New Haven vs. Austin Peay prediction: Why Austin Peay is favored to win in college football Week 5 [2026]

Using powerful machine learning and data analysis, we have re-simulated the outcome of New Haven vs. Austin Peay, forming part of our college football predictions coverage.

Our leading predictive model currently gives Austin Peay a 99.3% chance of defeating New Haven. Our predicted final score has Austin Peay winning 43-7. According to our model, Austin Peay (-35.5) has a 50.9% chance of covering the spread, while the 50.5-point over/under has a 51.8% 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: New Haven +35.5 (-115) / Austin Peay -35.5 (-115)
• Moneyline: New Haven , Austin Peay

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:

• Moneyline: Over @ -113 via DraftKings

According to our college football best bets, the top play to make on this game is over 50.5 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 matchup between Austin Peay and New Haven at Fortera Stadium is scheduled to begin at 5:00 PM ET.

• Who: New Haven vs. Austin Peay
• Date: Saturday, October 3, 2026
• Time: 5:00 PM ET/2:00PM PT
• Venue: Fortera Stadium

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Conclusion

We predict Austin Peay, with a 99.3% win probability, will likely beat New Haven 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.