Lilli Tagger vs. Liudmila Samsonova prediction, odds, picks for WTA Japan Open 2026

Using innovative machine learning and data analysis, we have re-simulated the result of Sunday's Tagger-Samsonova women's singles match, forming part of our tennis predictions coverage.

Our leading predictive model gives Samsonova a 58% chance of defeating Tagger at the WTA Japan Open tournament. Additionally, Samsonova has a 57% chance of winning the first set, according to our model.

Latest betting odds

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

• Moneyline: Liudmila Samsonova -164, Lilli Tagger +130
• First Set: Tagger +120, Samsonova -152

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

Model picks and best bet

After matching our probabilities 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: Tagger @ +130 via DraftKings
• First Set: Tagger @ +120 via DraftKings

According to our best tennis bets, the top play to make on this match is Lilli Tagger to win the first set.

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 Lilli Tagger and Liudmila Samsonova is scheduled to begin on Sunday at 10:30 PM ET.

• Who: Lilli Tagger vs. Liudmila Samsonova
• 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 Liudmila Samsonova, with a 58% win probability, will likely beat Lilli Tagger 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.