{"id":31404,"date":"2026-01-19T10:51:50","date_gmt":"2026-01-19T10:51:50","guid":{"rendered":"https:\/\/atswins.ai\/blog\/?p=31404"},"modified":"2026-01-20T05:22:45","modified_gmt":"2026-01-20T05:22:45","slug":"looking-past-the-records-in-penguins-and-kraken","status":"publish","type":"post","link":"https:\/\/atswins.ai\/blog\/looking-past-the-records-in-penguins-and-kraken\/","title":{"rendered":"Looking Past the Records in Penguins and Kraken"},"content":{"rendered":"
\n
\n
\n
\n
\n
\n
\n
\n

The Pittsburgh Penguins and Seattle Kraken do not always grab national headlines, but when these two teams meet, the details matter. This matchup brings together a veteran Penguins roster that still knows how to control games and a Kraken team that relies on structure, goaltending, and patience. On the surface, the numbers look close. Dig deeper, and a clearer picture starts to form.<\/p>\n

This game is not about flash. It is about execution, discipline, and which team can create the most quality chances when it matters most. When all the data, form, and context are lined up, Pittsburgh holds a meaningful edge that shows up again and again across models and metrics.<\/p>\n

Let\u2019s break down why.<\/p>\n

\n

Current Team Form Sets the Tone<\/h2>\n

Pittsburgh enters this matchup playing efficient hockey. Their season average of 3.11 goals per game<\/strong> stands out immediately, especially when compared to Seattle\u2019s 2.69 goals per game<\/strong>. That difference may look small, but over 60 minutes, it matters.<\/p>\n

Defensively, both teams allow 2.86 goals per game<\/strong>, which tells us something important. The separation in this matchup is not defense. It is an offense and how consistently each team turns puck possession into real scoring chances.<\/p>\n

Seattle has been competitive, especially at home, but their recent results have leaned heavily on close games and goaltending performance. Pittsburgh, on the other hand, has generated offense more reliably, even in tougher matchups and on the road.<\/p>\n

\n

Match Context Favors Pittsburgh\u2019s Style<\/h2>\n

This game sets up well for Pittsburgh\u2019s strengths. Seattle prefers slower, controlled games with fewer rush chances. Pittsburgh is comfortable in that environment. They do not need chaos to score. They can work the puck down low, win battles along the boards, and capitalize on mistakes.<\/p>\n

The Penguins also travel well. Their scoring does not drop off sharply away from home, and their special teams remain effective regardless of venue. Seattle\u2019s home ice advantage tends to limit opponents, but it does not eliminate high-skill plays or disciplined pressure.<\/p>\n

That balance matters in a game projected to be close from start to finish.<\/p>\n

\n

Key Player Impact Tilts the Ice<\/h2>\n

Sidney Crosby remains one of the most reliable centers in hockey. His impact goes beyond goals and assists. He drives possession, wins faceoffs, and forces defensive adjustments every shift. Against a Seattle team that relies on structure, Crosby\u2019s ability to break coverage is a major factor.<\/p>\n

Pittsburgh\u2019s power play is another difference-maker. At 28.7%<\/strong>, it is one of the most efficient units in the league. Seattle\u2019s penalty kill is solid but not elite, and facing a power play that moves the puck quickly and creates traffic can shift momentum fast.<\/p>\n

Seattle\u2019s offense relies more on balance than star power. While players like Jared McCann can finish, the Kraken do not have the same game-breaking presence. That means their margin for error is smaller if they fall behind.<\/p>\n

\n

Advanced Metrics Support the Penguins<\/h2>\n

The underlying numbers back up what the scoreboard shows.<\/p>\n

Pittsburgh holds a positive edge in Corsi and Fenwick<\/strong>, indicating stronger puck possession and shot quality over time. These metrics matter because they are more predictive than short-term results. They tell us which team is driving play, not just reacting.<\/p>\n

Seattle\u2019s recent success has come with a slightly elevated PDO<\/strong>, which often points to goaltending and shooting percentages running a bit hot. That does not mean regression is guaranteed, but it does suggest less room for error.<\/p>\n

Pittsburgh\u2019s numbers, by contrast, are stable and sustainable. They are not overperforming. They are playing to their expected level.<\/p>\n

\n

Goaltending Sets the Floor, Not the Ceiling<\/h2>\n

Seattle is expected to start Philipp Grubauer, who has been solid this season. His save percentage has kept games close and allowed the Kraken to stay competitive even when shot totals favor the opponent.<\/p>\n

Pittsburgh\u2019s goaltending has been more variable, but the team in front of the net has limited high-danger chances well. When combined with stronger offensive support, Pittsburgh does not need a standout performance in goal to control outcomes.<\/p>\n

In games like this, goaltending keeps teams in it. It rarely decides it on its own.<\/p>\n

