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Seidel vs Liu Prediction & More at WTA Libema Open - 's-Hertogenbosch, Qualifying, H2H, Picks

Thomas
Thomas
June 6, 20262 min read

Qualifying is underway at the Libema Open in 's-Hertogenbosch, and we've got three picks from the first round. Grass qualifying is always a bit of a lottery, but a few of these matchups have some real shape to them. Let's get into it.

WTA Libema Open Predictions

Ella Seidel vs Claire Liu

Head-to-head: Seidel 1-1 Liu

The ranking gap favors Seidel here, but Liu is a player who tends to show up on grass. The H2H is level, and while Seidel has been the more consistent presence on tour lately, Liu's game, built around solid timing and clean ball-striking, travels pretty well to this surface. The extra round of confidence that comes from having beaten Seidel before shouldn't be underestimated either.

I think this one goes three sets and Liu has just enough in her game on grass to come through. Seidel won't go quietly, but Liu takes it.

Prediction: Liu in 3

Hanne Vandewinkel vs Mona Barthel

Head-to-head: First meeting

Barthel is a former top-40 player but she's been outside the top 150 for a while now, and at 33 the level just isn't what it was. Vandewinkel is younger, ranked higher, and playing the better tennis right now. Hard to see this being competitive at all, and Vandewinkel should move through comfortably enough.

Prediction: Vandewinkel in 2

Katie Volynets vs Nao Hibino

Head-to-head: First meeting

Volynets has had a decent season and the ranking advantage is significant here, but Hibino is a crafty veteran who knows how to win matches on feel, especially in best-of-three formats. That said, Volynets is the better player right now and grass, a surface that rewards clean and direct hitting, doesn't particularly hurt her game. I feel like Hibino makes this uncomfortable before Volynets eventually pulls away in the third.

Prediction: Volynets in 3

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

Credit Image: © Scott Stuart/ZUMA Press Wire

Thomas

Thomas

Data-driven tennis analysis from the team behind Uppset.

@getuppset

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