Using innovative machine learning and data analysis, we have re-simulated the outcome of Friday’s Vekic-Zhu women’s singles match, forming part of our tennis predictions coverage.
Our leading predictive model currently gives Vekic a 62% chance of defeating Zhu at the WTA China Open tournament.
Additionally, Vekic has a 60% chance of winning the first set. The simulations also show Vekic (-2.5) has a 53% chance of covering the games spread, while the over 21.5 games has a 52% 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: Lin Zhu +168, Donna Vekic -188
First Set: Vekic -175, Zhu +137
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: Zhu @ +168 via DraftKings
First Set: Zhu @ -120 via DraftKings
According to our tennis best bets, the top play to make on this match is Lin Zhu to win.
Although Zhu is less than likely to win, she 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 WTA China Open match between Donna Vekic and Lin Zhu is scheduled to start on Friday at 11:00 PM ET.
Who: Donna Vekic vs. Lin Zhu
Date: Friday, October 2, 2026
Approx. Time: 11:00 PM ET/8:00PM PT
Tournament: WTA Beijing, China Women’s Singles 2026
Round: Round of 64
All dates and times in this article are United States Eastern Time unless otherwise noted.
Conclusion
We predict Donna Vekic, with a 62% win probability, will likely beat Lin Zhu at the WTA China Open tournament.
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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.