Columbus defeated Seattle 5-2 in a game that expected goals said was nearly even. The xG split was 3.17–2.85 in Columbus's favor—just 53–47—yet the scoreline separated them by three goals.

The mismatch traced to finishing. Seattle's high-danger chances totaled 7 to Columbus's 4, but the Blue Jackets converted 2 goals from low-danger areas. Those are shots the opposing goalie needs to stop. Columbus overperformed their expected goals by 1.83; Seattle underperformed by 0.85. E. Merzlikins finished at 0.882 SV% (+0.85 vs. expected), while J. Daccord posted 0.852 SV% (−0.83 vs. expected).

Transition play defined the gap. Columbus scored 3 goals on 24 rush attempts. Seattle managed 2 on 21. Both teams weaponized the transition, but Columbus's volume advantage decided it. Shot-attempt control favored Columbus at 62% (28–17 on goal).

The incongruity is clear: Seattle generated more dangerous scoring chances, but Columbus finished their moderate opportunities. Cole Sillinger's wrist shot from the wing (P3, 17:34) typified Columbus's efficiency. The final score masks a game where underlying numbers said close and conversion said Columbus.

The model projects a 2.3–2.7 goal spread favoring Columbus, with the Blue Jackets at 57% win probability. That lean is driven by what the analytics show: Columbus dominates on the underlying metrics.

Columbus owns 52.0% 5v5 expected goals against Seattle's 46.0%. The territorial advantage is even starker in Corsi—the Blue Jackets hit 51.0% to Seattle's 45.0%, meaning Columbus will spend more time in Seattle's end. Neither team has been fortunate relative to talent (Seattle's 1.011 PDO vs Columbus at 1.003), so luck isn't confounding the picture.

The edge belongs to the team that creates better chances more often. That's Columbus.

Seattle's scoring load flows through Shane Wright, who generates 0.77 expected goals per 60 minutes and has converted at a 10.4% shooting rate—high, but not unsustainably so. His four high-danger goals on just eight total have come at the expense of volume: he's picked up 10 assists in the same span. Berkly Catton runs a similar pattern, posting 0.68 xG/60 with five high-danger goals on eight total, though his 8.8% shooting is lower and suggests some regression risk.

Columbus counters with more prolific production. Boone Jenner's 0.98 xG/60 is the highest single rate in this matchup; he's posted 11 goals and 21 assists while generating high-danger chances at a more sustainable rate—just two of his goals have come from prime scoring areas. Mathieu Olivier sits at 0.89 xG/60 and has scored 12 goals on 9 assists, though his 13.3% shooting rate is elevated enough to merit caution.

The data reveals specific defensive vulnerabilities. Chandler Stephenson represents Seattle's weak link; Conor Garland is Columbus's liability on the back end.

Three Stars

• Boone Jenner (CBJ) — 0.98 xG/60, 11G 21A
• Shane Wright (SEA) — 0.77 xG/60, 8G 10A
• Mathieu Olivier (CBJ) — 0.89 xG/60, 12G 9A