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

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Written by Jason Bevilacqua

Get Charlotte vs Rice predictions for college basketball Sunday.

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

Rice will face Charlotte in men's college basketball action at Tudor Fieldhouse on Sunday, commencing at 2:00 PM ET.

Based on updated simulations, Dimers' advanced college basketball model predicts Charlotte as the most likely winner of the Charlotte vs. Rice game.

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

Charlotte vs. Rice prediction: Who will win and cover?

Using powerful machine learning and data analysis, we have simulated the result of Sunday's NCAA basketball game between Charlotte and Rice 10,000 times as part of our men's college basketball predictions coverage.

Our leading predictive model currently gives Charlotte a 55% chance of defeating Rice. Our predicted final score has Charlotte winning 71-69.

According to our model, Rice (+1.5) has a 51% chance of covering the spread, while the 138.5-point over/under has a 55% chance of going over.

 

Charlotte vs. Rice odds

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

Bet Type Charlotte Rice
Spread -1.5 (-102) +1.5 (-115)
Moneyline -110 +102
Total o138.5 (-105) u138.5 (-115)

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

Charlotte vs. Rice 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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