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Avalanche vs. Stars prediction: Colorado favored to win Friday's NHL matchup [3/6/2026]

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Written by Jason Bevilacqua

Get Colorado Avalanche vs Dallas Stars predictions for NHL Friday.

Colorado Avalanche-Dallas Stars Predictions and Game Preview.
Colorado Avalanche vs. Dallas Stars NHL prediction for Friday, March 6, 2026.

The Dallas Stars will square off with the Colorado Avalanche, in what is expected to be a close NHL game, at American Airlines Center on Friday, beginning at 8:00 PM ET.

Based on the latest simulation results, Dimers' advanced NHL model gives the Avalanche a slight edge with a 52% win probability over the Stars.

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

Avs vs. Stars prediction: Who will win and cover?

Using trusted machine learning and statistical analysis, we have simulated the result of Friday's NHL matchup between the Avalanche and Stars 10,000 times as part of our NHL predictions coverage.

Our famous predictive model gives the Avalanche a 52% chance of beating the Stars.

According to our model, the Stars (+1.5) have a 67% chance of covering the puck line, while the over/under total of six goals has an equal 50-50 chance of hitting.

 

Avalanche vs. Stars odds

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

Bet Type Avalanche Stars
Puck Line -1.5 (+205) +1.5 (-230)
Moneyline -120 +102
Total o6 (-110) u6 (-110)

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

Avalanche vs. Stars 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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