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Angels vs. Yankees prediction: Yankees favored to win Wednesday's MLB matchup [4/15/2026]

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Written by Jason Bevilacqua

Get Los Angeles Angels vs New York Yankees predictions for MLB Wednesday.

Los Angeles Angels-New York Yankees Predictions and Game Preview.
Los Angeles Angels vs. New York Yankees MLB prediction for Wednesday, April 15, 2026.

The New York Yankees and Los Angeles Angels will meet in MLB action at Yankee Stadium on Wednesday, starting at 7:05 PM ET.

The Yankees will have Luis Gil (0-1, 6.75 ERA) as their starting pitcher, up against Jack Kochanowicz (2-0, 3.24 ERA) for the Angels.

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

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

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

Using powerful machine learning and statistical analysis, we have simulated the result of Wednesday's MLB matchup between the Angels and Yankees, forming part of our MLB predictions coverage.

Our famous predictive model currently gives the Yankees a 62% chance of beating the Angels.

According to our model, the Angels (+1.5) have a 53% chance of covering the run line, while the over/under total of 10.5 runs has a 54% chance of going over.

 

Angels vs. Yankees odds [4/15/2026]

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

Bet Type Angels Yankees
Run Line +1.5 (-126) -1.5 (+105)
Moneyline +154 -184
Total o10.5 (-102) u10.5 (-105)

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

Angels vs. Yankees 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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