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Cardinals vs. Astros prediction: Houston favored to win Sunday's MLB matchup [4/19/2026]

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Written by Jason Bevilacqua

Get St. Louis Cardinals vs Houston Astros predictions for MLB Sunday.

St. Louis Cardinals-Houston Astros Predictions and Game Preview.
St. Louis Cardinals vs. Houston Astros MLB prediction for Sunday, April 19, 2026.

The Houston Astros will square off with the St. Louis Cardinals in MLB action at Daikin Park on Sunday, commencing at 2:10 PM ET.

The Astros will have Mike Burrows (1-3, 6.54 ERA) as their starting pitcher, up against Matthew Liberatore (0-1, 4.29 ERA) for the Cardinals.

Based on the latest simulations, Dimers' proven MLB model predicts the Astros as the most likely winner of the Cardinals vs. Astros game.

This article offers further insights into Sunday's matchup, including best bets and picks.

Cardinals vs. Astros prediction: Who will win and cover?

Using powerful machine learning and data, we have simulated the result of Sunday's MLB game between the Cardinals and Astros, forming part of our MLB predictions coverage.

Our famous predictive model gives the Astros a 59% chance of beating the Cardinals.

According to our model, the Cardinals (+1.5) have a 58% chance of covering the run line, while the 8.5-run over/under has a 52% chance of going over.

 

Cardinals vs. Astros odds [4/19/2026]

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

Bet Type Cardinals Astros
Run Line +1.5 (-163) -1.5 (+146)
Moneyline +125 -142
Total o8.5 (-105) u8.5 (+100)

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

Cardinals vs. Astros 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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