Brown vs. New Haven prediction favors Brown to win in college football Week 3 [2026]

Using powerful machine learning and data, we have re-simulated the result of Brown vs. New Haven, forming part of our college football predictions coverage.

Our independent predictive model currently gives Brown a 78.7% chance of beating New Haven. Our predicted final score has Brown winning 30-20. According to our model, New Haven (+10.5) has a 52.3% chance of covering the spread, while the 49.5-point over/under has a 52.7% chance of going over.

Latest betting odds

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

• Spread: Brown -10.5 (-110) / New Haven +10.5 (-110)
• Moneyline: Brown -400, New Haven +320
• Total: Over/Under 49.5 (-110/-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: New Haven +10.5 @ -110 via bet365
• Moneyline: Brown @ -400 via bet365
• Total: Over 49.5 @ -110 via bet365

According to our college football best bets, the top play to make on this game is Over 49.5 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 New Haven and Brown at Ralph F. DellaCamera Stadium is scheduled to start at 12:00 PM ET.

• Who: Brown vs. New Haven
• Date: Saturday, September 19, 2026
• Time: 12:00 PM ET/9:00AM PT
• Venue: Ralph F. DellaCamera Stadium

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Conclusion

We predict Brown, with a 78.7% win probability, will likely beat New Haven 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.