Mercer vs. Chattanooga prediction: Why Mercer is favored to win in college football Week 10 [2026]

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

Our leading predictive model gives Mercer a 56.1% chance of defeating Chattanooga. Our predicted final score has Mercer winning 22-20. According to our model, Mercer (-1.5) has a 51.1% chance of covering the spread, while the over/under total of 40.5 points has a 55.0% 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: Mercer -1.5 (-106) / Chattanooga +1.5 (+104)
• Moneyline: Mercer -121, Chattanooga +125
• Total: Over/Under 40.5 (-113/-110)

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: Chattanooga +1.5 @ 49¢ via Novig
• Moneyline: Mercer @ -121 via BetRivers
• Total: Over 40.5 @ -113 via DraftKings

According to our college football best bets, the top play to make on this game is Over 40.5 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 game between Chattanooga and Mercer at Finley Stadium is scheduled to start at 1:00 PM ET.

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

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Conclusion

We predict Mercer, with a 56.1% win probability, will likely beat Chattanooga 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.