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Canisius vs. Siena prediction: Siena favored to win men's college basketball matchup [12/7/2025]

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Written by Jason Bevilacqua

Get Canisius vs Siena predictions for college basketball Sunday.

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

Siena and Canisius will lock horns in men's college basketball action at MVP Arena on Sunday, with tipoff at 2:00PM ET.

Based on the latest simulations, Dimers' proven college basketball model predicts Siena as the most likely winner of the Canisius vs. Siena game.

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

Canisius vs. Siena prediction: Who will win and cover?

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

Our independent predictive model gives Siena a 95% chance of beating Canisius. Our predicted final score has Siena winning 75-58.

According to our model, the bookies have got it right, and Canisius and Siena each have a 50% chance of covering the spread, while the over/under total of 131.5 points has a 54% chance of going over.

 

Canisius vs. Siena odds

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

Bet Type Canisius Siena
Spread +17.5 (-105) -17.5 (-108)
Moneyline +1300 -2100
Total o131.5 (-114) u131.5 (-105)

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

Canisius vs. Siena picks and best bet

After matching our predictions 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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