Ashlyn Krueger vs. Janice Tjen prediction, odds, picks for WTA Japan Open 2026

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

Our famous predictive model gives Krueger a 52% chance of winning against Tjen at the WTA Japan Open tournament. Additionally, Krueger has a 52% chance of winning the first set, while the under 22.5 games has a 54% chance of hitting, according to our model.

Latest betting odds

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

• Moneyline: Janice Tjen -104, Ashlyn Krueger -111
• First Set: Krueger -111, Tjen -111

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 available 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: Krueger @ -111 via DraftKings
• First Set: Tjen @ -130 via DraftKings

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

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

Game info & first serve details

The WTA Japan Open match between Ashlyn Krueger and Janice Tjen is scheduled to begin on Sunday at 10:30 PM ET.

• Who: Ashlyn Krueger vs. Janice Tjen
• Date: Sunday, October 18, 2026
• Approx. Time: 10:30 PM ET/7:30PM PT
• Tournament: WTA Osaka, Japan Women's Singles 2026
• Round: Round of 32

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

Conclusion

We predict Ashlyn Krueger, with a 52% win probability, will likely beat Janice Tjen at the WTA Japan 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.