dpOur leading predictive model gives Khachanov a 57% chance of defeating Shapovalov at the ATP Paris Masters tournament.
Additionally, Khachanov has a 55% chance of winning the first set. The simulations also show Shapovalov (+2.5) has a 53% chance of covering the games spread, while the under 24.5 games has a 55% chance of hitting, according to our model.
Latest betting odds
We have researched the most up-to-date betting odds in America for this match, which are listed here:
- Moneyline: Karen Khachanov -167, Denis Shapovalov +146
- First Set: Shapovalov +130, Khachanov -164
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:
- Moneyline: Shapovalov @ +146 via DraftKings
- First Set: Khachanov @ -130 via DraftKings
According to our tennis best bets, the top play to make on this match is Denis Shapovalov to win.
Although Shapovalov is less than likely to win, he provides the best value at the current available odds.
These picks are based on our probabilities matched against the implied probabilities from the current available odds.
Game info & first serve details
The ATP Paris Masters match between Denis Shapovalov and Karen Khachanov is scheduled to start on Monday at 1:00 PM ET.
- Who: Denis Shapovalov vs. Karen Khachanov
- Date: Monday, November 2, 2026
- Approx. Time: 1:00 PM ET/10:00 AM PT
- Tournament: ATP Paris, France Men’s Singles 2026
- Round: Round of 64
All dates and times mentioned in this article are United States Eastern Time unless otherwise noted.
Conclusion
We predict Karen Khachanov, with a 57% win probability, will likely beat Denis Shapovalov at the ATP Paris Masters tournament.
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 Tennis prediction model. Our editorial team reviews the resulting content for accuracy and presentation before publication.
