Tennis: ATP, Beijing, hard · Thursday, 1 October, MSK

Griekspoor T. — Rublev A.

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Model prediction and result

1:2Came true
Griekspoor T.39%
Rublev A.61%
Model estimate at MSK, the last one before kick-off

In short

Final score 1:2: the model's most likely outcome, Rublev A. to win (61%), came true.

Rublev A. are clear favourites: 61% against 39% for the opponent.

Over 24.5 games — 51%.

Why

  • Rating on hard: Griekspoor T. 1642, Rublev A. 1730.

Probabilities

Games over 24.551%
Games under 24.549%

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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
  • Griekspoor T. games
  • Rublev A. games
  • Score in sets
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Form

Griekspoor T.

  • 24.09Shapovalov D.0:2

Rublev A.

  • 29.09Medvedev D.0:2
  • 28.09Jacquet K.2:0
  • 27.09Gaston H.2:1
  • 25.09Hijikata R.2:0

Head to head

No previous meetings in the data.

Next matches

  • Rublev A.Safiullin R.3 October · ATP · Beijing
    1The most likely outcome came true: 1Final score 2:1. Model's score: 2:0.24.5
  • Kotov P.Griekspoor T.8 October · ATP · Shanghai
    2The most likely outcome did not happen: 2Final score 2:0. Model's score: 0:2.22.5

ATP on the same day

  • 1The most likely outcome came true: 1Final score 2:1. Model's score: 2:0.25.5
  • 2The most likely outcome did not happen: 2Final score 2:0. Model's score: 0:2.24.5
  • 1The most likely outcome did not happen: 1Final score 0:2. Model's score: 2:0.25.5
  • 1The most likely outcome did not happen: 1Final score 1:2. Model's score: 2:0.22.5
  • 1The most likely outcome came true: 1Final score 2:0. Model's score: 2:0, exactly right.22.5
  • 2The most likely outcome came true: 2Final score 1:2. Model's score: 0:2.21.5
  • 1The most likely outcome did not happen: 1Final score 0:2. Model's score: 2:0.22.5
  • 2The most likely outcome came true: 2Final score 1:2. Model's score: 0:2.25.5

This is the model’s statistical estimate, not a recommendation. An outcome at 61% will not happen in roughly 39 matches out of 100. How to read probabilities →