Stars vs. Predators prediction favors Dallas to win Saturday's NHL matchup [10/3/2026]

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Written by Jason Bevilacqua

Dimers' simulation model projects a 54.2% win probability for the Stars at Bridgestone Arena.

The Dallas Stars take on the Nashville Predators in NHL action.
Dallas Stars vs. Nashville Predators NHL prediction for Saturday, October 3, 2026.

NHL action continues on Saturday at 8:00 PM ET as the Dallas Stars take on the Nashville Predators at Bridgestone Arena.

Dimers' advanced NHL model gives the Stars a slight edge with a 54.2% win probability over the Predators.

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

Stars vs. Predators prediction and odds

Using innovative machine learning and data, we have re-simulated the outcome of Saturday's NHL matchup between the Stars and Predators, forming part of our NHL predictions coverage.

Our famous predictive model gives the Stars a 54.2% chance of defeating the Predators. According to our model, the Predators (+1.5) have a 67.8% chance of covering the puck line, while the over/under total of six goals has a 50.8% 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: Stars -1.5 (+190) / Predators +1.5 (-210)
  • Moneyline: Stars -128, Predators +115
  • Total: Over/Under 6 (-110/-105)

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

Model picks and best bet

After matching our predictions 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: Predators +1.5 @ -210 via bet365
  • Moneyline: Predators @ +115 via bet365
  • Total: Under 6 @ -105 via BetMGM

According to our NHL best bets, the top play to make on this game is Predators +1.5 at the spread.

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

Stars vs. Predators player props

Who will score a goal in Stars vs. Predators?

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

Our projections give Johnston a 38.1% chance of scoring a goal at Bridgestone Arena, while the star is an 8.3% chance of netting the first goal the game.

Anytime goal scorer predictions

Dallas Stars

  • Wyatt Johnston: 38.1% probability
  • Jason Robertson: 37.9% probability
  • Mikko Rantanen: 30.5% probability
  • Tyler Seguin: 24.0% probability
  • Roope Hintz: 23.7% probability

Nashville Predators

  • Filip Forsberg: 37.4% probability
  • Steven Stamkos: 36.8% probability
  • Ryan O'Reilly: 25.8% probability
  • Matthew Wood: 22.8% probability
  • Jonathan Marchessault: 20.3% probability

First goal scorer predictions

Dallas Stars

  • Wyatt Johnston: 8.3% probability
  • Jason Robertson: 7.7% probability
  • Mikko Rantanen: 5.3% probability
  • Tyler Seguin: 4.2% probability
  • Jamie Benn: 4.1% probability

Nashville Predators

  • Steven Stamkos: 7.2% probability
  • Filip Forsberg: 7.1% probability
  • Ryan O'Reilly: 4.4% probability
  • Matthew Wood: 4.1% probability
  • Mavrik Bourque: 3.6% probability

Game info & puck drop details

Saturday's action between the Predators and Stars at Bridgestone Arena is scheduled to begin at 8:00 PM ET.

Conclusion

We predict the Stars, with a 54.2% win probability, will likely beat the Predators in Saturday'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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