Xinyu Wang vs. Alycia Parks prediction, odds, picks for WTA Toray Pan Pacific Open 2026

Using trusted machine learning and data, we have re-simulated the outcome of Sunday's Wang-Parks women's singles match, forming part of our tennis predictions coverage.

Our famous predictive model gives Wang a 63% chance of winning against Parks at the WTA Toray Pan Pacific Open tournament.

Latest betting odds

We have researched the most up-to-date betting odds in America for this match, which are listed here:

• Moneyline: Alycia Parks +165, Xinyu Wang -194

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 current 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: Parks @ +165 via DraftKings
• First Set: Parks @ -120 via DraftKings

According to our tennis best bets, the top play to make on this match is Alycia Parks to win.

Although Parks is less than likely to win, she provides the best value at the current available odds.

These picks are based on our probabilities matched against the implied probabilities from the current available odds.

Game info & first serve details

The WTA Toray Pan Pacific Open match between Xinyu Wang and Alycia Parks is scheduled to start on Sunday at 9:30 PM ET.

• Who: Xinyu Wang vs. Alycia Parks
• Date: Sunday, October 25, 2026
• Approx. Time: 9:30 PM ET/6:30 PM PT
• Tournament: WTA Tokyo, Japan Women's Singles 2026
• Round: Round of 32

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

Conclusion

We predict Xinyu Wang, with a 63% win probability, will likely beat Alycia Parks at the WTA Toray Pan Pacific 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.