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Tigers vs. Twins prediction: Why Detroit is favored to win Thursday's MLB matchup [4/9/2026]

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Written by Jason Bevilacqua

Get Detroit Tigers vs Minnesota Twins predictions for MLB Thursday.

Detroit Tigers-Minnesota Twins Predictions and Game Preview.
Detroit Tigers vs. Minnesota Twins MLB prediction for Thursday, April 9, 2026.

The Minnesota Twins and Detroit Tigers will lock horns in MLB action at Target Field on Thursday, starting at 1:40 PM ET.

The Twins will send Mick Abel (0-2, 11.04 ERA) to the mound, pitting him against Jack Flaherty (0-1, 7.56 ERA) for the Tigers.

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

This article offers an expanded analysis of Thursday'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 analysis, we have simulated the outcome of Thursday's MLB matchup between the Tigers and Twins, forming part of our MLB predictions coverage.

Our independent predictive model currently gives the Tigers a 54% chance of beating the Twins.

According to our model, the Twins (+1.5) have a 59% chance of covering the run line, while the 8.5-run over/under has an equal 50-50 chance of hitting.

 

Tigers vs. Twins odds [4/9/2026]

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

Bet Type Tigers Twins
Run Line -1.5 (+123) +1.5 (-144)
Moneyline -130 +120
Total o8.5 (-102) u8.5 (-118)

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

Tigers vs. Twins picks and best bet

After matching our probabilities 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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