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Tigers vs. Twins prediction: Why Minnesota is favored to win Monday's MLB matchup [4/6/2026]

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Written by Jason Bevilacqua

Get Detroit Tigers vs Minnesota Twins predictions for MLB Monday.

Detroit Tigers-Minnesota Twins Predictions and Game Preview.
Detroit Tigers vs. Minnesota Twins MLB prediction for Monday, April 6, 2026.

The Minnesota Twins will square off with the Detroit Tigers, in what is expected to be a close MLB game, at Target Field on Monday, commencing at 7:40 PM ET.

Joe Ryan (0-1, 4.82 ERA) will get the ball for the Twins, while the Tigers are going with Casey Mize (0-0, 1.50 ERA).

Based on the latest simulations, Dimers' advanced MLB model gives the Twins a slight edge with a 54% win probability over the Tigers.

This article offers further insights into Monday's Tigers vs. Twins matchup, including best bets and picks.

Tigers vs. Twins prediction: Who will win and cover?

Using trusted machine learning and data, we have simulated the result of Monday's MLB game between the Tigers and Twins, forming part of our MLB predictions coverage.

Our leading predictive model currently gives the Twins a 54% chance of defeating the Tigers.

According to our model, the Tigers (+1.5) have a 63% chance of covering the run line, while the over/under total of seven runs has a 55% chance of going over.

 

Tigers vs. Twins odds [4/6/2026]

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

Bet Type Tigers Twins
Run Line +1.5 (-205) -1.5 (+180)
Moneyline +108 -125
Total o7 (-115) u7 (-105)

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

Tigers vs. Twins 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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