Baylor vs. UCF prediction favors Baylor to win in college football Week 9 [2026]

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

Our famous predictive model gives Baylor a 52.6% chance of beating UCF. Our predicted final score has Baylor winning 25-24. According to our model, Baylor (+2.5) has a 59.6% chance of covering the spread, while the 48.5-point over/under has a 53.7% 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: Baylor +2.5 (-138) / UCF -2.5 (+133)
• Moneyline: Baylor -117, UCF +113
• Total: Over/Under 48.5 (+104/-106)

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: Baylor +2.5 @ 58¢ via Novig
• Moneyline: UCF @ 47¢ via Novig
• Total: Over 48.5 @ 49¢ via Novig

According to our college football best bets, the top play to make on this game is Over 48.5 total points.

These picks are based on our probabilities matched against the implied probabilities from the current available odds.

Game info & kickoff details

Friday's college football action between UCF and Baylor at Acrisure Bounce House is scheduled to begin at 7:30 PM ET.

• Who: Baylor vs. UCF
• Date: Friday, October 30, 2026
• Time: 7:30 PM ET/4:30 PM PT
• Venue: Acrisure Bounce House

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Conclusion

We predict Baylor, with a 52.6% win probability, will likely beat UCF in Friday'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.