Brown vs. Yale prediction favors Yale to win in college football Week 10 [2026]

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

Our leading predictive model gives Yale a 70.6% chance of defeating Brown. Our predicted final score has Yale winning 27-21. According to our model, Yale (-6.5) has a 50.5% chance of covering the spread, while the over/under total of 46.5 points has a 54.5% chance of going over.

Latest betting odds

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

• Spread: Brown +6.5 (+108) / Yale -6.5 (-117)
• Moneyline: Brown +245, Yale -251
• Total: Over/Under 46.5 (-110/-112)

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: Brown +6.5 @ 48¢ via Novig
• Moneyline: Brown @ 29¢ via Novig
• Total: Over 46.5 @ -110 via DraftKings

According to our college football best bets, the top play to make on this game is Over 46.5 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 matchup between Yale and Brown at Yale Bowl is scheduled to begin at 12:00 PM ET.

• Who: Brown vs. Yale
• Date: Saturday, November 7, 2026
• Time: 12:00 PM ET/9:00 AM PT
• Venue: Yale Bowl

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Conclusion

We predict Yale, with a 70.6% win probability, will likely beat Brown 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.