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Richmond Tigers vs. Port Adelaide Power prediction: Why Power are favored to win Saturday's AFL Round 4 matchup [4/4/2026]

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Written by Jason Bevilacqua

Get Richmond Tigers vs Port Adelaide Power predictions for AFL Saturday.

Richmond Tigers-Port Adelaide Power Predictions and Game Preview.
Richmond Tigers vs. Port Adelaide Power AFL prediction for Saturday, April 4, 2026.

The Richmond Tigers will square off with the favored Port Adelaide Power in Australian Football League (AFL) action at Melbourne Cricket Ground on Saturday, starting at 1:15 AM ET.

Based on the latest simulations, Dimers' proven AFL model predicts the Power as the most likely winner of the Power vs. Tigers game.

This article offers an expanded analysis of Saturday's matchup, including best bets and picks.

Tigers vs. Power prediction: Who will win Round 4 game?

Using trusted machine learning and data, we have simulated the result of Saturday's AFL matchup between the Power and Tigers, forming part of our AFL predictions coverage.

Our independent predictive model currently gives the Power a 65% chance of defeating the Tigers.

According to our model, the Tigers (+13.5) have a 51% chance of covering the spread, while the 178.5-point over/under has a 51% chance of staying under.

 

Port Adelaide vs. Richmond odds

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

Bet Type Power Tigers
H2H (Moneyline) -208 +165
Line (Spread) -13.5 (-115) +13.5 (-115)
Total o178.5 (-115) u178.5 (-115)

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

Power vs. Tigers 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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