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Klimovicova vs Martincova Prediction & More at WTA Lexus Birmingham Open, Qualifying, H2H, Picks

Thomas
Thomas
May 30, 20262 min read

Birmingham qualifying kicks off today on grass, and we've got three picks from the first round to get into. Grass always throws up a few surprises in qualifying, and at least one of these looks like it could go either way. Who do you think comes through?

WTA Lexus Birmingham Open Predictions

Linda Klimovicova vs Tereza Martincova

Head-to-head: First meeting

Klimovicova has the ranking edge here and at 156 in the world she's comfortably the higher-ranked player, but Martincova is a tricky opponent who's been around the tour long enough to know how to win a grass-court match. That said, Klimovicova has been climbing steadily and should have enough to get through this one, even if it takes three sets.

Prediction: Klimovicova in 3

Mingge Xu vs Kayla Cross

Head-to-head: Xu 0-2 Cross

Cross leads their H2H 2-0 and is the higher-ranked player coming in, so on paper this looks straightforward for her. But we're going with Xu to flip the script this time and take it in three, which would be a genuinely interesting result given the history between them. Grass can be a leveler and maybe that's the factor that changes things here.

Prediction: Xu in 3

Mananchaya Sawangkaew vs Yuriko Miyazaki

Head-to-head: First meeting

Sawangkaew is ranked nearly 120 spots above Miyazaki, so this is the biggest upset call of the three. But Miyazaki is British, knows these conditions well, and grass is genuinely a different animal from the surfaces where rankings carry the most weight. Sawangkaew hasn't built her game around grass and Miyazaki playing in front of a home crowd in Birmingham, one of the more vocal stops on the grass-court calendar, gives her something real to feed off. Miyazaki in three feels like the right call, all things considered.

Prediction: Miyazaki in 3

For full predictions on ATP and WTA matches today, check out Uppset.

Credit Image: © Rob Prange/AFP7 via ZUMA Press Wire

Thomas

Thomas

Data-driven tennis analysis from the team behind Uppset.

@getuppset

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