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Rays vs. White Sox prediction: Why Tampa Bay is favored to win Thursday's MLB matchup [4/16/2026]

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Written by Jason Bevilacqua

Get Tampa Bay Rays vs Chicago White Sox predictions for MLB Thursday.

Tampa Bay Rays-Chicago White Sox Predictions and Game Preview.
Tampa Bay Rays vs. Chicago White Sox MLB prediction for Thursday, April 16, 2026.

The Chicago White Sox will square off with the Tampa Bay Rays, in what is expected to be a close MLB game, at Rate Field on Thursday, beginning at 2:10 PM ET.

Jordan Leasure (1-0, 4.00 ERA) will start for the White Sox, up against Steven Matz (3-0, 3.94 ERA) for the Rays.

Based on the latest simulations, Dimers' proven MLB model gives the Rays a slight edge with a 51% win probability over the White Sox.

This article offers a closer look at Thursday's Rays vs. White Sox matchup, including best bets and picks.

Rays vs. White Sox prediction: Who will win and cover?

Using innovative machine learning and data analysis, we have simulated the outcome of Thursday's MLB game between the Rays and White Sox, forming part of our MLB predictions coverage.

Our famous predictive model gives the Rays a 51% chance of beating the White Sox.

According to our model, the White Sox (+1.5) have a 60% chance of covering the run line, while the **8.5-run over/under **.

 

Rays vs. White Sox odds [4/16/2026]

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

Bet Type Rays White Sox
Run Line -1.5 (+140) +1.5 (-156)
Moneyline -124 +106
Total o8.5 (+100) u8.5 (-104)

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

Rays vs. White Sox 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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