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Ann Li vs Elina Svitolina Prediction - WTA China Open 2026

Ann Li will take on Elina Svitolina in the round of 16 at the 2026 WTA China Open tournament on Wednesday.

This article features Stats Insider's top betting tips for the Li vs Svitolina match, plus the latest betting odds in Australia.

Who Will Win?

Utilising trusted computer power and data, Stats Insider has simulated the result of Wednesday's Li-Svitolina women's singles match 10,000 times.

Our independent predictive analytics model currently gives Svitolina a 77% chance of defeating Li at the WTA China Open tournament.

Li vs Svitolina: Odds

The latest betting odds in Australia for Wednesday's WTA China Open match between Li and Svitolina are shown here:

  • Head to Head: Li $4.00, Svitolina $1.25
  • First Set: Li $3.40, Svitolina $1.33

Odds are correct at the time of publication and subject to change.

Looking at the latest head-to-head odds, TAB currently has Li at $4.00 and Svitolina at $1.25.

TAB currently has odds for Li to win the first set at $3.40 and odds for Svitolina to win the first set at $1.33.

Li vs Svitolina: Best Bets

  • Head to Head: Li at $4.00 with TAB
  • First Set: Svitolina at $1.80 with TAB (53% probability)

Stats Insider's Ann Li vs Elina Svitolina betting tips are based on detailed modelling and betting expertise to help you place more informed bets with your chosen online bookie.

Although our predictive analytics model indicates that Svitolina is more likely to win the match, betting on Li to win is the best option because of the edge we identified when comparing our data-led probabilities to the odds that are currently being offered.

Taking advantage of the edges seen on Stats Insider is one of the keys to being profitable over the long run.

And while Svitolina is more likely to win the first set on this occassion, our suggested bet of Svitolina ($1.80) is based on the chance of that happening, per our model, and the betting odds currently available.

Li vs Svitolina: Prediction

Stats Insider provides full coverage of the Ann Li vs Elina Svitolina match at the WTA China Open tournament, including data-driven predictions and the best betting tips.

Our model updates frequently, so keep checking this page for the latest betting tips before the Li-Svitolina match at the WTA China Open event.

As always, see Stats Insider's Best Bets to get the best tips on every tennis match, plus predictions for a wide range of other sports.

Li vs Svitolina: WTA China Open Essential Details

The 2026 WTA China Open match between Ann Li and Elina Svitolina is scheduled to start at 2:00pm AEDT.

  • Match: Ann Li vs Elina Svitolina
  • Date: Wednesday 7 October 2026
  • Approx. Time: 2:00pm AEDT
  • Event: WTA Beijing, China Women's Singles 2026
  • Round: Round of 16

All dates and times in this article are in Australian Eastern Daylight Time (AEDT), unless otherwise noted.

Conclusion

Our Ann Li vs Elina Svitolina predictions have been made after running 10,000 data-driven simulations of the game, carefully curated by our team of experienced data scientists and analysts. We use cutting-edge technology and machine learning to ensure our tennis tips are trustworthy and reliable, giving you the confidence to make informed decisions.

If you decide to use our tennis predictions for betting purposes, it's vital to gamble responsibly and know when to stop. For free and confidential support, call 1800 858 858 or visit gamblinghelponline.org.au.

More on Tennis

Stats Insider is your go-to source for betting on tennis in Australia, with the latest tennis betting news, tips for every tennis tournament, and our in-house approach to accurately ranking the world's top 100 men's and women's players.

Stats Insider

Stats Insider, Australia's leading predictive analytics website, offers Australian sports fans innovative tools and content to enhance their enjoyment of major sporting events both domestically and internationally. Our goal is to transform the sports fan experience by providing readily accessible, data-driven content for sports enthusiasts like us.

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