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Blues vs. Sharks prediction: San Jose favored to win Friday's NHL matchup [3/6/2026]
Updated: | First published:
Written by Jason Bevilacqua, Head of Content and Communities
Get St. Louis Blues vs San Jose Sharks predictions for NHL Friday.
The San Jose Sharks will square off with the St. Louis Blues, in what is expected to be a tight NHL game, at SAP Center at San Jose on Friday, commencing at 10:00 PM ET.
Based on updated simulation results, Dimers' proven NHL model gives the Sharks a slight edge with a 53% win probability over the Blues.
This article offers an expanded analysis of Friday's Blues vs. Sharks matchup, including projected goal scorers, best bets and player prop picks.
Blues vs. Sharks prediction: Who will win and cover?
Using powerful machine learning and statistical analysis, we have simulated the result of Friday's NHL matchup between the Blues and Sharks 10,000 times as part of our NHL predictions coverage.
Our famous predictive model gives the Sharks a 53% chance of beating the Blues.
According to our model, the Blues (+1.5) have a 68% chance of covering the puck line, while the 6-goal over/under has a 51% chance of going over.
Blues vs. Sharks odds
We have researched the best NHL odds in America for this game, which are listed here:
| Bet Type | Blues | Sharks |
|---|---|---|
| Puck Line | +1.5 (-205) | -1.5 (+170) |
| Moneyline | +124 | -145 |
| Total | o6 (-130) | u6 (+100) |
All odds are correct at the time of publication and are subject to change.
Blues vs. Sharks 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 | Blues +1.5 | -205 |
| Moneyline | Blues | +124 |
| Total | Under 6 | +100 |
According to our NHL best bets, the top play to make on this game is Blues to win.
These picks are based on our probabilities matched against the implied probabilities from the sportsbook odds.
Blues vs. Sharks player props
Who will score a goal in Blues vs. Sharks?
According to our model, Macklin Celebrini is most likely to score an anytime goal in Blues vs. Sharks.
Our projections give Celebrini a 36.5% chance of scoring a goal at SAP Center at San Jose, while the star is a 7.3% chance of registering the first goal the game.
Anytime goal scorer predictions
St. Louis Blues
| Player | Anytime Goal Probability |
|---|---|
| Dylan Holloway | 35.7% |
| Jordan Kyrou | 30.8% |
| Robert Thomas | 26.1% |
| Jake Neighbours | 24.5% |
| Pavel Buchnevich | 24.5% |
San Jose Sharks
| Player | Anytime Goal Probability |
|---|---|
| Macklin Celebrini | 36.5% |
| Will Smith | 31.0% |
| Kiefer Sherwood | 25.6% |
| Tyler Toffoli | 25.5% |
| Michael Misa | 20.2% |
First goal scorer predictions
St. Louis Blues
| Player | First Goal Probability |
|---|---|
| Dylan Holloway | 7.0% |
| Jordan Kyrou | 5.2% |
| Robert Thomas | 4.8% |
| Jake Neighbours | 4.5% |
| Pavel Buchnevich | 4.2% |
San Jose Sharks
| Player | First Goal Probability |
|---|---|
| Macklin Celebrini | 7.3% |
| Will Smith | 6.0% |
| Tyler Toffoli | 4.4% |
| Kiefer Sherwood | 4.4% |
| Michael Misa | 3.9% |
Blues vs. Sharks game-day updates and essential details
Friday's matchup between the Sharks and Blues at SAP Center at San Jose is scheduled to commence at 10:00 PM ET.
- Who: St. Louis Blues vs. San Jose Sharks
- Date: Friday, March 6, 2026
- Time: 10:00 PM ET/7:00PM PT
- Venue: SAP Center at San Jose
Conclusion
We predict the Sharks, with a 53% win probability, will likely beat the Blues on Friday.
AI and automation have enhanced this article to quickly deliver accurate Blues vs. Sharks insights, with human oversight ensuring high editorial quality. Our predictions are based on 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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