Stony Brook vs. Campbell prediction: Why Campbell is favored to win in college football Week 10 [2026]

Using trusted machine learning and data, we have re-simulated the outcome of Stony Brook vs. Campbell, forming part of our college football predictions coverage.

Our independent predictive model currently gives Campbell a 75.0% chance of defeating Stony Brook. Our predicted final score has Campbell winning 36-28. According to our model, Campbell (-7) has a 55.1% chance of covering the spread, while the over/under total of 67.5 points has a 56.3% chance of staying under.

Latest betting odds

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

• Spread: Stony Brook +7 (-110) / Campbell -7 (-113)
• Moneyline: Stony Brook +251, Campbell -270
• Total: Over/Under 67.5 (+100/-110)

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

Model picks and best bet

After matching our predictions against the best current odds, we can reveal our picks for each of the major markets in this matchup. Plus, find our best bet for the game below:

• Spread: Campbell -7 @ -113 via DraftKings
• Moneyline: Campbell @ 73¢ via Novig
• Total: Under 67.5 @ -110 via BetRivers

According to our best college football bets, the top play to make on this game is Under 67.5 total points.

These picks are based on our probabilities matched against the implied probabilities from the current available odds.

Game info & kickoff details

Saturday's college football game between Campbell and Stony Brook at Barker-Lane Stadium is scheduled to begin at 1:00 PM ET.

• Who: Stony Brook vs. Campbell
• Date: Saturday, November 7, 2026
• Time: 1:00 PM ET/10:00 AM PT
• Venue: Barker-Lane Stadium

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Conclusion

We predict Campbell, with a 75.0% win probability, will likely beat Stony Brook in Saturday's college football matchup.

Additional tools and information for betting safely can be found in our Responsible Gambling hub.

This article's predictions and probabilities are generated by Dimers' proprietary college football prediction model. Our editorial team reviews the resulting content for accuracy and presentation before publication.