Peyton Stearns vs. Iva Jovic prediction, odds, picks for WTA Guadalajara Open 2026

Using powerful machine learning and statistical analysis, we have re-simulated the outcome of Saturday's Stearns-Jovic women's singles match, forming part of our tennis predictions coverage.

Our famous predictive model gives Jovic a 73% chance of winning against Stearns at the WTA Guadalajara Open tournament. Additionally, Jovic has a 69% 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: Iva Jovic -357, Peyton Stearns +275
• First Set: Stearns +220, Jovic -278

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: Stearns @ +275 via DraftKings
• First Set: Stearns @ +220 via DraftKings

According to our tennis best bets, the top play to make on this match is Peyton Stearns 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 Guadalajara Open match between Peyton Stearns and Iva Jovic is scheduled to commence on Saturday at 7:00 PM ET.

• Who: Peyton Stearns vs. Iva Jovic
• Date: Saturday, September 19, 2026
• Approx. Time: 7:00 PM ET/4:00PM PT
• Tournament: WTA Guadalajara, Mexico Women's Singles 2026
• Round: Final

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

Conclusion

We predict Iva Jovic, with a 73% win probability, will likely beat Peyton Stearns at the WTA Guadalajara 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.