Janice Tjen vs. Diana Shnaider prediction, odds, picks for WTA China Open 2026

Using innovative machine learning and data, we have re-simulated the outcome of Thursday's Tjen-Shnaider women's singles match, forming part of our tennis predictions coverage.

Our independent predictive model currently gives Shnaider a 72% chance of winning against Tjen at the WTA China Open tournament. Additionally, Shnaider has a 67% 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: Diana Shnaider -278, Janice Tjen +240
• First Set: Tjen +200, Shnaider -250

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: Tjen @ +240 via DraftKings
• First Set: Tjen @ +200 via DraftKings

According to our best tennis bets, the top play to make on this match is Janice Tjen 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 Janice Tjen and Diana Shnaider is scheduled to commence on Thursday at 11:00 PM ET.

• Who: Janice Tjen vs. Diana Shnaider
• 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 mentioned in this article are United States Eastern Time unless otherwise stated.

Conclusion

We predict Diana Shnaider, with a 72% win probability, will likely beat Janice Tjen 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.