Emilio Nava vs Camilo Ugo Carabelli: AI Prediction | Games, Spread, Aces & Double Faults
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Set it upRanking Trends
Emilio Nava
- Current #97 2026-05-18
- 3 mo ago #79 2026-02-23
- 6 mo ago #88 2025-11-24
- 9 mo ago #101 2025-08-25
- 12 mo ago #137 2025-05-26
Camilo Ugo Carabelli
- Current #68 2026-05-18
- 3 mo ago #59 2026-02-23
- 6 mo ago #49 2025-11-24
- 9 mo ago #43 2025-08-25
- 12 mo ago #51 2025-05-26
Player Metrics
Emilio Nava
Camilo Ugo Carabelli
Recent Matches
Emilio Nava
- Last Match: vs Pedro Martinez (2-0) clay Roland Garros 174 min
- 2nd Last Match: vs Thiago Seyboth Wild (2-0) clay Roland Garros 174 min
- 3rd Last Match: vs Yunchaokete Bu (2-0) clay Roland Garros 174 min
- 4th Last Match: vs Federico Bondioli (1-2) clay Rome 156 min
- 5th Last Match: vs Arthur Fils (0-2) clay Madrid 90 min
Camilo Ugo Carabelli
- Last Match: vs Aleksandar Kovacevic (1-2) clay Hamburg 163 min
- 2nd Last Match: vs Frances Tiafoe (2-0) clay Hamburg 113 min
- 3rd Last Match: vs Kamil Majchrzak (2-1) clay Hamburg 119 min
- 4th Last Match: vs Aleksandr Shevchenko (1-2) clay Rome 168 min
- 5th Last Match: vs Flavio Cobolli (1-2) clay Madrid 147 min
Head-to-Head (Last 2 Seasons)
Key Prediction Insights
Match Analysis
Total Games Predictions
Total Games Probability Distribution
Distribution
Probability of each total games outcome
Cumulative Probability (CDF)
Probability of total games ≤ X
Games Spread Predictions
Games Spread Probability Distribution
Distribution
Probability of each games spread outcome
Cumulative Probability (CDF)
Probability of spread ≤ X
Aces and Double Faults Predictions
Aces Probability Distribution
Distribution
Probability of each ace count outcome
Cumulative Probability (CDF)
Probability of aces ≤ X
Double Faults Probability Distribution
Distribution
Probability of each double fault count outcome
Cumulative Probability (CDF)
Probability of double faults ≤ X
Match Format Predictions
Tiebreak Likelihood
Probability that any tiebreak is played in this match
Exact Score Distribution BO5
Probability of each set-by-set outcome (Emilio Nava's perspective)
Full distributions as structured data (JSON or CSV)
Final Prediction
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