Mattia Bellucci vs. Kamil Majchrzak prediction, odds, picks for ATP Hangzhou Open 2026

Using trusted machine learning and statistical analysis, we have re-simulated the result of Wednesday's Bellucci-Majchrzak men's singles match, forming part of our tennis predictions coverage.

Our leading predictive model currently gives Majchrzak a 54% chance of beating Bellucci at the ATP Hangzhou Open tournament.

Latest betting odds

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

• Moneyline: Kamil Majchrzak -156, Mattia Bellucci +139

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: Bellucci @ +139 via DraftKings
• First Set: Majchrzak @ -135 via DraftKings

According to our best tennis bets, the top play to make on this match is Mattia Bellucci to win.

Although Bellucci 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 Hangzhou Open match between Mattia Bellucci and Kamil Majchrzak is scheduled to start on Wednesday at 12:00 AM ET.

• Who: Mattia Bellucci vs. Kamil Majchrzak
• Date: Wednesday, September 23, 2026
• Approx. Time: 12:00 AM ET/9:00PM PT
• Tournament: ATP Hangzhou, China Men's Singles 2026
• Round: Round of 32

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

Conclusion

We predict Kamil Majchrzak, with a 54% win probability, will likely beat Mattia Bellucci at the ATP Hangzhou Open 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.