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Maple Leafs vs. Golden Knights prediction: Vegas favored to win Thursday's NHL matchup [1/15/2026]

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Written by Jason Bevilacqua

Get Toronto Maple Leafs vs Vegas Golden Knights predictions for NHL Thursday.

Toronto Maple Leafs-Vegas Golden Knights Predictions and Game Preview.
Toronto Maple Leafs vs. Vegas Golden Knights NHL prediction for Thursday, January 15, 2026.

NHL action continues on Thursday at 9:30 PM ET as the Toronto Maple Leafs square off with the Vegas Golden Knights at T-Mobile Arena.

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

This article offers an expanded analysis of Thursday's matchup, including projected goal scorers, best bets and player prop picks.

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

Using powerful machine learning and data analysis, we have simulated the result of Thursday's NHL matchup between the Maple Leafs and Golden Knights 10,000 times as part of our NHL predictions coverage.

Our famous predictive model gives the Golden Knights a 55% chance of defeating the Maple Leafs.

According to our model, the Maple Leafs (+1.5) have a 66% chance of covering the puck line, while the 6-goal over/under has a 54% chance of going over.

 

Maple Leafs vs. Golden Knights odds

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

Bet Type Maple Leafs Golden Knights
Puck Line +1.5 (-205) -1.5 (+180)
Moneyline +118 -135
Total o6 (-130) u6 (-102)

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

Maple Leafs vs. Golden Knights picks and best bet

After matching our probabilities 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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