Using powerful 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 leading predictive model gives Shnaider a 71% chance of winning against Tjen at the WTA China Open tournament.
Additionally, Shnaider has a 67% chance of winning the first set. The simulations also show Tjen (+4.5) has a 53% chance of covering the games spread, while the under 21.5 games has a 53% chance of hitting, according to our model.

 

Latest betting odds

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

Moneyline: Diana Shnaider -278, Janice Tjen +235
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 @ +235 via DraftKings
First Set: Shnaider @ -125 via DraftKings

According to our tennis best bets, the top play to make on this match is over 21.5 total games.

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 begin 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 in this article are United States Eastern Time unless otherwise stated.

Conclusion

We predict Diana Shnaider, with a 71% 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.