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Kraken vs. Stars prediction: Dallas favored to win Wednesday's NHL matchup [2/25/2026]
Updated: | First published:
Written by Jason Bevilacqua, Head of Content and Communities
Get Seattle Kraken vs Dallas Stars predictions for NHL Wednesday.
The Dallas Stars will square off with the Seattle Kraken in NHL action at American Airlines Center on Wednesday, starting at 8:00 PM ET.
Based on updated simulations, Dimers' proven NHL model predicts the Stars as the most likely winner of the Kraken vs. Stars game.
This article offers further insights into Wednesday's matchup, including projected goal scorers, best bets and player prop picks.
Kraken vs. Stars prediction: Who will win and cover?
Using innovative machine learning and statistical analysis, we have simulated the outcome of Wednesday's NHL game between the Kraken and Stars 10,000 times as part of our NHL predictions coverage.
Our independent predictive model currently gives the Stars a 60% chance of beating the Kraken.
According to our model, the Kraken (+1.5) have a 63% chance of covering the puck line, while the over/under total of 5.5 goals has a 52% chance of going over.
Kraken vs. Stars odds
We have sourced the best NHL odds in America for this game, which are listed here:
| Bet Type | Kraken | Stars |
|---|---|---|
| Puck Line | +1.5 (-180) | -1.5 (+154) |
| Moneyline | +142 | -170 |
| Total | o5.5 (+106) | u5.5 (-120) |
All odds are correct at the time of publication and are subject to change.
Kraken 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 | Kraken +1.5 | -180 |
| Moneyline | Kraken | +142 |
| Total | Over 5.5 | +106 |
According to our NHL best bets, the top play to make on this game is Over 5.5 total goals.
These picks are based on our probabilities matched against the implied probabilities from the sportsbook odds.
Kraken vs. Stars player props
Who will score a goal in Kraken vs. Stars?
According to our model, Wyatt Johnston is most likely to score an anytime goal in Kraken vs. Stars.
Our projections give Johnston a 44.9% chance of scoring a goal at American Airlines Center, while the star is a 10.2% chance of netting the first goal the game.
Anytime goal scorer predictions
Seattle Kraken
| Player | Anytime Goal Probability |
|---|---|
| Jared McCann | 26.2% |
| Matty Beniers | 23.4% |
| Shane Wright | 23.0% |
| Eeli Tolvanen | 22.7% |
| Jordan Eberle | 20.8% |
Dallas Stars
| Player | Anytime Goal Probability |
|---|---|
| Wyatt Johnston | 44.9% |
| Jason Robertson | 44.8% |
| Matt Duchene | 33.0% |
| Mavrik Bourque | 30.3% |
| Jamie Benn | 19.9% |
First goal scorer predictions
Seattle Kraken
| Player | First Goal Probability |
|---|---|
| Jared McCann | 4.9% |
| Shane Wright | 4.4% |
| Matty Beniers | 4.1% |
| Jordan Eberle | 3.8% |
| Eeli Tolvanen | 3.7% |
Dallas Stars
| Player | First Goal Probability |
|---|---|
| Jason Robertson | 10.4% |
| Wyatt Johnston | 10.2% |
| Matt Duchene | 6.1% |
| Mavrik Bourque | 5.7% |
| Jamie Benn | 3.8% |
Kraken vs. Stars game-day updates and essential details
Wednesday's action between the Stars and Kraken at American Airlines Center is scheduled to start at 8:00 PM ET.
- Who: Seattle Kraken vs. Dallas Stars
- Date: Wednesday, February 25, 2026
- Time: 8:00 PM ET/5:00PM PT
- Venue: American Airlines Center
Conclusion
We predict the Stars, with a 60% win probability, will likely beat the Kraken on Wednesday.
AI and automation have enhanced this article to quickly deliver accurate Kraken vs. Stars 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.
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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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