Ball State vs. Kent State prediction favors Kent State to win Week 4 MACtion clash

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

Our famous predictive model gives Kent State a 58.8% chance of defeating Ball State. Our predicted final score has Kent State winning 27-24. According to our model, Ball State (+3.5) has a 53.8% chance of covering the spread, while the over/under total of 50.5 points has a 52.0% 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: Ball State +3.5 (-120) / Kent State -3.5 (+100)
• Moneyline: Ball State +135, Kent State -152
• Total: Over/Under 50.5 (-114/-105)

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: Ball State +3.5 @ -120 via bet365
• Moneyline: Ball State @ +135 via bet365
• Total: Over 50.5 @ -114 via Caesars

According to our college football best bets, the top play to make on this game is Ball State +3.5 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 Kent State and Ball State at Dix Stadium is scheduled to start at 12:00 PM ET.

• Who: Ball State vs. Kent State
• Date: Saturday, September 26, 2026
• Time: 12:00 PM ET/9:00AM PT
• Venue: Dix Stadium

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Conclusion

We predict Kent State, with a 58.8% win probability, will likely beat Ball State 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.