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Blues vs. Mammoth prediction: Close contest projected after new data released for Thursday's NHL matchup [4/16/2026]

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Written by Jason Bevilacqua

Get St. Louis Blues vs Utah Mammoth predictions for NHL Thursday.

St. Louis Blues-Utah Mammoth Predictions and Game Preview.
St. Louis Blues vs. Utah Mammoth NHL prediction for Thursday, April 16, 2026.

The Utah Mammoth will take on the St. Louis Blues, in what is expected to be a close NHL game, at Delta Center on Thursday, commencing at 7:30 PM ET.

Based on the latest simulation results, Dimers' advanced NHL model gives an equal chance for both both teams to win the Blues-Mammoth matchup.

This article offers a closer look at Thursday's Blues vs. Mammoth matchup, including projected goal scorers, best bets and player prop picks.

Blues vs. Mammoth prediction: Who will win and cover?

Using trusted machine learning and data analysis, we have simulated the result of Thursday's NHL matchup between the Blues and Mammoth, forming part of our NHL predictions coverage.

Our leading predictive model currently can't split the two teams, giving both the Blues and Mammoth a 50% chance of winning the game.

According to our model, the Mammoth (+1.5) have a 71% chance of covering the puck line, while the over/under total of six goals has an equal 50-50 chance of hitting.

 

Blues vs. Mammoth odds

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

Bet Type Blues Mammoth
Puck Line -1.5 (+190) +1.5 (-220)
Moneyline -130 +112
Total o6 (-118) u6 (-102)

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

Blues vs. Mammoth 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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