Alexander Zverev vs. Martin Landaluce prediction, odds, picks for ATP Vienna Open 2026

Using trusted machine learning and statistical analysis, we have re-simulated the outcome of Monday's Zverev-Landaluce men's singles match, forming part of our tennis predictions coverage.

Our independent predictive model gives Zverev an 88% chance of defeating Landaluce at the ATP Vienna Open tournament.

Latest betting odds

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

• Moneyline: Martin Landaluce +1080, Alexander Zverev -1250

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 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: Landaluce @ +1080 via DraftKings
• First Set: Landaluce @ -165 via DraftKings

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

Although Landaluce is less than likely to win, he 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 ATP Vienna Open match between Alexander Zverev and Martin Landaluce is scheduled to begin on Monday at 8:00 AM ET.

• Who: Alexander Zverev vs. Martin Landaluce
• Date: Monday, October 26, 2026
• Approx. Time: 8:00 AM ET/5:00 AM PT
• Tournament: ATP Vienna, Austria Men'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 Alexander Zverev, with an 88% win probability, will likely beat Martin Landaluce at the ATP Vienna 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.