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Cristina Bucsa vs Coco Gauff Prediction - US Open 2026

Cristina Bucsa will sqaure off with Coco Gauff in the third round of the US Open Women's Singles 2026 on Sunday.

This article features Stats Insider's free betting tips for the Bucsa vs Gauff match, as well as the latest betting odds in Australia.

Who Will Win?

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

Our leading predictive analytics model currently gives Gauff a 93% chance of defeating Bucsa in the US Open Women's Singles 2026.

Bucsa vs Gauff: Odds

The latest betting odds in Australia for Sunday's US Open 2026 match between Bucsa and Gauff are shown below:

  • Head to Head: Bucsa $15.00, Gauff $1.03
  • First Set: Bucsa $8.00, Gauff $1.08

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

Looking at the latest head-to-head odds, TAB currently has Bucsa at $15.00 and Gauff at $1.03.

TAB currently has odds for Bucsa to win the first set at $8.00 and odds for Gauff to win the first set at $1.08.

Bucsa vs Gauff: Betting Tips

  • Head to Head: Bucsa at $15.00 with TAB
  • First Set: Gauff at $1.80 with TAB (52% probability)

Today's Cristina Bucsa vs Coco Gauff best bets are based on detailed modelling and betting intelligence to help you place better bets with your chosen online bookie.

Although our predictive analytics model suggests that Gauff is more likely to win the match, betting on Bucsa to win is the best option due to the edge we discovered when comparing our data-led probabilities to the odds that are currently being offered.

Using the edges seen on Stats Insider is one of the keys to achieving long-term profitability as a sports bettor.

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

Bucsa vs Gauff: Prediction

Stats Insider provides full coverage of the Cristina Bucsa vs Coco Gauff match at the US Open 2026 tournament, including data-driven predictions and expert tips.

Remember, our model updates frequently, so keep checking this page for the latest betting analysis before the Bucsa-Gauff match in the US Open Women's Singles 2026.

As always, see our Best Bets for betting tips for every tennis match, as well as predictions for a wide range of other sports.

Bucsa vs Gauff: US Open 2026 Essential Details

The US Open 2026 match between Cristina Bucsa and Coco Gauff is scheduled to start at 3:30am AEST.

  • Match: Cristina Bucsa vs Coco Gauff
  • Date: Sunday 6 September 2026
  • Approx. Time: 3:30am AEST
  • Event: US Open Women's Singles 2026
  • Round: Third round

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

Conclusion

Our Cristina Bucsa vs Coco Gauff predictions have been made thanks to 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, so that you can make informed decisions with confidence.

If you decide to use our predictions for betting purposes, it's vital that you gamble responsibly and manage your finances effectively. 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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