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Mammoth vs. Golden Knights prediction: Vegas favored to win Thursday's NHL matchup [3/19/2026]

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Written by Jason Bevilacqua

Get Utah Mammoth vs Vegas Golden Knights predictions for NHL Thursday.

Utah Mammoth-Vegas Golden Knights Predictions and Game Preview.
Utah Mammoth vs. Vegas Golden Knights NHL prediction for Thursday, March 19, 2026.

NHL action continues on Thursday at 10:00 PM ET as the Utah Mammoth square off with the Vegas Golden Knights at T-Mobile Arena.

Based on the latest simulations, Dimers' proven NHL model gives the Golden Knights a slight edge with a 54% win probability over the Mammoth.

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

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

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

Our famous predictive model gives the Golden Knights a 54% chance of defeating the Mammoth.

According to our model, the Mammoth (+1.5) have a 68% chance of covering the puck line, while the 6-goal over/under has a 52% chance of staying under.

 

Mammoth vs. Golden Knights odds

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

Bet Type Mammoth Golden Knights
Puck Line +1.5 (-225) -1.5 (+190)
Moneyline +115 -135
Total o6 (-105) u6 (-115)

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

Mammoth 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:

Bet Type Pick Bet Now
Puck Line Mammoth +1.5 -225
Moneyline Mammoth +115
Total Under 6 -115

According to our NHL best bets, the top play to make on this game is Mammoth to win.

These picks are based on our probabilities matched against the implied probabilities from the sportsbook odds.

 

Mammoth vs. Golden Knights player props

Who will score a goal in Mammoth vs. Golden Knights?

According to our model, Pavel Dorofeyev is most likely to score an anytime goal in Mammoth vs. Golden Knights.

Our projections give Dorofeyev a 37.2% chance of scoring a goal at T-Mobile Arena, while the star is a 7.4% chance of netting the first goal the game.

Anytime goal scorer predictions

Utah Mammoth

Player Anytime Goal Probability
Dylan Guenther 31.1%
Clayton Keller 30.4%
Logan Cooley 25.0%
Nick Schmaltz 21.6%
JJ Peterka 20.7%

Vegas Golden Knights

Player Anytime Goal Probability
Pavel Dorofeyev 37.2%
Jack Eichel 36.4%
Tomas Hertl 29.5%
Ivan Barbashev 26.4%
Mitch Marner 25.7%

First goal scorer predictions

Utah Mammoth

Player First Goal Probability
Clayton Keller 6.6%
Dylan Guenther 6.3%
Logan Cooley 4.5%
JJ Peterka 3.9%
Nick Schmaltz 3.7%

Vegas Golden Knights

Player First Goal Probability
Jack Eichel 7.6%
Pavel Dorofeyev 7.4%
Tomas Hertl 5.6%
Ivan Barbashev 5.1%
Mitch Marner 4.2%

Mammoth vs. Golden Knights game-day updates and essential details

Thursday's action between the Golden Knights and Mammoth at T-Mobile Arena is scheduled to begin at 10:00 PM ET.

Conclusion

We predict the Golden Knights, with a 54% win probability, will likely beat the Mammoth on Thursday.

AI and automation have enhanced this article to quickly deliver accurate Mammoth vs. Golden Knights insights, with human oversight ensuring high editorial quality. Our predictions are drawn from the latest data to help you make informed decisions. For additional resources and advice on responsible gambling, please call 1-800-GAMBLER.

Note: Clicking links to our partners may earn us a referral fee. Learn about how we review products and services.

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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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