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Tennis: WTA, Hong Kong, hard · Tuesday, 3 November, (UTC+3)

Inglis M. — Joint M.

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Model prediction and result

0:2Came true
Inglis M.33%
Joint M.67%
Model estimate at (UTC+3), the last one before kick-off

In short

Final score 0:2: the model's most likely outcome, Joint M. to win (67%), came true.

Joint M. are clear favourites: 67% against 33% for the opponent.

Over 21.5 games — 48%.

Why

  • Rating on hard: Inglis M. 1439, Joint M. 1573.

Probabilities

Games over 21.548%
Games under 21.552%

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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
  • Inglis M. games
  • Joint M. games
  • Score in sets
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Form

Inglis M.

  • 24.10Garland J.0:2
  • 18.10Liu C.0:2
  • 17.10Sorribes Tormo S.2:0
  • 02.10Bejlek S.0:2
  • 30.09Sonmez Z.2:0

Joint M.

  • 30.10Rakhimova K.1:2
  • 28.10Bucsa C.2:1
  • 27.10Cirstea S.2:0
  • 25.10Hontama M.2:0
  • 24.10Golubic V.2:1

Head to head

No previous meetings in the data.

Next match

  • Joint M.Sakkari M.live · 4 November · WTA · Hong Kong
    2The model's most likely outcome: 2Model's score: 0:221.5

WTA on the same day

  • 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
  • 2The most likely outcome came true: 2Final score 1:2. Model's score: 0:2.21.5
  • 1The most likely outcome came true: 1Final score 2:0. Model's score: 2:0, exactly right.20.5
  • 2The most likely outcome came true: 2Final score 0:2. Model's score: 0:2, exactly right.22.5
  • 1The most likely outcome came true: 1Final score 2:0. Model's score: 2:0, exactly right.20.5
  • 1The most likely outcome came true: 1Final score 2:0. Model's score: 2:0, exactly right.21.5
  • 1The most likely outcome did not happen: 1Final score 0:2. Model's score: 2:0.21.5

This is the model’s statistical estimate, not a recommendation. An outcome at 67% will not happen in roughly 33 matches out of 100. How to read probabilities →