice for extended stretches. That positioning advantage should yield volume benefits in the scoring areas, offsetting any Calgary counterpunches.

Form tells a murkier story. Utah is -11 on goal differential over the last 10 games, Calgary -16. Both teams are bleeding results, but Calgary's deficit reveals something crucial: the Flames carry a 0.985 PDO, indicating they're running cold by statistical standard. Utah sits at 1.003 PDO, near parity. That gap—luck normalizing away from Calgary, toward Utah—comprises the secondary edge the model prices into its win probability. It's luck in flux, not stable skill.

The complication is rest. Calgary has four days between games, while Utah is on one day's rest. It's a tangible advantage, especially if V. Vanecek, on a back-to-back, either sits or takes the ice fatigued. A fresh starter or a rested backup could absorb Utah's volume. The model acknowledges this but doesn't weight it heavily.

Players to Watch

Calgary

• Blake Coleman — 0.89 xG/60, 16G 12A, 11.4% shooting, 2 high-danger goals
• Matt Coronato — 0.80 xG/60, 10G 16A, 6.6% shooting

Utah

• Dylan Guenther — 1.02 xG/60, 28G 15A, 16.8% shooting, 3 high-danger goals
• Daniil But — 1.01 xG/60, 2G 2A, 5.6% shooting, 1 high-danger goal

Coleman's 11.4% shooting rate is elevated relative to league norms, suggesting some variance inflation in his goal total. Coronato's 6.6% rate is depressed—a regression setup paired with his solid underlying volume. Defensively, Coronato is Calgary's structural weak link; Maveric Lamoureux anchors Utah's vulnerable flank. Guenther, the game's gravitational center, is balanced against Coleman, who despite powering Calgary's offense, is due for normalization downward.

Utah's advantage is clean: better underlying play, better luck positioning, superior personnel. Calgary's rest edge is meaningful but insufficient to overcome the structural gap the model has identified.