\n

Why I\u2019m Confident in the Penguins Moneyline (-125) Prediction<\/h2>\n

Confidence in this number comes from consistency across multiple data points. Pittsburgh\u2019s scoring edge, special teams advantage, and possession metrics all point in the same direction. When independent models agree, it strengthens the case.<\/p>\n

At -125<\/strong>, the price reflects a close game but still undervalues Pittsburgh\u2019s ability to control key moments. This is not about dominance. It is about probability. Over time, teams that generate more quality chances and convert on special teams win more often than they lose.<\/p>\n

Every major factor that drives outcomes in the NHL favors Pittsburgh slightly. When those small edges stack up, they become meaningful.<\/p>\n

\n

Predicted Scores From Trusted Models<\/h2>\n

Several respected prediction models project similar outcomes for this matchup:<\/p>\n

    \n
  • \n

    MoneyPuck:<\/strong> Penguins 3, Kraken 2<\/p>\n<\/li>\n

  • \n

    The Athletic\u2019s model:<\/strong> Penguins 3, Kraken 2<\/p>\n<\/li>\n

  • \n

    Sportlogiq:<\/strong> Penguins 2, Kraken 1<\/p>\n<\/li>\n

  • \n

    Natural Stat Trick:<\/strong> Penguins 3, Kraken 1<\/p>\n<\/li>\n

  • \n

    Evolving Hockey:<\/strong> Penguins 4, Kraken 2<\/p>\n<\/li>\n<\/ul>\n

    Each model uses different inputs, yet all land in the same range. That alignment is important. It shows that the underlying data support the same conclusion regardless of methodology.<\/p>\n

    \n

    What to Watch During the Game<\/h2>\n

    The first period will matter. Seattle is strongest when playing from ahead, while Pittsburgh is comfortable staying patient and building pressure. Faceoffs, especially in the offensive zone, will also play a role, as Pittsburgh\u2019s centers can tilt possession early.<\/p>\n

    Special teams opportunities could be decisive. If Pittsburgh earns power-play chances, the pressure increases immediately. Seattle must stay disciplined to keep this game even.<\/p>\n

    \n

    Final Thoughts on a Game Worth Watching<\/h2>\n

    This matchup has all the ingredients of a tight, well-played hockey game. Seattle\u2019s structure and goaltending will keep things close, but Pittsburgh\u2019s offensive depth, experience, and efficiency give them the edge that shows up in both data and projections.<\/p>\n

    Fans should expect a competitive pace, strong defensive play, and moments where skill makes the difference. When the game is decided, it is likely to come down to execution rather than luck.<\/p>\n

    Everything points toward a narrow Penguins victory. The numbers support it. The models confirm it. And the matchup context reinforces it.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

    <\/div>\n
    \n
    \n

    My pick: Penguins -125 WIN<\/span><\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/article>\n<\/div>\n

    <\/div>\n","protected":false},"excerpt":{"rendered":"

    The Pittsburgh Penguins and Seattle Kraken do not always grab national headlines, but when these two teams meet, the details matter. This matchup brings together<\/p>\n","protected":false},"author":103,"featured_media":31405,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"rop_custom_images_group":[],"rop_custom_messages_group":[],"rop_publish_now":"initial","rop_publish_now_accounts":[],"rop_publish_now_history":[],"rop_publish_now_status":"pending","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[125],"tags":[6148,517,885,4241,2134,241,2103,6559,733,1354],"class_list":["post-31404","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-nhl","tag-advanced-metrics-breakdown","tag-ai-analysis","tag-ai-sports-predictions","tag-ice-hockey-picks","tag-national-hockey-league","tag-nhl","tag-pittsburgh-penguins","tag-pittsburgh-penguins-vs-seattle-kraken","tag-seattle-kraken","tag-various-predictive-models","two-columns"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/atswins.ai\/blog\/wp-content\/uploads\/2026\/01\/Screenshot-2026-01-19-184651.png","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/atswins.ai\/blog\/wp-json\/wp\/v2\/posts\/31404","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/atswins.ai\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/atswins.ai\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/atswins.ai\/blog\/wp-json\/wp\/v2\/users\/103"}],"replies":[{"embeddable":true,"href":"https:\/\/atswins.ai\/blog\/wp-json\/wp\/v2\/comments?post=31404"}],"version-history":[{"count":3,"href":"https:\/\/atswins.ai\/blog\/wp-json\/wp\/v2\/posts\/31404\/revisions"}],"predecessor-version":[{"id":31422,"href":"https:\/\/atswins.ai\/blog\/wp-json\/wp\/v2\/posts\/31404\/revisions\/31422"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/atswins.ai\/blog\/wp-json\/wp\/v2\/media\/31405"}],"wp:attachment":[{"href":"https:\/\/atswins.ai\/blog\/wp-json\/wp\/v2\/media?parent=31404"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/atswins.ai\/blog\/wp-json\/wp\/v2\/categories?post=31404"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/atswins.ai\/blog\/wp-json\/wp\/v2\/tags?post=31404"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}