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Xinyu Wang vs Anna Kalinskaya Prediction - US Open 2026

Xinyu Wang will face Anna Kalinskaya in the second round of the US Open Women's Singles 2026 on Thursday.

This article features Stats Insider's best betting tips for the Wang vs Kalinskaya match, as well as the latest betting odds in Australia.

Who Will Win?

Utilising advanced machine learning and data, Stats Insider has simulated the outcome of Thursday's Wang-Kalinskaya women's singles match 10,000 times.

Our proven predictive analytics model currently gives Kalinskaya a 62% chance of winning against Wang in the US Open Women's Singles 2026.

Wang vs Kalinskaya: Odds

The current betting odds in Australia for Thursday's US Open 2026 match between Wang and Kalinskaya are listed below:

  • Head to Head: Wang $2.75, Kalinskaya $1.44
  • First Set: Wang $2.62, Kalinskaya $1.50

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

Looking at the latest head-to-head odds, TAB currently has Wang at $2.75 and Kalinskaya at $1.44.

TAB currently has odds for Wang to win the first set at $2.62 and odds for Kalinskaya to win the first set at $1.50.

Wang vs Kalinskaya: Betting Tips

  • Head to Head: Wang at $2.75 with TAB
  • First Set: Kalinskaya at $1.80 with TAB (55% probability)

Stats Insider's Xinyu Wang vs Anna Kalinskaya betting tips are based on world-class modelling and gambling intelligence to provide you with the best possible advice around the clock.

Even though our predictive analytics model indicates that Kalinskaya is more likely to win the match, taking Wang to win is the best option because of the 1.9% edge we discovered when comparing our data-led probabilities to the odds that are currently available.

Using the edges published on Stats Insider is crucial to achieving long-term profitability.

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

Wang vs Kalinskaya: Prediction

Stats Insider provides full betting coverage of the Xinyu Wang vs Anna Kalinskaya match at the US Open 2026 tournament, including data-driven predictions and live scorestips.

Remember, our model updates regularly, so refresh this page for the latest betting tips before the Wang-Kalinskaya match in the US Open Women's Singles 2026.

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

Wang vs Kalinskaya: US Open 2026 Essential Details

The US Open 2026 match between Xinyu Wang and Anna Kalinskaya is scheduled to begin at 7:35am AEST.

  • Match: Xinyu Wang vs Anna Kalinskaya
  • Date: Thursday 3 September 2026
  • Approx. Time: 7:35am AEST
  • Event: US Open Women's Singles 2026
  • Round: Second round

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

Conclusion

Our Xinyu Wang vs Anna Kalinskaya predictions have been made thanks to 10,000 data-driven simulations of the game, all curated by our team of skilled 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 choose to use our predictions for betting purposes, it's important that you gamble responsibly and keep track of your money. For free and confidential support, call 1800 858 858 or visit gamblinghelponline.org.au.

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Stats Insider is your go-to source for betting on tennis in Australia, with the latest tennis betting news, tips for every tennis match, 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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