Arizona vs. Texas Tech prediction: Why Texas Tech is favored to win in college football Week 9 [2026]

Using innovative machine learning and data, we have re-simulated the result of Arizona vs. Texas Tech, forming part of our college football predictions coverage.

Our famous predictive model currently gives Texas Tech a 63.3% chance of beating Arizona. Our predicted final score has Texas Tech winning 29-25. According to our model, Arizona (+7.5) has a 61.6% chance of covering the spread, while the 54.5-point over/under has a 50.9% chance of going over.

Latest betting odds

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

• Spread: Arizona +7.5 (-160) / Texas Tech -7.5 (+150)
• Moneyline: Arizona +163, Texas Tech -165
• Total: Over/Under 54.5 (-102/-102)

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: Arizona +7.5 @ 61¢ via Novig
• Moneyline: Texas Tech @ -165 via Caesars
• Total: Over 54.5 @ 50¢ via Novig

According to our college football best bets, the top play to make on this game is Texas Tech 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 matchup between Texas Tech and Arizona at Galaxy Stadium is scheduled to commence at 12:00 PM ET.

• Who: Arizona vs. Texas Tech
• Date: Saturday, October 31, 2026
• Time: 12:00 PM ET/9:00 AM PT
• Venue: Galaxy Stadium

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Conclusion

We predict Texas Tech, with a 63.3% win probability, will likely beat Arizona 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.