Taylor Fritz vs. Cameron Norrie prediction, odds, picks for ATP Stockholm Open 2026

Using powerful machine learning and data analysis, we have re-simulated the result of Wednesday's Fritz-Norrie men's singles match, forming part of our tennis predictions coverage.

Our famous predictive model gives Fritz a 74% chance of defeating Norrie at the ATP Stockholm Open tournament. Additionally, Fritz has a 70% chance of winning the first set. The simulations also show Fritz (-3.5) has a 53% chance of covering the games spread, while the under 23.5 games has a 60% chance of hitting, according to our model.

Latest betting odds

We have sourced the most up-to-date betting odds in America for this match, which are listed here:

• Moneyline: Cameron Norrie +263, Taylor Fritz -333
• First Set: Fritz -250, Norrie +200

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 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:

• Moneyline: Norrie @ +263 via DraftKings
• First Set: Norrie @ -150 via DraftKings

According to our tennis best bets, the top play to make on this match is over 23.5 total games.

These picks are based on our probabilities matched against the implied probabilities from the current available odds.

Game info & first serve details

The ATP Stockholm Open match between Taylor Fritz and Cameron Norrie is scheduled to start on Wednesday at 8:30 AM ET.

• Who: Taylor Fritz vs. Cameron Norrie
• Date: Wednesday, November 11, 2026
• Approx. Time: 8:30 AM ET/5:30 AM PT
• Tournament: ATP Stockholm, Sweden Men's Singles 2026
• Round: Round of 16

All dates and times in this article are United States Eastern Time unless otherwise stated.

Conclusion

We predict Taylor Fritz, with a 74% win probability, will likely beat Cameron Norrie at the ATP Stockholm Open tournament.

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This article's predictions and probabilities are generated by Dimers' proprietary tennis prediction model. Our editorial team reviews the resulting content for accuracy and presentation before publication.