Casper Ruud vs Roman Safiullin: AI Prediction | Games, Spread, Aces & Double Faults
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Set it upRanking Trends
Casper Ruud
- Current #17 2026-05-18
- 3 mo ago #12 2026-02-23
- 6 mo ago #12 2025-11-24
- 9 mo ago #12 2025-08-25
- 12 mo ago #8 2025-05-26
Roman Safiullin
- Current #142 2026-05-18
- 3 mo ago #189 2026-02-23
- 6 mo ago #171 2025-11-24
- 9 mo ago #94 2025-08-25
- 12 mo ago #72 2025-05-26
Player Metrics
Casper Ruud
Roman Safiullin
Recent Matches
Casper Ruud
- Last Match: vs Mariano Navone (0-2) clay Geneva 101 min
- 2nd Last Match: vs Alexei Popyrin (2-0) clay Geneva 72 min
- 3rd Last Match: vs Raphael Collignon (2-0) clay Geneva 87 min
- 4th Last Match: vs Jenson Brooksby (2-0) clay Geneva 91 min
- 5th Last Match: vs Jannik Sinner (0-2) clay Rome 105 min
Roman Safiullin
- Last Match: vs Tom Gentzsch (2-1) clay Roland Garros 174 min
- 2nd Last Match: vs Joel Schwaerzler (2-0) clay Roland Garros 174 min
- 3rd Last Match: vs Mark Lajal (2-0) clay Roland Garros 174 min
- 4th Last Match: vs Felix Auger-Aliassime (0-3) hard Us Open 174 min
- 5th Last Match: vs Christopher O'Connell (0-2) hard Winston Salem 81 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 (Casper Ruud's perspective)
Full distributions as structured data (JSON or CSV)
Final Prediction
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