Temple vs. USF prediction favors South Florida to win in college football Week 5 [2026]

Using powerful machine learning and statistical analysis, we have re-simulated the result of Temple vs. USF, forming part of our college football predictions coverage.

Our famous predictive model gives South Florida a 70.0% chance of defeating Temple. Our predicted final score has South Florida winning 27-21. According to our model, South Florida (-5.5) has a 52.4% chance of covering the spread, while the 48.5-point over/under has a 52.3% 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: Temple +5.5 (-105) / USF -5.5 (-112)
• Moneyline: Temple +190, USF -230
• Total: Over/Under 48.5 (-107/-108)

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 available 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: South Florida -5.5 @ -112 via DraftKings
• Moneyline: South Florida @ -230 via bet365
• Total: Over 48.5 @ -107 via Caesars

According to our college football best bets, the top play to make on this game is Over 48.5 total points.

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 action between USF and Temple at Raymond James Stadium is scheduled to begin at 7:30 PM ET.

• Who: Temple vs. South Florida
• Date: Saturday, October 3, 2026
• Time: 7:30 PM ET/4:30PM PT
• Venue: Raymond James Stadium

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Conclusion

We predict South Florida, with a 70.0% win probability, will likely beat Temple 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.