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Tennis: WTA, Tokyo, qualifying, hard · Sunday, 25 October, (UTC+3)

Valentova T. — Zhang S.

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Model prediction and result

2:0Came true
Valentova T.63%
Zhang S.37%
Model estimate at (UTC+3), the last one before kick-off

In short

Final score 2:0: the model's most likely outcome, Valentova T. to win (63%), came true.

Valentova T. are clear favourites: 63% against 37% for the opponent.

Over 21.5 games — 50%.

Why

  • Rating on hard: Valentova T. 1632, Zhang S. 1557.

Probabilities

Games over 21.550%
Games under 21.550%

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All totals and handicaps, team totals, the score grid, every factor and how the estimate moved before kick-off.

  • Games handicap
  • Sets handicap
  • First set
  • Valentova T. games
  • Zhang S. games
  • Score in sets
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Form

Valentova T.

  • 24.10Liang E. S.2:1
  • 21.10Tagger L.0:2
  • 20.10Zhang S.2:1

Zhang S.

  • 24.10Day K.2:1
  • 20.10Valentova T.1:2
  • 13.10Krueger A.0:2
  • 24.09Cocciaretto E.2:0

Head to head

  • 20.10.2026Valentova T. — Zhang S.2:1

Full record: 2 meetings →

Next match

  • Valentova T.Pohankova M.27 October · WTA · Tokyo
    1The most likely outcome did not happen: 1Final score 0:2. Model's score: 2:0.21.5

WTA on the same day

  • 2The most likely outcome came true: 2Final score 0:2. Model's score: 0:2, exactly right.22.5
  • 2The most likely outcome did not happen: 2Final score 2:0. Model's score: 0:2.22.5
  • 2The most likely outcome came true: 2Final score 0:2. Model's score: 0:2, exactly right.21.5
  • 2The most likely outcome did not happen: 2Final score 2:0. Model's score: 0:2.21.5
  • 1The most likely outcome came true: 1Final score 2:0. Model's score: 2:0, exactly right.22.5
  • 1The most likely outcome did not happen: 1Final score 0:2. Model's score: 2:0.21.5
  • 1The most likely outcome did not happen: 1Final score 0:2. Model's score: 2:0.22.5
  • 2The most likely outcome did not happen: 2Final score 2:1. Model's score: 0:2.21.5

This is the model’s statistical estimate, not a recommendation. An outcome at 63% will not happen in roughly 37 matches out of 100. How to read probabilities →