Michigan vs. Oregon prediction favors Oregon to win in college football Week 11 [2026]

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

Our famous predictive model gives Oregon an 81.2% chance of beating Michigan. Our predicted final score has Oregon winning 26-15. According to our model, Oregon (-10.5) has a 51.6% chance of covering the spread, while the 38.5-point over/under has a 58.0% 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: Michigan +10.5 (-106) / Oregon -10.5 (+104)
• Moneyline: Michigan +344, Oregon -355
• Total: Over/Under 38.5 (-102/-102)

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

Model picks and best bet

After matching our 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: Oregon -10.5 @ 49¢ via Novig
• Moneyline: Oregon @ 78¢ via Novig
• Total: Over 38.5 @ 50¢ via Novig

According to our best college football bets, the top play to make on this game is Over 38.5 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 Oregon and Michigan at Autzen Stadium is scheduled to commence at 3:30 PM ET.

• Who: Michigan vs. Oregon
• Date: Saturday, November 14, 2026
• Time: 3:30 PM ET/12:30 PM PT
• Venue: Autzen Stadium

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Conclusion

We predict Oregon, with an 81.2% win probability, will likely beat Michigan 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.