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Angels vs. Yankees prediction: Yankees favored to win Thursday's MLB matchup [4/16/2026]

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Written by Jason Bevilacqua

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

Los Angeles Angels-New York Yankees Predictions and Game Preview.
Los Angeles Angels vs. New York Yankees MLB prediction for Thursday, April 16, 2026.

The New York Yankees will take on the Los Angeles Angels in MLB action at Yankee Stadium on Thursday, commencing at 1:35 PM ET.

The Yankees will start Max Fried (2-0, 1.93 ERA), pitting him against Brent Suter (0-1, 2.08 ERA) for the Angels.

Based on updated simulation results, 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 Thursday's matchup, including best bets and picks.

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

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

Our famous predictive model currently gives the Yankees a 72% chance of beating the Angels.

According to our model, the Yankees (-1.5) have a 56% chance of covering the run line, while the over/under total of 10 runs has a 53% chance of going over.

 

Angels vs. Yankees odds [4/16/2026]

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

Bet Type Angels Yankees
Run Line +1.5 (+128) -1.5 (-149)
Moneyline +245 -295
Total o10 (-105) u10 (-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 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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