Roland Garros France Clay Grand Slam Round of 16

Jesper de Jong vs Alexander Zverev: AI Prediction | Games, Spread, Aces & Double Faults

Jesper de Jong

Rank: #109
12%
VS

Alexander Zverev

Rank: #3
88%
Expected Total Games: 37.4
Predicted Winner: Alexander Zverev

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Player Metrics

Jesper de Jong

Form Index: 54.4
ELO Rating: 1671.0
Glicko2 Rating: 1567.4
Current Fatigue (minutes): 870.0
Surface Strength:
Hard: 18.8
Clay: 25.4
Grass: 7.2
Serve Rating: 95.5
Return Rating: 91.9

Alexander Zverev

Form Index: 67.2
ELO Rating: 2077.1
Glicko2 Rating: 2060.3
Current Fatigue (minutes): 522.0
Surface Strength:
Hard: 54.5
Clay: 48.1
Grass: 38.7
Serve Rating: 95.1
Return Rating: 85.9

Recent Matches

Jesper de Jong

  • Last Match: vs Karen Khachanov (3-2) clay Roland Garros 174 min
  • 2nd Last Match: vs Federico Cina (3-0) clay Roland Garros 174 min
  • 3rd Last Match: vs Stan Wawrinka (3-1) clay Roland Garros 174 min
  • 4th Last Match: vs Michael Zheng (0-2) clay Roland Garros 174 min
  • 5th Last Match: vs Liam Draxl (2-1) clay Roland Garros 174 min

Alexander Zverev

  • Last Match: vs Quentin Halys (3-1) clay Roland Garros 174 min
  • 2nd Last Match: vs Tomas Machac (3-0) clay Roland Garros 174 min
  • 3rd Last Match: vs Benjamin Bonzi (3-0) clay Roland Garros 174 min
  • 4th Last Match: vs Luciano Darderi (1-2) clay Rome 144 min
  • 5th Last Match: vs Alexander Blockx (2-0) clay Rome 73 min

Head-to-Head (Last 2 Seasons)

0
Jesper de Jong
vs
1
Alexander Zverev
Hard
0 - 0
Clay
0 - 1
Grass
0 - 0

Key Prediction Insights

Round of 16 at Roland Garros in Paris, clay courts, sets up a clear favorite in Alexander Zverev against Jesper de Jong. The model projects Zverev to win (88.16%) with de Jong on 11.84%, and the match is expected to produce about 37.4 games.

Match Analysis

On paper the gap is stark: Zverev sits at world No. 3 with an Elo of 2077 and a form index of 67.2, while de Jong is No. 109 with an Elo of 1671 and a form index of 54.4. Zverev’s surface strength index (48.1) is nearly double de Jong’s (25.4), and he has accumulated substantially less fatigue in the tournament (522 minutes vs 870 minutes), which matters deep into best-of-five affairs on clay. Jesper’s mean serve index (95.5) and Zverev’s (95.1) are effectively level, so serve-firepower alone is not a differentiator here. Where de Jong can pressure is his return: his mean return index (91.93) is about six points higher than Zverev’s (85.89), a margin worth noting on clay where breaks are more frequent. Both players arrive having won their three previous Roland Garros matches; de Jong’s run includes wins over Stan Wawrinka, Federico Cina and Karen Khachanov, while Zverev dispatched Benjamin Bonzi, Tomas Machac and Quentin Halys. Each advanced through similar phases to reach this round, but Zverev’s higher ranking, superior Elo and fresher legs tilt the balance.

Total Games Predictions

🎾
Expected Total Games in Match 37.4 Most likely outcome: 37 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Jesper de Jong versus Alexander Zverev. 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 Jesper de Jong versus Alexander Zverev. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Jesper de Jong - Alexander Zverev) -5.6 Most likely spread: -6 (Alexander Zverev wins 6 more games)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Jesper de Jong versus Alexander Zverev. Positive values indicate Jesper de Jong winning more games, negative values indicate Alexander Zverev winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Jesper de Jong versus Alexander Zverev. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

Aces prediction is modest: the match’s predicted aces (16.02) reflects clay’s tendency to suppress free points, and the predicted aces total is unlikely to reflect serve-dominated games. Given the surface and similar serve indexes, the predicted aces figure is driven more by length of rallies than by a single big server. Double faults prediction also leans up: the expected double faults (5.74) account for clay’s longer exchanges and the greater fatigue carried by de Jong, which can raise the chance of late-match errors.
🎯
Expected Total Aces 16.0 Most likely: 16 aces
Expected Total Double Faults 5.7 Most likely: 5 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Jesper de Jong versus Alexander Zverev. 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 Jesper de Jong versus Alexander Zverev. 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 Jesper de Jong versus Alexander Zverev. 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 Jesper de Jong versus Alexander Zverev. 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

51.0% Predicted: Tiebreak likely

Exact Score Distribution BO5

Probability of each set-by-set outcome (Jesper de Jong's perspective)

0-3 Most likely set score (53.7%)
Probability distribution of the final set score from Jesper de Jong's perspective. Format: BO5.

Final Prediction

Zverev’s edge comes from higher ranking, stronger Elo, better surface profile and lower tournament fatigue. The key factor to watch is de Jong’s return efficiency—if he can convert early break chances, he can force longer sets; otherwise Zverev’s consistency and court experience should close this one.

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