Viktorija Golubic vs. Peyton Stearns prediction, odds, picks for WTA China Open 2026

Using innovative machine learning and data analysis, we have re-simulated the result of Thursday's Golubic-Stearns women's singles match, forming part of our tennis predictions coverage.

Our famous predictive model currently gives Stearns a 59% chance of beating Golubic at the WTA China Open tournament. Additionally, Stearns has a 57% 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: Peyton Stearns -170, Viktorija Golubic +146
• First Set: Golubic +130, Stearns -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: Golubic @ +146 via DraftKings
• First Set: Golubic @ +130 via DraftKings

According to our tennis best bets, the top play to make on this match is Viktorija Golubic to win the first set.

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

Game info & first serve details

The WTA China Open match between Viktorija Golubic and Peyton Stearns is scheduled to begin on Thursday at 11:00 PM ET.

• Who: Viktorija Golubic vs. Peyton Stearns
• Date: Thursday, October 1, 2026
• Approx. Time: 11:00 PM ET/8:00PM PT
• Tournament: WTA Beijing, China Women's Singles 2026
• Round: Round of 64

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

Conclusion

We predict Peyton Stearns, with a 59% win probability, will likely beat Viktorija Golubic at the WTA China 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.