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Jasmine Paolini vs Sofia Kenin Prediction - WTA China Open 2025

Jasmine Paolini will face Sofia Kenin in the round of 32 at the 2025 WTA China Open tournament on Sunday.

This article features Stats Insider's prediction and tips for the Paolini vs Kenin match, as well as the latest betting odds in Australia.

Who Will Win?

Using advanced computer power and data, Stats Insider has simulated the result of Sunday's Paolini-Kenin women's singles match 10,000 times.

Our leading predictive analytics model currently gives Paolini a 73% chance of defeating Kenin at the WTA China Open tournament.

Paolini vs Kenin: Odds

The latest betting odds in Australia for Sunday's WTA China Open match between Paolini and Kenin are shown below:

  • Head to Head: Paolini $1.33, Kenin $3.40
  • First Set: Paolini $0.00, Kenin $0.00

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

Looking at the latest head-to-head odds, TAB currently has Paolini at $1.33 and Kenin at $3.40.

currently has odds for Paolini to win the first set at $0.00 and odds for Kenin to win the first set at $0.00.

Paolini vs Kenin: Best Bets

  • Head to Head: Kenin at $3.40 with TAB

These Jasmine Paolini vs Sofia Kenin best bets are based on market-leading modelling and wagering intelligence to provide you with the best possible advice 24/7/365.

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

Taking advantage of the edges published on Stats Insider is pivotal to being profitable over the long run.

And while Paolini is more likely to win the first set on this occassion, our suggested bet of Kenin ($0.00) is based on the chance of that happening, per our model, and the betting odds currently available.

Paolini vs Kenin: Prediction

Stats Insider provides full betting coverage of the Jasmine Paolini vs Sofia Kenin match at the WTA China Open tournament, including data-driven predictions and expert tips.

Our model updates frequently, so refresh this article for the latest betting predictions before the Paolini-Kenin match at the WTA China Open tournament.

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

Paolini vs Kenin: WTA China Open Essential Details

The 2025 WTA China Open match between Jasmine Paolini and Sofia Kenin is scheduled to start at 6:15pm AEST.

  • Match: Jasmine Paolini vs Sofia Kenin
  • Date: Sunday 28 September 2025
  • Approx. Time: 6:15pm AEST
  • Event: WTA Beijing, China Women's Singles 2025
  • Round: Round of 32

All dates and times mentioned in this article are in Australian Eastern Standard Time (AEST), unless otherwise noted.

Conclusion

Our Jasmine Paolini vs Sofia Kenin predictions are the result of 10,000 data-driven simulations of the game, carefully curated by our team of expert data scientists and analysts. We use the latest in predictive analytics technology and machine learning to ensure our tennis tips are accurate and reliable, giving you the knowledge you need to make informed decisions with confidence.

If you decide to use our tennis predictions for betting purposes, it's important that you 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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