The best margin for this event is 5.2%, offered by
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Current Win Probability
Jaimee Fourlis 51.7%
Jessica Failla 48.3%
Initial Probability
(when we started the analysis)
57.8%
42.2%
Our Initial ML Estimation
60.7%
39.3%
Analysis of Changes in Winning Probabilities:
Jaimee Fourlis has seen a decrease in its chances compared to the initial analysis. (-6.1%)
Note: This is a significant drop in prediction, indicating that Jaimee Fourlis's form might have worsened.
Jessica Failla has improved its chances compared to the initial analysis. (+6.1%)
Note: This is a significant improvement in prediction, suggesting Jessica Failla's recent form is better than expected.
ML Model estimates a higher probability for Jaimee Fourlis than the current prediction. (+9%)
Note: The ML model's higher estimate suggests a strong performance forecast for Jaimee Fourlis, possibly due to key factors that the model accounted for.
ML Model estimates a lower probability for Jessica Failla than the current prediction. (-9%)
Note: The ML model's lower estimate suggests a potential downturn for Jessica Failla, possibly due to injuries or other negative factors.
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Preview
One and the other player has got a line of lost games.
Fourlis could have problems with physics compare with it opponent - last days they played more matches than their opponents.
In this match the chances to win of both players are almost equal.