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Niagara vs. Manhattan prediction: Why Manhattan is favored to win men's college basketball matchup [1/11/2026]

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Written by Jason Bevilacqua

Get Niagara vs Manhattan predictions for college basketball Sunday.

Niagara-Manhattan Predictions and Game Preview.
Niagara vs. Manhattan men's college basketball prediction for Sunday, January 11, 2026.

Manhattan and Niagara will lock horns in men's college basketball action at Draddy Gymnasium on Sunday, with tipoff at 2:00 PM ET.

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

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

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

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

Our independent predictive model gives Manhattan a 68% chance of beating Niagara. Our predicted final score has Manhattan winning 74-69.

According to our model, Niagara (+5.5) has a 55% chance of covering the spread, while the over/under total of 141.5 points has a 54% chance of going over.

 

Niagara vs. Manhattan odds

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

Bet Type Niagara Manhattan
Spread +5.5 (-108) -5.5 (-110)
Moneyline +210 -250
Total o141.5 (-105) u141.5 (-110)

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

Niagara vs. Manhattan picks and best bet

After matching our predictions against the best available 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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