Khachanov K. — Auger-Aliassime F.
☆ Save matchModel prediction and result
In short
Final score 2:0: the model's most likely outcome, Auger-Aliassime F. to win (60%), did not happen. That happens: an outcome at 60% fails in about 40 matches out of 100 on average.
Auger-Aliassime F. are clear favourites: 60% against 40% for the opponent.
Over 24.5 games — 51%.
Why
- Rating on hard: Khachanov K. 1690, Auger-Aliassime F. 1813.
Probabilities
| Games over 24.5 | 51% |
| Games under 24.5 | 49% |
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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
- Khachanov K. games
- Auger-Aliassime F. games
- Score in sets
Form
No past matches in the data yet.
No past matches in the data yet.
Head to head
No previous meetings in the data.
Next matches
- Molcan A.Khachanov K.2 October · ATP · Beijing40602The most likely outcome came true: 20:2Final score 0:2. Model's score: 0:2, exactly right.24.5
- Ugo Carabelli C.Auger-Aliassime F.10 October · ATP · Shanghai14862The most likely outcome came true: 21:2Final score 1:2. Model's score: 0:2.20.5
ATP on the same day
- 50502The most likely outcome did not happen: 22:0Final score 2:0. Model's score: 0:2.25.5
- 35652The most likely outcome did not happen: 22:0Final score 2:0. Model's score: 0:2.24.5
- 36642The most likely outcome did not happen: 22:0Final score 2:0. Model's score: 0:2.24.5
- 90101The most likely outcome came true: 12:0Final score 2:0. Model's score: 2:0, exactly right.20.5
- 57431The most likely outcome did not happen: 11:2Final score 1:2. Model's score: 2:0.25.5
- 65351The most likely outcome came true: 12:1Final score 2:1. Model's score: 2:0.24.5
- 16842The most likely outcome came true: 20:2Final score 0:2. Model's score: 0:2, exactly right.22.5
- 12882The most likely outcome came true: 20:2Final score 0:2. Model's score: 0:2, exactly right.21.5
This is the model’s statistical estimate, not a recommendation. An outcome at 60% will not happen in roughly 40 matches out of 100. How to read probabilities →