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

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

Our independent predictive model currently gives Oregon a 75.9% chance of defeating Illinois. Our predicted final score has Oregon winning 29-20. According to our model, Illinois (+13.5) has a 58.8% chance of covering the spread, while the 52.5-point over/under has a 55.6% chance of staying under.

Latest betting odds

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

• Spread: Oregon -13.5 (+127) / Illinois +13.5 (-130)
• Moneyline: Oregon -355, Illinois +344
• Total: Over/Under 52.5 (+147/-153)

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: Illinois +13.5 @ 57¢ via Novig
• Moneyline: Illinois @ 23¢ via Novig
• Total: Over 52.5 @ 40¢ via Novig

According to our college football best bets, the top play to make on this game is Over 52.5 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 Illinois and Oregon at Gies Memorial Stadium is scheduled to commence at 3:00 PM ET.

• Who: Oregon vs. Illinois
• Date: Saturday, October 24, 2026
• Time: 3:00 PM ET/12:00 PM PT
• Venue: Gies Memorial Stadium

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Conclusion

We predict Oregon, with a 75.9% win probability, will likely beat Illinois 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.