Marist vs. Lafayette prediction favors Lafayette to win in college football Week 2 [2026]

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

Our famous predictive model gives Lafayette an 82.1% chance of beating Marist. Our predicted final score has Lafayette winning 30-18. According to our model, Marist (+15) has a 56.6% chance of covering the spread, while the over/under total of 47.5 points has a 53.6% 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: Marist +15 (-105) / Lafayette -15 (-115)
• Moneyline: Marist +484, Lafayette -650
• Total: Over/Under 47.5 (-105/-115)

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: Marist +15 @ -105 via bet365
• Moneyline: Marist @ +484 via DraftKings
• Total: Over 47.5 @ -105 via bet365

According to our best college football bets, the top play to make on this game is Marist +15 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 matchup between Lafayette and Marist at Fisher Stadium is scheduled to begin at 12:30 PM ET.

• Who: Marist vs. Lafayette
• Date: Saturday, September 12, 2026
• Time: 12:30 PM ET/9:30AM PT
• Venue: Fisher Stadium

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Conclusion

We predict Lafayette, with an 82.1% win probability, will likely beat Marist 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.