Donna Vekic vs. Xinyu Wang prediction, odds, picks for WTA Singapore 2026

Using powerful machine learning and data analysis, we have re-simulated the result of Sunday's Vekic-Wang women's singles match, forming part of our tennis predictions coverage.

Our famous predictive model currently gives Wang a 52% chance of defeating Vekic at the WTA Singapore tournament. Additionally, Wang has a 52% chance of winning the first set, 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: Xinyu Wang -135, Donna Vekic +110
• First Set: Vekic +100, Wang -125

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: Vekic @ +110 via DraftKings
• First Set: Vekic @ +100 via DraftKings

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

Although Vekic is less than likely to win, she 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 WTA Singapore match between Donna Vekic and Xinyu Wang is scheduled to begin on Sunday at 11:00 PM ET.

• Who: Donna Vekic vs. Xinyu Wang
• Date: Sunday, September 20, 2026
• Approx. Time: 11:00 PM ET/8:00PM PT
• Tournament: WTA Singapore, Singapore Women's Singles 2026
• Round: Round of 32

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

Conclusion

We predict Xinyu Wang, with a 52% win probability, will likely beat Donna Vekic at the WTA Singapore 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.