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SMU vs. Texas A&M prediction: Why Texas A&M is favored to win men's college basketball matchup [12/7/2025]

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Written by Jason Bevilacqua

Get SMU vs Texas A&M predictions for college basketball Sunday.

SMU-Texas A&M Predictions and Game Preview.
SMU vs. Texas A&M men's college basketball prediction for Sunday, December 7, 2025.

Texas A&M and SMU are scheduled to meet in men's college basketball action at College Park Center on Sunday, with tipoff at 5:00PM ET.

Based on the latest simulation results, Dimers' advanced college basketball model projects Texas A&M as the most likely winner of the SMU vs. Texas A&M game.

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

SMU vs. Texas A&M prediction: Who will win and cover?

Using powerful machine learning and data, we have simulated the outcome of Sunday's NCAA basketball game between SMU and Texas A&M 10,000 times as part of our men's college basketball predictions coverage.

Our independent predictive model gives Texas A&M a 56% chance of defeating SMU. Our predicted final score has Texas A&M winning 80-78.

According to our model, Texas A&M (-1.5) has a 51% chance of covering the spread, while the 164.5-point over/under has a 55% chance of staying under.

 

SMU vs. Texas A&M odds

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

Bet Type SMU Texas A&M
Spread +1.5 (-105) -1.5 (-110)
Moneyline +105 -120
Total o164.5 (-115) u164.5 (-105)

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

SMU vs. Texas A&M 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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