Columbus created high-danger chances at a 4-to-1 rate (12–3) and controlled 65% of expected goals (5.49–2.98), yet both goalies' performances suppressed what should have been a more decisive result. E. Merzlikins saved 1.98 goals above expected while K. Lankinen saved 1.49—each overperforming against their respective chances. The scoreline misses what the underlying numbers reveal: E. Merzlikins stole a game Columbus was already winning.

The Blue Jackets held 54% of shot attempts (36–31) and generated superior danger throughout. They recorded 0.070 expected goals per shot versus Vancouver's 0.051, a quality advantage that manifested on the rush: 4 goals on 31 chances, a ruthless conversion rate. Their finish inside the high-danger area betrayed them—0 for 12—but K. Lankinen's perfection there (12 for 12 saves on high-danger looks) negated what could have been a rout.

Kent Johnson's wrist shot from the slot in the third period (10:13) typified Columbus's control. They dominated through shot volume (36 attempts), rebounding aggression (11 opportunities created), and consistent chance quality. Vancouver managed three high-danger chances and underperformed their 2.98 expected goals by 1.98; Columbus underperformed their 5.49 by 1.49. Both teams left goals on the table, but Columbus had far more to leave.

Columbus is the play. The model projects a 2.3–2.9 game and assigns the Blue Jackets a 59% win probability.

The form split is stark. Columbus has posted a 5-4-1 record over its last 10 games; Vancouver sits at -22 goal differential in the same stretch. That's a team performing against one underperforming.

The underlying play backs the projection. Columbus controls 52.0% of 5v5 xG versus Vancouver's 44.0%—an edge that reflects territorial control and the quality of chances being created. The shot-attempt share tells the same story: Blue Jackets at 51.0% Corsi, Canucks at 46.0%. This is consistent play advantage.

PDO adds nuance to Vancouver's position. The Canucks are at 0.974, running cold relative to their underlying metrics, which statistically implies regression ahead. But here's the distinction: regression describes where a team stands relative to its shot quality, not when that correction materializes. Columbus sits at 1.003, almost exactly where its play suggests it should be.

Goaltending presents a complication. Both J. Greaves and K. Lankinen are on back-to-backs, which raises the likelihood of a backup start or diminished performance. A fatigued or replaced starter compounds Columbus's territorial advantage.

Players to Watch

VAN

• Filip Chytil — 1.03 xG/60, 3G 0A, 1 HD goals, 15.0% shooting
• Drew O'Connor — 0.85 xG/60, 13G 11A, 3 HD goals, 11.8% shooting

CBJ

• Boone Jenner — 0.98 xG/60, 11G 21A, 2 HD goals, 9.6% shooting
• Mathieu Olivier — 0.89 xG/60, 12G 9A, 1 HD goals, 13.3% shooting