LSU vs. Auburn prediction: Why LSU is favored to win in college football Week 8 [2026]

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

Our famous predictive model currently gives LSU a 71.6% chance of defeating Auburn. Our predicted final score has LSU winning 29-22. According to our model, LSU (-6.5) has a 52.2% chance of covering the spread, while the 50.5-point over/under has a 55.0% 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: LSU -6.5 (-130) / Auburn +6.5 (+125)
• Moneyline: LSU -257, Auburn +245
• Total: Over/Under 50.5 (-115/+111)

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

Model picks and best bet

After matching our predictions 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: Auburn +6.5 @ 45¢ via Novig
• Moneyline: LSU @ 72¢ via Novig
• Total: Over 50.5 @ 53¢ via Novig

According to our college football best bets, the top play to make on this game is Auburn +6.5 at the spread.

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 Auburn and LSU at Jordan-Hare Stadium is scheduled to commence at 12:00 PM ET.

• Who: LSU vs. Auburn
• Date: Saturday, October 24, 2026
• Time: 12:00 PM ET/9:00 AM PT
• Venue: Jordan-Hare Stadium

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Conclusion

We predict LSU, with a 71.6% win probability, will likely beat Auburn 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.