The 4-3 overtime result suggested a close game. The underlying numbers said otherwise: Tampa held 63% of 5v5 expected goals (4.57–2.70) and 7-1 in high-danger chances, a dominance that should've produced a blowout, not overtime.

The Lightning controlled shot volume and quality alike. They generated 57% of shot attempts and cashed efficiency: 0.077 xG per shot to Buffalo's 0.055. A. Vasilevskiy made 23 saves on 26 shots (0.885 SV%), while C. Ellis kept the Sabres afloat with 31 saves (0.886 SV%, +0.57 vs expected).

Buffalo scored three times from rush play, mirroring Tampa's total. But two came from low-danger spots—the kind of scoring chance a goalie needs to stop. Tampa showed no such leaks. They scored three times from the rush on 22 chances and converted 2-for-9 on the power play (1.07 xG), demonstrating precision the Sabres never approached.

Jake Guentzel ended it at 4:45 of overtime with a snap shot from the high slot. Kucherov orchestrated the dominance (1G, 3A in 22:24) alongside Guentzel (1G, 1A in 26:07) and D. Raddysh (1G, 1A in 25:48).

The scoreline was deceptive. On nights when teams play to their underlying performance, Tampa's advantage—in both shot volume and shot quality—should've produced more than a one-goal margin.

The model projects a 2.4-2.7 win for Tampa Bay, with the Lightning favored at 56%.

Tampa Bay controls the underlying play on both offensive and defensive efficiency. At 54.0% expected goals versus Buffalo's 50.0%, the Lightning generate better chances at even strength. The Corsi split—53.0% for Tampa, 49.0% for Buffalo—reveals territorial dominance; expect the Lightning to spend most of the game in Buffalo's zone.

Both teams, however, are running unsustainably hot. Buffalo's PDO sits at 1.020, Tampa's at 1.019. PDO measures team puck luck—the combination of on-ice save percentage and shooting percentage—and both figures signal regression ahead. The Sabres may feel this correction more acutely; they're more dependent on conversion rates than the underlying metrics suggest they should be.

On Buffalo's side, Jason Zucker is the offensive anchor at 1.07 xG per 60 minutes. His 14 goals come with a 15.1% shooting percentage, and six of those scores are high-danger chances—a clip that defies sustainability. Josh Doan (1.01 xG/60, 11.5% shooting) offers secondary production, though his own conversion also signals short-term luck.

Tampa counters with Brandon Hagel, whose 1.10 xG/60 and 23 goals represent the most dominant even-strength presence in this matchup. Unlike Zucker, Hagel's underlying metrics and raw output align; his production isn't luck-dependent. Anthony Cirelli (0.95 xG/60, 15 goals) rounds out the scoring with his own 17.0% shooting clip, another sign of positive variance headed toward normalcy.

The model's tilt is structural, not speculative. Better process prevails over better luck. Once PDO regresses—and it will—Buffalo's already-narrow underlying edge disappears entirely.