Miami FL, U.S.A. Hard Masters 1000 Round of 128

Giovanni Mpetshi Perricard vs Camilo Ugo Carabelli: AI Prediction | Games, Spread, Aces & Double Faults

Giovanni Mpetshi Perricard

Rank: #59
46%
VS

Camilo Ugo Carabelli

Rank: #66
54%
Expected Total Games: 24.8
Predicted Winner: Camilo Ugo Carabelli

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Player Metrics

Giovanni Mpetshi Perricard

Form Index: 34.4
ELO Rating: 888.5
Glicko2 Rating: 1643.8
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 5.9
Clay: 6.7
Grass: 6.9
Serve Rating: 99.2
Return Rating: 4.3

Camilo Ugo Carabelli

Form Index: 30.9
ELO Rating: 904.2
Glicko2 Rating: 1551.0
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 7.6
Clay: 7.6
Grass: 7.9
Serve Rating: 98.0
Return Rating: 91.9

Recent Matches

Giovanni Mpetshi Perricard

  • Last Match: vs Kamil Majchrzak (1-2) hard Indian Wells 106 min
  • 2nd Last Match: vs Felix Auger-Aliassime (0-2) hard Dubai 81 min
  • 3rd Last Match: vs Moez Echargui (2-1) hard Dubai 155 min
  • 4th Last Match: vs Jan Choinski (2-1) hard Dubai 113 min
  • 5th Last Match: vs Shintaro Mochizuki (2-0) hard Dubai 71 min

Camilo Ugo Carabelli

  • Last Match: vs Brandon Nakashima (0-2) hard Indian Wells 73 min
  • 2nd Last Match: vs Martin Damm (2-0) hard Indian Wells 110 min
  • 3rd Last Match: vs Yannick Hanfmann (0-2) clay Santiago 96 min
  • 4th Last Match: vs Roman Andres Burruchaga (0-2) clay Rio 96 min
  • 5th Last Match: vs Sebastian Baez (0-2) clay Buenos Aires 119 min

Head-to-Head (Last 2 Seasons)

0
Giovanni Mpetshi Perricard
vs
0
Camilo Ugo Carabelli
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

At the Miami Masters in Florida, the round of 128 on hard court pits Giovanni Mpetshi Perricard against Camilo Ugo Carabelli in a matchup between two big servers with contrasting return profiles. The model favors Camilo Ugo Carabelli to win (54.32%) over Giovanni Mpetshi Perricard (45.68%), with an expected total of about 24.8 games in the match — suggesting a fairly straight-set affair is likeliest.

Match Analysis

Giovanni Mpetshi Perricard arrives as the higher-ranked player (No. 59) with a slightly stronger form index (34.41) than Carabelli (30.86), but Elo tells a different story: Carabelli holds the edge (904.22 vs 888.47). Both players show zero tournament fatigue. Surface strength indexes are modest for both — 5.94 for Perricard and 7.63 for Carabelli — indicating neither is a true hard-court specialist on the data provided. Their mean serve indices are very close (Giovanni 99.20, Camilo 98.01), so serve power alone is unlikely to separate them. The clearest statistical gap is return ability: Carabelli registers a very high mean return index (91.90) versus Perricard’s low 4.32, a difference that should be decisive in service games and break opportunities. Recent form for Perricard shows one win (vs Moez Echargui) and back-to-back losses to Felix Auger-Aliassime and Kamil Majchrzak at hard-court events, including a long 155-minute match that may have taxed him in prior weeks. Carabelli’s last three matches produced a win over Martin Damm and losses to Brandon Nakashima and Yannick Hanfmann; his return strengths are the standout feature through that sample.

Total Games Predictions

🎾
Expected Total Games in Match 24.8 Most likely outcome: 24 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Giovanni Mpetshi Perricard versus Camilo Ugo Carabelli. 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 Giovanni Mpetshi Perricard versus Camilo Ugo Carabelli. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Giovanni Mpetshi Perricard - Camilo Ugo Carabelli) +0.4 Most likely spread: 0 (even number of games won)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Giovanni Mpetshi Perricard versus Camilo Ugo Carabelli. Positive values indicate Giovanni Mpetshi Perricard winning more games, negative values indicate Camilo Ugo Carabelli winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Giovanni Mpetshi Perricard versus Camilo Ugo Carabelli. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

The aces prediction for this hard-court match is moderate-high with predicted aces around 16.46, reflecting both players’ strong serve indices. Expected double faults sit at about 5.44; the double faults prediction implies some risk when both push for free points. On a medium-paced hard court, predicted aces are neither as high as on grass nor as suppressed as on clay. Neither player has a significantly higher serve rating, so the ace count will more likely be shaped by serving aggressiveness and return prowess.
🎯
Expected Total Aces 16.5 Most likely: 16 aces
Expected Total Double Faults 5.4 Most likely: 5 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Giovanni Mpetshi Perricard versus Camilo Ugo Carabelli. 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 Giovanni Mpetshi Perricard versus Camilo Ugo Carabelli. 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 Giovanni Mpetshi Perricard versus Camilo Ugo Carabelli. 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 Giovanni Mpetshi Perricard versus Camilo Ugo Carabelli. The curve shows the cumulative probability for each double faults threshold.

Final Prediction

Carabelli’s superior return metrics and slightly higher Elo give him the edge in this encounter, particularly when it comes to converting break chances. The key factor to watch is whether Perricard can protect his serve under Carabelli’s pressure on return — that battle should decide the match.

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