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Golden Knights vs. Kraken prediction: Vegas favored to win Thursday's NHL matchup [4/9/2026]

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Written by Jason Bevilacqua

Get Vegas Golden Knights vs Seattle Kraken predictions for NHL Thursday.

Vegas Golden Knights-Seattle Kraken Predictions and Game Preview.
Vegas Golden Knights vs. Seattle Kraken NHL prediction for Thursday, April 9, 2026.

The Seattle Kraken and Vegas Golden Knights will meet in the NHL at Climate Pledge Arena on Thursday, starting at 10:00 PM ET.

Based on the latest simulation results, Dimers' advanced NHL model projects the Golden Knights as the most likely winner of the Golden Knights vs. Kraken game.

This article offers a closer look at Thursday's matchup, including projected goal scorers, best bets and player prop picks.

Golden Knights vs. Kraken prediction: Who will win and cover?

Using powerful machine learning and data, we have simulated the result of Thursday's NHL matchup between the Golden Knights and Kraken, forming part of our NHL predictions coverage.

Our independent predictive model currently gives the Golden Knights a 59% chance of defeating the Kraken.

According to our model, the Kraken (+1.5) have a 63% chance of covering the puck line, while the over/under total of six goals has a 51% chance of staying under.

 

Golden Knights vs. Kraken odds

We have researched the best NHL odds in America for this game, which are listed here:

Bet Type Golden Knights Kraken
Puck Line -1.5 (+140) +1.5 (-155)
Moneyline -185 +160
Total o6 (-120) u6 (+100)

All odds are correct at the time of publication and are subject to change.

Golden Knights vs. Kraken picks and best bet

After matching our predictions against the best current odds, we can reveal our picks for each of the major markets. Plus, find our best bet for the game below:

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Written by
Jason Bevilacqua
Head of Content and Communities

Jason Bevilacqua, an expert in MLB, NHL, NBA, MLS, and NFL, delivers game previews, best bets, and props. Since 2020, as Head of Social and Community at Dimers, he has contributed insightful articles utilizing data-driven models and simulations.

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