UConn vs. Air Force prediction: Why Connecticut is favored to win in college football Week 9 [2026]

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

Our independent predictive model gives Connecticut a 51.1% chance of beating Air Force. Our predicted final score has Connecticut winning 26-25. According to our model, Connecticut (+1.5) has a 56.1% chance of covering the spread, while the over/under total of 55.5 points has a 59.1% 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: UConn +1.5 (-124) / Air Force -1.5 (-107)
• Moneyline: UConn -104, Air Force +102
• Total: Over/Under 55.5 (+141/-156)

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 available 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: Connecticut +1.5 @ -124 via DraftKings
• Moneyline: Connecticut @ 51¢ via Novig
• Total: Over 55.5 @ 41¢ via Novig

According to our college football best bets, the top play to make on this game is Connecticut +1.5 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 action between Air Force and UConn at Falcon Stadium is scheduled to commence at 3:00 PM ET.

• Who: Connecticut vs. Air Force
• Date: Saturday, October 31, 2026
• Time: 3:00 PM ET/12:00 PM PT
• Venue: Falcon Stadium

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Conclusion

We predict Connecticut, with a 51.1% win probability, will likely beat Air Force 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.