Ann Li vs. Elina Svitolina prediction, odds, picks for WTA China Open 2026

Using powerful machine learning and data, we have re-simulated the result of Tuesday's Li-Svitolina women's singles match, forming part of our tennis predictions coverage.

Our famous predictive model gives Svitolina a 77% chance of defeating Li at the WTA China Open tournament. Additionally, Svitolina has a 71% chance of winning the first set, while the under 21.5 games has a 57% chance of hitting, 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: Elina Svitolina -357, Ann Li +300
• First Set: Li +240, Svitolina -303

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 available 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: Svitolina @ -357 via DraftKings
• First Set: Svitolina @ -135 via DraftKings

According to our tennis best bets, the top play to make on this match is Elina Svitolina 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 Ann Li and Elina Svitolina is scheduled to commence on Tuesday at 11:00 PM ET.

• Who: Ann Li vs. Elina Svitolina
• Date: Tuesday, October 6, 2026
• Approx. Time: 11:00 PM ET/8:00PM PT
• Tournament: WTA Beijing, China Women's Singles 2026
• Round: Round of 16

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

Conclusion

We predict Elina Svitolina, with a 77% win probability, will likely beat Ann Li 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.