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Blue Jays vs. Angels prediction: Toronto favored to win Monday's MLB matchup [4/20/2026]

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Written by Jason Bevilacqua

Get Toronto Blue Jays vs Los Angeles Angels predictions for MLB Monday.

Toronto Blue Jays-Los Angeles Angels Predictions and Game Preview.
Toronto Blue Jays vs. Los Angeles Angels MLB prediction for Monday, April 20, 2026.

MLB action continues on Monday at 9:38 PM ET as the Toronto Blue Jays take on the Los Angeles Angels at Angel Stadium.

The Angels will start Reid Detmers (1-1, 3.57 ERA), up against Dylan Cease (0-0, 1.74 ERA) for the Blue Jays.

Based on the latest simulation results, Dimers' advanced MLB model gives the Blue Jays a slight edge with a 54% win probability over the Angels.

This article offers further insights into Monday's Blue Jays vs. Angels matchup, including best bets and picks.

Blue Jays vs. Angels prediction: Who will win and cover?

Using trusted machine learning and statistical analysis, we have simulated the outcome of Monday's MLB matchup between the Blue Jays and Angels, forming part of our MLB predictions coverage.

Our famous predictive model currently gives the Blue Jays a 54% chance of defeating the Angels.

According to our model, the Angels (+1.5) have a 59% chance of covering the run line, while the over/under total of 7.5 runs has a 53% chance of going over.

 

Blue Jays vs. Angels odds [4/20/2026]

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

Bet Type Blue Jays Angels
Run Line -1.5 (+140) +1.5 (-165)
Moneyline -120 +102
Total o7.5 (-104) u7.5 (-102)

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

Blue Jays vs. Angels 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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