Monmouth vs. Hampton prediction favors Monmouth to win in college football Week 8 [2026]

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

Our independent predictive model currently gives Monmouth a 97.4% chance of beating Hampton. Our predicted final score has Monmouth winning 41-15. According to our model, Hampton (+26.5) has a 51.3% chance of covering the spread, while the 58.5-point over/under has a 51.6% 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: Monmouth -26.5 (-112) / Hampton +26.5 (-110)
• Moneyline: Monmouth -1718, Hampton +1567
• Total: Over/Under 58.5 (+100/-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 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: Hampton +26.5 @ -110 via Caesars
• Moneyline: Monmouth @ 95¢ via Novig
• Total: Under 58.5 @ -112 via DraftKings

According to our college football best bets, the top play to make on this game is Monmouth to win.

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 Hampton and Monmouth at Armstrong Stadium is scheduled to commence at 2:00 PM ET.

• Who: Monmouth vs. Hampton
• Date: Saturday, October 24, 2026
• Time: 2:00 PM ET/11:00 AM PT
• Venue: Armstrong Stadium

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Conclusion

We predict Monmouth, with a 97.4% win probability, will likely beat Hampton 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.