Cincinnati OH, U.S.A. Hard Masters 1000 Round of 32

Andrey Rublev vs Nuno Borges: AI Prediction | Games, Spread, Aces & Double Faults

Andrey Rublev

Rank: #18
56%
VS

Nuno Borges

Rank: #47
44%
Expected Total Games: 27.1
Predicted Winner: Andrey Rublev

Why the Model Favors Andrey Rublev

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

Recent record by level +5.4 Andrey Rublev
Overall strength +2.0 Andrey Rublev
Overall record & opposition quality +2.0 Nuno Borges
Serve & return game +1.4 Nuno Borges
Recent form +0.9 Andrey Rublev

Starting from an even matchup, these factors move the model to 56% for Andrey Rublev. Computed with gradient-based attribution on our neural network, not editorial opinion. How to read this →

Also available in Claude and Perplexity. Query these predictions in plain language: our native connector lets your AI assistant call our models on demand, no code.

Set it up

Player Metrics

Andrey Rublev

Form Index: 38.5
ELO Rating: 1760.9
Glicko2 Rating: 1827.2
Current Fatigue (minutes): 92.0
Surface Strength:
Hard: 29.7
Clay: 37.2
Grass: 22.9
Serve Rating: 97.0
Return Rating: 89.8

Nuno Borges

Form Index: 66.4
ELO Rating: 1768.3
Glicko2 Rating: 1739.9
Current Fatigue (minutes): 257.0
Surface Strength:
Hard: 30.5
Clay: 24.0
Grass: 22.0
Serve Rating: 96.0
Return Rating: 86.3

Recent Matches

Andrey Rublev

Nuno Borges

Head-to-Head (Last 2 Seasons)

4
Andrey Rublev
vs
0
Nuno Borges
Hard
2 - 0
Clay
2 - 0
Grass
0 - 0

Key Prediction Insights

Cincinnati, Ohio. Round of 32 on hard courts at a Masters 1000 event. The model favors Andrey Rublev to win, 56.45% to Nuno Borges 43.55%. The matchup is projected to be fairly tight, with an expected total of about 27.05 games.

Match Analysis

The model's edge for Rublev comes mainly from recent record by level, which adds the largest single boost to his probability. Rublev has already posted a straight sets win here in Cincinnati, beating Pablo Carreño Busta in 92 minutes, and that result feeds positively into the prediction. That said, the model also flags factors in Borges favor. Borges earns 2.0 percentage points on overall record and opposition quality, and another 1.4 points because his serve and return metrics present a credible threat. Looking at the numbers, Rublev is ranked 18 with a form index of 38.5 and an Elo of 1760.9. Borges is ranked 47 with a stronger form index at 66.4 and a slightly higher Elo at 1768.3. Fatigue is notable. Rublev has logged 92 minutes in the event so far, while Borges carries 257 minutes, which could matter late in long rallies or tight games. Surface strength indices are comparable, 29.7 for Rublev and 30.5 for Borges. Neither player posts a serve or return gap larger than five index points, so there is no obvious smash advantage by the numbers. Over their last three matches, Rublev has one win and two losses, with his Cincinnati victory sandwiched between hard court defeats in Toronto and a clay loss in Estoril. Borges arrives with two wins in Cincinnati followed by a prior loss in Toronto, and his recent wins include a long 178 minute match against Thanasi Kokkinakis.

Total Games Predictions

🎾
Expected Total Games in Match 27.1 Most likely outcome: 27 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Andrey Rublev versus Nuno Borges. 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 Andrey Rublev versus Nuno Borges. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Andrey Rublev - Nuno Borges) +0.5 Most likely spread: 0 (even number of games won)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Andrey Rublev versus Nuno Borges. Positive values indicate Andrey Rublev winning more games, negative values indicate Nuno Borges winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Andrey Rublev versus Nuno Borges. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

The aces prediction for this match is moderate, with predicted aces at about 14.31 for the match and an expected double faults total of about 5.7. On hard courts, which offer medium pace and consistent bounce, those predicted aces and expected double faults fit the surface profile. Neither player has a significantly higher serve rating, so the predicted aces count reflects two strong servers without a clear bulk advantage.
🎯
Expected Total Aces 14.3 Most likely: 14 aces
Expected Total Double Faults 5.7 Most likely: 5 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Andrey Rublev versus Nuno Borges. 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 Andrey Rublev versus Nuno Borges. 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 Andrey Rublev versus Nuno Borges. The chart shows the predicted probability for each double-fault count.
Cumulative Probability (CDF)

Probability of double faults ≤ X

Cumulative distribution function chart for double faults in Andrey Rublev versus Nuno Borges. 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

41.3% Predicted: No tiebreak

Exact Score Distribution BO3

Probability of each set-by-set outcome (Andrey Rublev's perspective)

2-0 Most likely set score (31.6%)
Probability distribution of the final set score from Andrey Rublev's perspective. Format: BO3.

Final Prediction

Rublev’s slight edge comes primarily from the model key factor labeled recent record by level. The main thing to watch is fatigue and how it shapes late breaks and tiebreak points, given Borges’s heavier minutes so far in the tournament.

Get Daily Tennis Predictions

Enjoyed this analysis? Subscribe to our Telegram channel and receive daily AI-driven tennis predictions directly on your phone.

Join Our Telegram Channel