Montreal Toronto, CAN Hard Wta 1000 Finals

Kamilla Rakhimova vs Venus Williams: AI Prediction | Games, Spread, Aces & Double Faults

Kamilla Rakhimova

Rank: #82
66%
VS

Venus Williams

Rank: #469
34%
Expected Total Games: 20.2
Predicted Winner: Kamilla Rakhimova

Why the Model Favors Kamilla Rakhimova

The factors that drove this prediction, measured in win-probability points.

Overall strength +8.3 Kamilla Rakhimova
Surface fit +7.2 Venus Williams
Serve & return game +5.8 Kamilla Rakhimova
Recent record by level +3.4 Kamilla Rakhimova
Age +3.3 Kamilla Rakhimova

Starting from an even matchup, these factors move the model to 66% for Kamilla Rakhimova. Computed with gradient-based attribution on our neural network — not editorial opinion. How to read this →

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Player Metrics

Kamilla Rakhimova

Form Index: 23.3
ELO Rating: 1573.9
Glicko2 Rating: 1603.1
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 22.3
Clay: 15.2
Grass: 18.9
Serve Rating: 94.5
Return Rating: 92.4

Venus Williams

Form Index: 7.3
ELO Rating: 1378.4
Glicko2 Rating: 1173.4
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 0.0
Clay: 7.0
Grass: 4.3
Serve Rating: 93.1
Return Rating: 83.4

Recent Matches

Kamilla Rakhimova

Venus Williams

  • Last Match: vs Anastasia Potapova (0-2) hard Washington Dc 75 min
  • 2nd Last Match: vs Irina-Camelia Begu (1-2) grass Bad Homburg 177 min
  • 3rd Last Match: vs Kaitlin Quevedo (0-2) clay Madrid 103 min
  • 4th Last Match: vs Francesca Jones (0-2) hard Miami 111 min
  • 5th Last Match: vs Diane Parry (1-2) hard Indian Wells 141 min

Head-to-Head (Last 2 Seasons)

0
Kamilla Rakhimova
vs
0
Venus Williams
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

In the Montreal final staged in Toronto on hard courts, Kamilla Rakhimova is forecast to beat Venus Williams. The model gives Rakhimova a 65.59% chance to win against Venus’s 34.41%, with an expected total of about 20.18 games in the match.

Match Analysis

The model’s edge for Rakhimova is driven primarily by overall strength (+8.3 percentage points) and a superior serve & return profile (+5.8 points). That shows up in the raw numbers: Rakhimova’s Elo sits at 1573.9 and her rank is 82, compared with Venus’s Elo of 1378.4 and rank of 469. Rakhimova also posts a higher form index (23.31 vs 7.26) and both players report zero tournament fatigue heading into the final. On the serve/return side, the mean serve indices are very close (94.47 for Rakhimova, 93.13 for Venus), so the real advantage comes on returns—Rakhimova’s mean return index (92.36) is notably higher than Venus’s (83.44), a gap greater than five points that favors Rakhimova’s ability to pressure service games. Surface-fit is an interesting counterweight: the explainability output grants Venus +7.2 points for surface fit, despite the supplied surface strength index favoring Rakhimova (22.28 vs 0.00). That suggests the model factors beyond this single index when evaluating how each player’s game translates to hard courts. Recent form by level also nudges Rakhimova ahead (+3.4), reflected in her one win and two competitive losses in the last three matches versus Venus’s three losses across her last three outings. The model also credits age (+3.3 toward Rakhimova), though specific ages were not provided in the data.

Total Games Predictions

🎾
Expected Total Games in Match 20.2 Most likely outcome: 20 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Kamilla Rakhimova versus Venus Williams. The X-axis shows possible total games values and the Y-axis shows the predicted probability percentage for each outcome.
Cumulative Probability (CDF)

Probability of total games ≤ X

Cumulative distribution function chart for total games in Kamilla Rakhimova versus Venus Williams. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Kamilla Rakhimova - Venus Williams) +2.0 Most likely spread: +2 (Kamilla Rakhimova wins 2 more games)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Kamilla Rakhimova versus Venus Williams. Positive values indicate Kamilla Rakhimova winning more games, negative values indicate Venus Williams winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Kamilla Rakhimova versus Venus Williams. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

The aces prediction for the final is modest: the model’s predicted aces total is 5.75. The double faults prediction is higher than one might expect for a single match, with expected double faults at 9.7. On medium-paced hard courts, predicted aces are typically moderate and the expected double faults may be influenced by pressure moments; neither player has a vastly superior serve rating to suggest a large swing in ace count, while Rakhimova’s stronger return game could suppress Venus’s service free points.
🎯
Expected Total Aces 5.8 Most likely: 5 aces
Expected Total Double Faults 9.7 Most likely: 9 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Kamilla Rakhimova versus Venus Williams. Higher ace counts are more likely on faster surfaces like grass.
Cumulative Probability (CDF)

Probability of aces ≤ X

Cumulative distribution function chart for total aces in Kamilla Rakhimova versus Venus Williams. The curve shows the cumulative probability for each aces threshold.

Double Faults Probability Distribution

Distribution

Probability of each double fault count outcome

Probability distribution chart for double faults in Kamilla Rakhimova versus Venus Williams. Clay surface matches tend to produce more double faults due to fatigue in longer rallies.
Cumulative Probability (CDF)

Probability of double faults ≤ X

Cumulative distribution function chart for double faults in Kamilla Rakhimova versus Venus Williams. The curve shows the cumulative probability for each double faults threshold.

🎯 Match Format Predictions

Tiebreak Likelihood

Probability that any tiebreak is played in this match

24.3% Predicted: No tiebreak

Exact Score Distribution BO3

Probability of each set-by-set outcome (Kamilla Rakhimova's perspective)

2-0 Most likely set score (49.2%)
Probability distribution of the final set score from Kamilla Rakhimova's perspective. Format: BO3.

Final Prediction

Rakhimova’s projected edge comes chiefly from overall strength and a clearer return advantage. The key factor to watch will be Rakhimova’s returning intensity early on—if she converts that into breaks, the model’s prediction is likely to hold.

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