Cornell vs. Georgetown prediction favors Cornell to win in college football Week 5 [2026]

Using innovative machine learning and data analysis, we have re-simulated the outcome of Cornell vs. Georgetown, forming part of our college football predictions coverage.

Our famous predictive model currently gives Cornell a 73.1% chance of defeating Georgetown. Our predicted final score has Cornell winning 27-19. According to our model, Georgetown (+7.5) has a 51.5% chance of covering the spread, while the 45.5-point over/under has a 53.6% 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: Cornell -7.5 (+109) / Georgetown +7.5 (-125)
• Moneyline: Cornell -275, Georgetown +246
• Total: Over/Under 45.5 (-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: Cornell -7.5 @ +109 via Caesars
• Moneyline: Cornell @ -275 via Caesars
• Total: Over 45.5 @ -110 via Caesars

According to our college football best bets, the top play to make on this game is Over 45.5 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 action between Georgetown and Cornell at Cooper Field is scheduled to begin at 12:30 PM ET.

• Who: Cornell vs. Georgetown
• Date: Saturday, October 3, 2026
• Time: 12:30 PM ET/9:30AM PT
• Venue: Cooper Field

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Conclusion

We predict Cornell, with a 73.1% win probability, will likely beat Georgetown 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.