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Canterbury Bulldogs vs. St George Illawarra Dragons prediction: Bulldogs favored to win Saturday's NRL Round 1 matchup [2/28/2026]

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Written by Jason Bevilacqua

Get Canterbury Bulldogs vs St George Illawarra Dragons predictions for NRL Saturday.

Canterbury Bulldogs-St George Illawarra Dragons Predictions and Game Preview.
Canterbury Bulldogs vs. St George Illawarra Dragons NRL prediction for Saturday, February 28, 2026.

The Canterbury Bulldogs will face the St George Illawarra Dragons in National Rugby League (NRL) action at Allegiant Stadium on Saturday, beginning at 11:30 PM ET.

Based on the latest simulations, Dimers' proven NRL model projects the Bulldogs as the most likely winner of the Dragons vs. Bulldogs game.

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

Bulldogs vs. Dragons prediction: Who will win Round 1 game?

Using powerful machine learning and data, we have simulated the result of Saturday's NRL game between the Dragons and Bulldogs 10,000 times as part of our NRL predictions coverage.

Our leading predictive model currently gives the Bulldogs a 79% chance of defeating the Dragons.

According to our model, the Bulldogs (-7.5) have a 61% chance of covering the spread, while the 38.5- over/under has a 60% chance of going over.

 

St George vs. Bulldogs odds

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

Bet Type Dragons Bulldogs
H2H (Moneyline) +210 -278
Line (Spread) +7.5 (-105) -7.5 (-120)
Total o38.5 (-125) u38.5 (+100)

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

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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