Roland Garros France Clay Grand Slam Round of 32

Karen Khachanov vs Jesper de Jong: AI Prediction | Games, Spread, Aces & Double Faults

Karen Khachanov

Rank: #15
52%
VS

Jesper de Jong

Rank: #109
48%
Expected Total Games: 39.4
Predicted Winner: Karen Khachanov

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Ranking Trends

Karen Khachanov

  • Current #15 2026-05-18
  • 3 mo ago #16 2026-02-23
  • 6 mo ago #18 2025-11-24
  • 9 mo ago #9 2025-08-25
  • 12 mo ago #24 2025-05-26

Jesper de Jong

  • Current #109 2026-05-18
  • 3 mo ago #89 2026-02-23
  • 6 mo ago #76 2025-11-24
  • 9 mo ago #83 2025-08-25
  • 12 mo ago #88 2025-05-26

Player Metrics

Karen Khachanov

Form Index: 56.3
ELO Rating: 1749.1
Glicko2 Rating: 1720.8
Current Fatigue (minutes): 348.0
Surface Strength:
Hard: 24.4
Clay: 29.1
Grass: 32.8
Serve Rating: 95.9
Return Rating: 91.7

Jesper de Jong

Form Index: 46.0
ELO Rating: 1616.5
Glicko2 Rating: 1530.7
Current Fatigue (minutes): 696.0
Surface Strength:
Hard: 18.8
Clay: 21.5
Grass: 7.2
Serve Rating: 94.8
Return Rating: 86.5

Recent Matches

Karen Khachanov
✅ ✅ ❌ ✅ ❌

  • Last Match: ✅ vs Marco Trungelliti (3-1) clay Roland Garros 174 min
  • 2nd Last Match: ✅ vs Arthur Gea (3-0) clay Roland Garros 174 min
  • 3rd Last Match: ❌ vs Ugo Humbert (1-2) clay Hamburg 133 min
  • 4th Last Match: ✅ vs Hugo Gaston (2-1) clay Hamburg 158 min
  • 5th Last Match: ❌ vs Casper Ruud (1-2) clay Rome 100 min

Jesper de Jong
✅ ✅ ❌ ✅ ❌

  • Last Match: ✅ vs Federico Cina (3-0) clay Roland Garros 174 min
  • 2nd Last Match: ✅ vs Stan Wawrinka (3-1) clay Roland Garros 174 min
  • 3rd Last Match: ❌ vs Michael Zheng (0-2) clay Roland Garros 174 min
  • 4th Last Match: ✅ vs Liam Draxl (2-1) clay Roland Garros 174 min
  • 5th Last Match: ❌ vs Nuno Borges (0-2) clay Rome 61 min

Head-to-Head (Last 2 Seasons)

1
Karen Khachanov
vs
0
Jesper de Jong
Hard
1 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

Roland-Garros Round of 32 in Paris sets up a clay-court clash between No.15 Karen Khachanov and No.109 Jesper de Jong. The model nudges Khachanov as the favorite — 52.48% to 47.52% — with a projected total of roughly 39.4 games in the match.

Match Analysis

Khachanov brings the higher rank (15), a stronger Elo (1749 vs 1616) and a superior form index (56.3 to 46.0). He has moderate cumulative fatigue at 348 minutes on court this event, whereas de Jong carries heavy mileage (696 minutes), which could matter over long rallies on clay. Both players show modest surface strength indices on clay (Khachanov 29.1, de Jong 21.5), indicating neither is a pure clay specialist. Khachanov’s mean serve index (95.9) and de Jong’s (94.8) are very close, so serve firepower alone is unlikely to be decisive; however Khachanov’s mean return index (91.7) is about 5.13 points higher than de Jong’s (86.55), a difference worth noting on the slower surface. Form in the last three matches is similar in pattern: Khachanov arrived with two straight wins at Roland-Garros (over Marco Trungelliti and Arthur Gea) after a prior loss in Hamburg to Ugo Humbert. De Jong has also won two matches at Roland-Garros (including a four-set win over Stan Wawrinka) after an earlier defeat to Michael Zheng. Recent results suggest both players can string wins together here, but Khachanov’s higher ranking and return numbers give him a slight edge in baseline exchanges.

Total Games Predictions

🎾
Expected Total Games in Match 39.4 Most likely outcome: 39 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Cumulative Probability (CDF)

Probability of total games ≤ X

Games Spread Predictions

📈
Expected Games Spread (Karen Khachanov - Jesper de Jong) +0.3 Most likely spread: 0 (even number of games won)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Cumulative Probability (CDF)

Probability of spread ≤ X

Aces and Double Faults Predictions

The aces prediction is modest: the match has a predicted aces total of about 15.9, while the predicted double faults (expected double faults) sit near 6.5. On clay, slower ball speed and higher bounce generally suppress ace counts and can increase pressure-induced errors, so the expected double faults figure is consistent with surface demands. Neither player posts a substantially higher serve rating to materially lift the predicted aces.
🎯
Expected Total Aces 15.9 Most likely: 15 aces
❌
Expected Total Double Faults 6.5 Most likely: 6 double faults

🎯 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

49.9% Predicted: No tiebreak

Exact Score Distribution BO5

Probability of each set-by-set outcome (Karen Khachanov's perspective)

0-3 Most likely set score (21.0%)
New to probability charts? Learn how to interpret distribution and CDF curves

Final Prediction

Khachanov’s edge comes from higher ranking, Elo and a notably stronger return profile, paired with fresher legs relative to de Jong’s heavy court time. Watch long baseline exchanges and return games early: if Khachanov converts breaks, his slight probabilistic advantage should carry him through.

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