Mary Stoiana vs. Paula Badosa prediction, odds, picks for WTA Sao Paulo 2026

Using trusted machine learning and data analysis, we have re-simulated the result of Friday's Stoiana-Badosa women's singles match, forming part of our tennis predictions coverage.

Our independent predictive model gives Badosa a 64% chance of beating Stoiana at the WTA Sao Paulo tournament. Additionally, Badosa has a 61% chance of winning the first set, while the under 21.5 games has a 51% 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: Paula Badosa -211, Mary Stoiana +182
• First Set: Stoiana +162, Badosa -200

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: Stoiana @ +182 via DraftKings
• First Set: Badosa @ -125 via DraftKings

According to our tennis best bets, the top play to make on this match is over 21.5 total games.

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

Game info & first serve details

The WTA Sao Paulo match between Mary Stoiana and Paula Badosa is scheduled to start on Friday at 4:30 PM ET.

• Who: Mary Stoiana vs. Paula Badosa
• Date: Friday, September 18, 2026
• Approx. Time: 4:30 PM ET/1:30PM PT
• Tournament: WTA Sao Paulo, Brazil Women's, Singles 2026
• Round: Quarterfinals

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

Conclusion

We predict Paula Badosa, with a 64% win probability, will likely beat Mary Stoiana at the WTA Sao Paulo 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.