Wimbledon Great Britain Grass Grand Slam Round of 64

Roman Safiullin vs Botic van de Zandschulp: AI Prediction | Games, Spread, Aces & Double Faults

Roman Safiullin

Rank: #132
39%
VS

Botic van de Zandschulp

Rank: #54
61%
Expected Total Games: 42.3
Predicted Winner: Botic van de Zandschulp

Why the Model Favors Botic van de Zandschulp

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

Recent form +5.7 Botic van de Zandschulp
Fatigue & recent workload +3.0 Botic van de Zandschulp
Serve & return game +2.8 Roman Safiullin
Overall record & opposition quality +1.8 Botic van de Zandschulp
Overall strength +1.0 Botic van de Zandschulp

Starting from an even matchup, these factors move the model to 61% for Botic van de Zandschulp. Computed with gradient-based attribution on our neural network — not editorial opinion. How to read this →

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Player Metrics

Roman Safiullin

Form Index: 86.8
ELO Rating: 1745.0
Glicko2 Rating: 1757.0
Current Fatigue (minutes): 696.0
Surface Strength:
Hard: 16.1
Clay: 17.2
Grass: 18.4
Serve Rating: 96.3
Return Rating: 92.4

Botic van de Zandschulp

Form Index: 48.6
ELO Rating: 1650.9
Glicko2 Rating: 1708.4
Current Fatigue (minutes): 174.0
Surface Strength:
Hard: 23.5
Clay: 16.7
Grass: 12.9
Serve Rating: 95.4
Return Rating: 88.2

Recent Matches

Roman Safiullin

Botic van de Zandschulp

  • Last Match: vs Aleksandar Kovacevic (3-1) grass Wimbledon 174 min
  • 2nd Last Match: vs Tommy Paul (0-2) grass London 101 min
  • 3rd Last Match: vs Harry Wendelken (2-0) grass London 114 min
  • 4th Last Match: vs Tallon Griekspoor (1-2) grass S Hertogenbosch 134 min
  • 5th Last Match: vs Francisco Cerundolo (1-3) clay Roland Garros 174 min

Head-to-Head (Last 2 Seasons)

0
Roman Safiullin
vs
0
Botic van de Zandschulp
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

At Wimbledon in London, round of 64 on grass, Botic van de Zandschulp is the model pick over Roman Safiullin. The forecast gives Botic a 61.32% chance to win against Safiullin’s 38.68%, with a predicted total of about 42.3 games in the match.

Match Analysis

The model’s edge for van de Zandschulp comes mainly from recent form and the contrast in fatigue and recent workload. Recent form shifts 5.7 percentage points toward Botic, and the lighter minutes on court (174 vs 696) add another 3.0 points in his favor — fatigue is a clear material factor heading into this grass contest. Safiullin’s superior short-term form index (86.78 vs 48.55) and his slightly higher Elo (1745 vs 1651) and surface strength index (18.43 vs 12.89) are reflected in a +2.8 point tilt for his serve and return game, but they are not enough to overcome Botic’s freshness and overall match context. Looking through the numbers: van de Zandschulp is the higher-ranked player (No. 54) versus Safiullin (No. 132), while Safiullin shows the stronger recent form index and marginally better return numbers. Neither player holds a dramatically better serve rating — Safiullin’s mean serve index is 96.25 to Botic’s 95.36, a negligible gap — and the same is true for returns (about a four-point gap). Over their last three matches at grass events, Safiullin has won three straight at this tournament (including two five-set victories and a straight-sets match), indicating resilience but heavy court time. Van de Zandschulp arrives with mixed results — a straight-sets loss to Tommy Paul in London but a solid 3–1 win here and a prior straight-sets victory.

Total Games Predictions

🎾
Expected Total Games in Match 42.3 Most likely outcome: 42 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Roman Safiullin versus Botic van de Zandschulp. 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 Roman Safiullin versus Botic van de Zandschulp. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Roman Safiullin - Botic van de Zandschulp) -0.9 Most likely spread: -1 (Botic van de Zandschulp wins 1 more games)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Roman Safiullin versus Botic van de Zandschulp. Positive values indicate Roman Safiullin winning more games, negative values indicate Botic van de Zandschulp winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Roman Safiullin versus Botic van de Zandschulp. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

The aces prediction is for a high tally: the match has a predicted aces total of about 21.9, while the double faults prediction sits near 10.0 expected double faults. Grass typically inflates ace counts because the ball stays low and players have less time to react; this predicted aces figure reflects that surface effect. With no significant gap in serve ratings, neither player is expected to dominate the ace count outright, though both should contribute to the predicted aces.
🎯
Expected Total Aces 21.9 Most likely: 21 aces
Expected Total Double Faults 10.0 Most likely: 9 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Roman Safiullin versus Botic van de Zandschulp. 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 Roman Safiullin versus Botic van de Zandschulp. 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 Roman Safiullin versus Botic van de Zandschulp. 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 Roman Safiullin versus Botic van de Zandschulp. 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

57.3% Predicted: Tiebreak likely

Exact Score Distribution BO5

Probability of each set-by-set outcome (Roman Safiullin's perspective)

0-3 Most likely set score (21.2%)
Probability distribution of the final set score from Roman Safiullin's perspective. Format: BO5.

Final Prediction

Van de Zandschulp’s edge is driven primarily by recent form and, crucially, the fatigue/workload differential that favors him. The key variable to watch is Safiullin’s accumulated minutes — his ability to sustain intensity after heavy court time will likely decide whether his serve/return quality can overcome Botic’s freshness.

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