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Manhattan vs. Marist prediction: Why Marist is favored to win men's college basketball matchup [12/7/2025]

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Written by Jason Bevilacqua

Get Manhattan vs Marist predictions for college basketball Sunday.

Manhattan-Marist Predictions and Game Preview.
Manhattan vs. Marist men's college basketball prediction for Sunday, December 7, 2025.

Marist will face Manhattan in men's college basketball action at McCann Arena on Sunday, commencing at 2:00PM ET.

Based on the latest simulation results, Dimers' advanced college basketball model predicts Marist as the most likely winner of the Manhattan vs. Marist game.

This article offers a closer look at Sunday's matchup, including an expanded look at the predicted score, best bets and picks.

Manhattan vs. Marist prediction: Who will win and cover?

Using trusted machine learning and statistical analysis, we have simulated the outcome of Sunday's NCAA basketball matchup between Manhattan and Marist 10,000 times as part of our men's college basketball predictions coverage.

Our leading predictive model gives Marist a 78% chance of beating Manhattan. Our predicted final score has Marist winning 74-66.

According to our model, Marist (-7.5) has a 51% chance of covering the spread, while the over/under total of 140.5 points has a 52% chance of going over.

 

Manhattan vs. Marist odds

We have sourced the best men's college basketball odds in America for this game, which are listed here:

Bet Type Manhattan Marist
Spread +7.5 (-110) -7.5 (-110)
Moneyline +285 -345
Total o140.5 (-108) u140.5 (-110)

All odds are correct at the time of publication and are subject to change.

Manhattan vs. Marist picks and best bet

After matching our probabilities against the best current odds, we can reveal our picks for each of the major markets. Plus, find our best bet for the game below:

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Written by
Jason Bevilacqua
Head of Content and Communities

Jason Bevilacqua, an expert in MLB, NHL, NBA, MLS, and NFL, delivers game previews, best bets, and props. Since 2020, as Head of Social and Community at Dimers, he has contributed insightful articles utilizing data-driven models and simulations.

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