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Flyers vs. Golden Knights prediction: Vegas favored to win Monday's NHL matchup [1/19/2026]

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Written by Jason Bevilacqua

Get Philadelphia Flyers vs Vegas Golden Knights predictions for NHL Monday.

Philadelphia Flyers-Vegas Golden Knights Predictions and Game Preview.
Philadelphia Flyers vs. Vegas Golden Knights NHL prediction for Monday, January 19, 2026.

The Vegas Golden Knights will face the Philadelphia Flyers in NHL action at T-Mobile Arena on Monday, starting at 8:00 PM ET.

Based on updated simulations, Dimers' proven NHL model predicts the Golden Knights as the most likely winner of the Flyers vs. Golden Knights game.

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

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

Using innovative machine learning and data, we have simulated the outcome of Monday's NHL matchup between the Flyers and Golden Knights 10,000 times as part of our NHL predictions coverage.

Our famous predictive model currently gives the Golden Knights a 64% chance of defeating the Flyers.

According to our model, the Flyers (+1.5) have a 58% chance of covering the puck line, while the over/under total of six goals has a 54% chance of going over.

 

Flyers vs. Golden Knights odds

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

Bet Type Flyers Golden Knights
Puck Line +1.5 (-125) -1.5 (+112)
Moneyline +190 -225
Total o6 (-130) u6 (+100)

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

Flyers vs. Golden Knights picks and best bet

After matching our probabilities against the best available 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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