Avalanche vs. Stars prediction favors Dallas to win Tuesday's NHL matchup [10/13/2026]

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Written by Jason Bevilacqua

Dimers' simulation model projects a 50.2% win probability for the Stars at American Airlines Center.

The Colorado Avalanche take on the Dallas Stars in NHL action.
Colorado Avalanche vs. Dallas Stars NHL prediction for Tuesday, October 13, 2026.

The Dallas Stars will take on the Colorado Avalanche, in what is expected to be a tight NHL game, at American Airlines Center on Tuesday, starting at 8:30 PM ET.

Dimers' advanced NHL model gives the Stars a slight edge with a 50.2% win probability over the Avalanche.

This article offers a complete Avalanche vs. Stars prediction, including projected goal scorers, best bets and player prop picks.

Avs vs. Stars prediction and odds

Using powerful machine learning and data analysis, we have re-simulated the outcome of Tuesday's NHL matchup between the Avalanche and Stars, forming part of our NHL predictions coverage.

Our leading predictive model gives the Stars a 50.2% chance of defeating the Avalanche. According to our model, the Avalanche (+1.5) have a 70.8% chance of covering the puck line, while the 6-goal over/under has a 50.6% chance of staying under.

 

Latest betting odds

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

  • Puck Line: Avalanche +1.5 (-250) / Stars -1.5 (+220)
  • Moneyline: Avalanche +100, Stars -115
  • Total: Over/Under 6 (+100/-115)

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

Model picks and best bet

After matching our probabilities against the best current odds, we can reveal our picks for each of the major markets in this matchup. Plus, find our best bet for the game below:

  • Puck line: Avalanche +1.5 @ -250 via BetMGM
  • Moneyline: Avalanche @ +100 via BetRivers
  • Total: Over 6 @ +100 via bet365

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

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

Avalanche vs. Stars player props

Who will score a goal in Avalanche vs. Stars?

According to our model, Nathan MacKinnon is most likely to score an anytime goal in Avalanche vs. Stars.

Our projections give MacKinnon a 42.1% chance of scoring a goal at American Airlines Center, while the star is a 9.3% chance of netting the first goal the game.

Anytime goal scorer predictions

Colorado Avalanche

  • Nathan MacKinnon: 42.1% probability
  • Martin Necas: 33.5% probability
  • Brock Nelson: 28.5% probability
  • Artturi Lehkonen: 28.3% probability
  • Gabriel Landeskog: 19.1% probability

Dallas Stars

  • Wyatt Johnston: 37.3% probability
  • Jason Robertson: 36.7% probability
  • Mikko Rantanen: 30.1% probability
  • Roope Hintz: 23.3% probability
  • Tyler Seguin: 20.3% probability

First goal scorer predictions

Colorado Avalanche

  • Nathan MacKinnon: 9.3% probability
  • Martin Necas: 7.0% probability
  • Brock Nelson: 5.6% probability
  • Artturi Lehkonen: 5.2% probability
  • Jaden Schwartz: 3.5% probability

Dallas Stars

  • Wyatt Johnston: 7.4% probability
  • Jason Robertson: 7.3% probability
  • Mikko Rantanen: 5.8% probability
  • Roope Hintz: 4.6% probability
  • Tyler Seguin: 3.4% probability

Game info & puck drop details

Tuesday's action between the Stars and Avalanche at American Airlines Center is scheduled to commence at 8:30 PM ET.

Conclusion

We predict the Stars, with a 50.2% win probability, will likely beat the Avalanche in Tuesday's NHL matchup.

Additional tools and information for betting safely can be found in our Responsible Gambling hub.

This article's predictions and probabilities are generated by Dimers' proprietary NHL prediction model. Our editorial team reviews the resulting content for accuracy and presentation before publication.

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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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