Columbia vs. Harvard prediction favors Harvard to win in college football Week 10 [2026]

Using innovative machine learning and data, we have re-simulated the result of Columbia vs. Harvard, forming part of our college football predictions coverage.

Our famous predictive model currently gives Harvard a 92.9% chance of beating Columbia. Our predicted final score has Harvard winning 34-13. According to our model, Columbia (+21.5) has a 53.1% chance of covering the spread, while the over/under total of 47.5 points has a 52.5% 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: Columbia +21.5 (-110) / Harvard -21.5 (-110)
• Moneyline: Columbia +1076, Harvard -1233
• Total: Over/Under 47.5 (-110/-102)

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

Model picks and best bet

After matching our probabilities 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: Columbia +21.5 @ -110 via BetRivers
• Moneyline: Harvard @ 93¢ via Novig
• Total: Over 47.5 @ -110 via bet365

According to our best college football bets, the top play to make on this game is Columbia +21.5 at the spread.

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 Harvard and Columbia at Harvard Stadium is scheduled to commence at 1:00 PM ET.

• Who: Columbia vs. Harvard
• Date: Saturday, November 7, 2026
• Time: 1:00 PM ET/10:00 AM PT
• Venue: Harvard Stadium

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Conclusion

We predict Harvard, with a 92.9% win probability, will likely beat Columbia 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.