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Yankees vs. Astros prediction: Yankees favored to win Friday's MLB matchup [4/24/2026]

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Written by Jason Bevilacqua

Get New York Yankees vs Houston Astros predictions for MLB Friday.

New York Yankees-Houston Astros Predictions and Game Preview.
New York Yankees vs. Houston Astros MLB prediction for Friday, April 24, 2026.

The Houston Astros will face the New York Yankees in MLB action at Daikin Park on Friday, commencing at 8:10 PM ET.

Lance McCullers (1-1, 6.20 ERA) will start on the mound for the Astros, pitting him against Will Warren (2-0, 2.49 ERA) for the Yankees.

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

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

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

Using innovative machine learning and statistical analysis, we have simulated the outcome of Friday's MLB matchup between the Yankees and Astros, forming part of our MLB predictions coverage.

Our leading predictive model currently gives the Yankees a 56% chance of beating the Astros.

According to our model, the Astros (+1.5) have a 56% chance of covering the run line, while the over/under total of nine runs has a 54% chance of going over.

 

Yankees vs. Astros odds [4/24/2026]

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

Bet Type Yankees Astros
Run Line -1.5 (+108) +1.5 (-120)
Moneyline -154 +130
Total o9 (-105) u9 (+100)

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

Yankees vs. Astros picks and best bet

After matching our predictions against the best available 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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