TCU vs. Baylor prediction favors Baylor to win in college football Week 7 [2026]

Using innovative machine learning and data analysis, we have re-simulated the outcome of TCU vs. Baylor, forming part of our college football predictions coverage.

Our independent predictive model currently gives Baylor a 62.9% chance of beating TCU. Our predicted final score has Baylor winning 27-23. According to our model, Baylor (-2.5) has a 58.0% chance of covering the spread, while the over/under total of 50.5 points has a 52.6% chance of going over.

Latest betting odds

We have researched the best college football odds in America for this game, which are listed here:

• Spread: TCU +2.5 (-112) / Baylor -2.5 (-118)
• Moneyline: TCU +167, Baylor -140
• Total: Over/Under 50.5 (-106/-109)

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

Model picks and best bet

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

• Spread: Baylor -2.5 @ -118 via FanDuel
• Moneyline: Baylor @ -140 via FanDuel
• Total: Over 50.5 @ -106 via FanDuel

According to our college football best bets, the top play to make on this game is Baylor to win.

These picks are based on our probabilities matched against the implied probabilities from the current available odds.

Game info & kickoff details

Saturday's college football game between Baylor and TCU at McLane Stadium is scheduled to begin at 7:00 PM ET.

• Who: TCU vs. Baylor
• Date: Saturday, October 17, 2026
• Time: 7:00 PM ET/4:00PM PT
• Venue: McLane Stadium

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Conclusion

We predict Baylor, with a 62.9% win probability, will likely beat TCU in Saturday's college football matchup.

Additional tools and information for betting safely can be found in our Responsible Gambling hub.

This article's predictions and probabilities are generated by Dimers' proprietary College Football prediction model. Our editorial team reviews the resulting content for accuracy and presentation before publication.