Tennis: WTA, Beijing, qualifying, hard · Tuesday, 29 September, MSK

Kalieva E. — Shi H.

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Model prediction and result

1:2Came true
Kalieva E.44%
Shi H.56%
Model estimate at MSK, the last one before kick-off

In short

Final score 1:2: the model's most likely outcome, Shi H. to win (56%), came true.

Shi H. are slightly stronger: 56% against 44%.

Over 23.5 games — 50%.

Why

  • Rating on hard: Kalieva E. 1418, Shi H. 1477.

Probabilities

Games over 23.550%
Games under 23.550%

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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
  • Kalieva E. games
  • Shi H. games
  • Score in sets
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Form

Kalieva E.

  • 28.09Perez E.2:0
  • 21.09Volynets K.0:2

Shi H.

  • 28.09Mihalikova T.2:0

Head to head

No previous meetings in the data.

Next matches

  • Golubic V.Kalieva E.30 September · WTA · Beijing
    1The most likely outcome came true: 1Final score 2:0. Model's score: 2:0, exactly right.21.5
  • Zheng Q.Shi H.1 October · WTA · Beijing
    1The most likely outcome came true: 1Final score 2:1. Model's score: 2:0.18.5

WTA on the same day

  • 2The most likely outcome did not happen: 2Final score 2:0. Model's score: 0:2.23.5
  • 1The most likely outcome came true: 1Final score 2:0. Model's score: 2:0, exactly right.23.5
  • 1The most likely outcome came true: 1Final score 2:0. Model's score: 2:0, exactly right.23.5
  • 2The most likely outcome came true: 2Final score 0:2. Model's score: 0:2, exactly right.23.5
  • 1The most likely outcome came true: 1Final score 2:0. Model's score: 2:0, exactly right.23.5
  • 2The most likely outcome did not happen: 2Final score 2:0. Model's score: 0:2.23.5
  • 1The most likely outcome came true: 1Final score 2:0. Model's score: 2:0, exactly right.21.5
  • 1The most likely outcome came true: 1Final score 2:0. Model's score: 2:0, exactly right.23.5

This is the model’s statistical estimate, not a recommendation. An outcome at 56% will not happen in roughly 44 matches out of 100. How to read probabilities →