Yale vs. Holy Cross prediction favors Yale to win in college football Week 3 [2026]

Using innovative machine learning and statistical analysis, we have re-simulated the result of Yale vs. Holy Cross, forming part of our college football predictions coverage.

Our famous predictive model currently gives Yale a 93.2% chance of beating Holy Cross. Our predicted final score has Yale winning 35-15. According to our model, Holy Cross (+21.5) has a 52.9% chance of covering the spread, while the over/under total of 50.5 points has a 51.4% 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: Yale -21.5 (-105) / Holy Cross +21.5 (-115)
• Moneyline: Yale -1640, Holy Cross +1000
• Total: Over/Under 50.5 (-112/-105)

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: Holy Cross +21.5 @ -115 via bet365
• Moneyline: Yale @ -1640 via DraftKings
• Total: Over 50.5 @ -112 via DraftKings

According to our college football best bets, the top play to make on this game is Holy Cross +21.5 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 action between Holy Cross and Yale at Fitton Field is scheduled to start at 2:00 PM ET.

• Who: Yale vs. Holy Cross
• Date: Saturday, September 19, 2026
• Time: 2:00 PM ET/11:00AM PT
• Venue: Fitton Field

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Conclusion

We predict Yale, with a 93.2% win probability, will likely beat Holy Cross 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.