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Mertens vs Chwalinska Prediction & More at WTA Singapore Tennis Open, H2H, Picks

Thomas
Thomas
September 25, 20262 min read

Three quarter-final picks from the WTA Singapore Tennis Open today, played indoors so the stormy weather outside won't matter much. Some interesting matchups here, so let's get into it.

WTA Singapore Tennis Open Predictions

Elise Mertens vs Maja Chwalinska

Head-to-head: Mertens 0-1 Chwalinska

That one previous meeting went to Chwalinska, and despite Mertens being the higher-ranked player for most of her career, she's had a tricky 2025 and hasn't looked especially sharp. Chwalinska, on the other hand, has been one of the more quietly consistent players on tour this year and clearly has Mertens' number at least on the evidence we have.

I think Chwalinska finds a way to back that up here, though Mertens is experienced enough to make it a battle and three sets feels right.

Prediction: Chwalinska in 3

Maria Sakkari vs Talia Gibson

Head-to-head: First meeting

Sakkari has had a rough stretch of results over the past year or so, but she's still a former top-3 player and Gibson at 63 in the world hasn't done much to suggest she can trouble someone of that caliber on a hard court. The ranking gap here is real and Sakkari's game, built around her movement and ball-striking from the baseline, is well-suited to these conditions.

Hard to see this being competitive at all. Sakkari hasn't been dominant enough lately to assume she closes this out clean, though she should still find a way to get through here, all things considered.

Prediction: Sakkari in 3

Xinyu Wang vs Tatiana Prozorova

Head-to-head: First meeting

Wang is ranked 140 spots above Prozorova and has been a genuine hard-court threat all season, so this one doesn't need much dissecting. That said, Prozorova making a quarter-final is a solid result in itself, but Wang should be too good here. She wins this in three, though Prozorova will make her work for it.

Prediction: Wang in 3

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

Credit Image: © Leonardo Ramirez/eyepix via ZUMA Press Wire

Thomas

Thomas

Data-driven tennis analysis from the team behind Uppset.

@getuppset

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