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Rays vs. Twins prediction: Why Minnesota is favored to win Sunday's MLB matchup [4/5/2026]

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Written by Jason Bevilacqua

Get Tampa Bay Rays vs Minnesota Twins predictions for MLB Sunday.

Tampa Bay Rays-Minnesota Twins Predictions and Game Preview.
Tampa Bay Rays vs. Minnesota Twins MLB prediction for Sunday, April 5, 2026.

The Minnesota Twins will face the Tampa Bay Rays, in what is expected to be a close MLB game, at Target Field on Sunday, commencing at 2:10 PM ET.

The Twins will send Simeon Woods Richardson (0-1, 3.60 ERA) to the mound, up against Nick Martinez (0-0, 3.00 ERA) for the Rays.

Based on updated simulations, Dimers' proven MLB model gives the Twins a slight edge with a 53% win probability over the Rays.

This article offers an expanded analysis of Sunday's Rays vs. Twins matchup, including best bets and picks.

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

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

Our famous predictive model currently gives the Twins a 53% chance of defeating the Rays.

According to our model, the Rays (+1.5) have a 65% chance of covering the run line, while the 8-run over/under has a 52% chance of going over.

 

Rays vs. Twins odds [4/5/2026]

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

Bet Type Rays Twins
Run Line +1.5 (-235) -1.5 (+180)
Moneyline -104 -110
Total o8 (-105) u8 (-108)

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

Rays 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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