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Golden Knights vs. Stars prediction: Dallas favored to win Tuesday's NHL matchup [3/10/2026]

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Written by Jason Bevilacqua

Get Vegas Golden Knights vs Dallas Stars predictions for NHL Tuesday.

Vegas Golden Knights-Dallas Stars Predictions and Game Preview.
Vegas Golden Knights vs. Dallas Stars NHL prediction for Tuesday, March 10, 2026.

The Dallas Stars and Vegas Golden Knights will meet in the NHL at American Airlines Center on Tuesday, with puck drop at 8:00 PM ET.

Based on the latest simulations, Dimers' proven NHL model projects the Stars as the most likely winner of the Golden Knights vs. Stars game.

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

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

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

Our famous predictive model gives the Stars a 58% chance of beating the Golden Knights.

According to our model, the Golden Knights (+1.5) have a 63% chance of covering the puck line, while the 6-goal over/under has a 51% chance of going over.

 

Golden Knights vs. Stars odds

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

Bet Type Golden Knights Stars
Puck Line +1.5 (-190) -1.5 (+164)
Moneyline +134 -148
Total o6 (-110) u6 (-110)

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

Golden Knights vs. Stars picks and best bet

After matching our predictions 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 Stars -1.5 +164
Moneyline Golden Knights +134
Total Over 6 -110

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

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

 

Golden Knights vs. Stars player props

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

According to our model, Wyatt Johnston is most likely to score an anytime goal in Golden Knights vs. Stars.

Our projections give Johnston a 40.3% chance of scoring a goal at American Airlines Center, while the star is an 8.4% chance of registering the first goal the game.

Anytime goal scorer predictions

Vegas Golden Knights

Player Anytime Goal Probability
Pavel Dorofeyev 35.4%
Jack Eichel 35.3%
Tomas Hertl 27.0%
Mitch Marner 25.4%
Ivan Barbashev 25.0%

Dallas Stars

Player Anytime Goal Probability
Wyatt Johnston 40.3%
Jason Robertson 40.0%
Matt Duchene 31.7%
Mavrik Bourque 27.7%
Jamie Benn 21.5%

First goal scorer predictions

Vegas Golden Knights

Player First Goal Probability
Pavel Dorofeyev 7.1%
Jack Eichel 6.6%
Tomas Hertl 4.9%
Mitch Marner 4.7%
Ivan Barbashev 4.4%

Dallas Stars

Player First Goal Probability
Wyatt Johnston 8.4%
Jason Robertson 8.4%
Matt Duchene 5.4%
Mavrik Bourque 4.9%
Jamie Benn 4.3%

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

Tuesday's matchup between the Stars and Golden Knights at American Airlines Center is scheduled to begin at 8:00 PM ET.

Conclusion

We predict the Stars, with a 58% win probability, will likely beat the Golden Knights on Tuesday.

AI and automation have enhanced this article to quickly deliver accurate Golden Knights vs. Stars insights, with human oversight ensuring high editorial quality. Our predictions are sourced 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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