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Tigers vs. Twins prediction: Why Detroit is favored to win Wednesday's MLB matchup [4/8/2026]

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Written by Jason Bevilacqua

Get Detroit Tigers vs Minnesota Twins predictions for MLB Wednesday.

Detroit Tigers-Minnesota Twins Predictions and Game Preview.
Detroit Tigers vs. Minnesota Twins MLB prediction for Wednesday, April 8, 2026.

The Minnesota Twins will take on the Detroit Tigers in MLB action at Target Field on Wednesday, beginning at 7:40 PM ET.

Bailey Ober (0-0, 6.75 ERA) will be the starting pitcher for the Twins, while the Tigers have opted for Framber Valdez (1-0, 0.75 ERA).

Based on updated simulations, Dimers' proven MLB model predicts the Tigers as the most likely winner of the Tigers vs. Twins game.

This article offers a closer look at Wednesday's matchup, including best bets and picks.

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

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

Our famous predictive model currently gives the Tigers a 55% chance of defeating the Twins.

According to our model, the Twins (+1.5) have a 58% chance of covering the run line, while the over/under total of eight runs has a 53% chance of going over.

 

Tigers vs. Twins odds [4/8/2026]

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

Bet Type Tigers Twins
Run Line -1.5 (+113) +1.5 (-134)
Moneyline -150 +130
Total o8 (-110) u8 (-106)

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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