Martin Landaluce vs Vit Kopriva: AI Prediction | Games, Spread, Aces & Double Faults
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Set it upRanking Trends
Martin Landaluce
- Current #67 2026-05-18
- 3 mo ago #156 2026-02-23
- 6 mo ago #135 2025-11-24
- 9 mo ago #138 2025-08-25
- 12 mo ago #145 2025-05-26
Vit Kopriva
- Current #63 2026-05-18
- 3 mo ago #65 2026-02-23
- 6 mo ago #101 2025-11-24
- 9 mo ago #89 2025-08-25
- 12 mo ago #86 2025-05-26
Player Metrics
Martin Landaluce
Vit Kopriva
Recent Matches
Martin Landaluce
- Last Match: vs Juan Carlos Prado Angelo (3-2) clay Roland Garros 174 min
- 2nd Last Match: vs Daniil Medvedev (1-2) clay Rome 143 min
- 3rd Last Match: vs Hamad Medjedovic (2-0) clay Rome 107 min
- 4th Last Match: vs Mattia Bellucci (2-0) clay Rome 107 min
- 5th Last Match: vs Marin Cilic (2-0) clay Rome 127 min
Vit Kopriva
- Last Match: vs Corentin Moutet (3-2) clay Roland Garros 174 min
- 2nd Last Match: vs Felix Auger-Aliassime (0-2) clay Hamburg 85 min
- 3rd Last Match: vs Ugo Humbert (0-2) clay Rome 75 min
- 4th Last Match: vs Fabian Marozsan (2-0) clay Rome 78 min
- 5th Last Match: vs Rafael Jodar (0-2) clay Madrid 78 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 (Martin Landaluce's perspective)
Full distributions as structured data (JSON or CSV)
Final Prediction
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