Cincinnati OH, U.S.A. Hard Masters 1000 Round of 128

Zachary Svajda vs Mattia Bellucci: AI Prediction | Games, Spread, Aces & Double Faults

Zachary Svajda

Rank: #87
46%
VS

Mattia Bellucci

Rank: #80
54%
Expected Total Games: 27.0
Predicted Winner: Mattia Bellucci

Why the Model Favors Mattia Bellucci

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

Recent form +6.3 Mattia Bellucci
Recent record by level +2.0 Zachary Svajda
Overall record & opposition quality +0.7 Zachary Svajda
Serve & return game +0.7 Mattia Bellucci
Surface fit +0.6 Zachary Svajda

Starting from an even matchup, these factors move the model to 54% for Mattia Bellucci. Computed with gradient-based attribution on our neural network, not editorial opinion. How to read this →

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Player Metrics

Zachary Svajda

Form Index: 43.5
ELO Rating: 1670.9
Glicko2 Rating: 1679.2
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 23.6
Clay: 21.5
Grass: 12.9
Serve Rating: 94.2
Return Rating: 87.5

Mattia Bellucci

Form Index: 34.7
ELO Rating: 1573.7
Glicko2 Rating: 1625.3
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 11.8
Clay: 10.3
Grass: 18.9
Serve Rating: 95.7
Return Rating: 84.5

Recent Matches

Zachary Svajda

  • Last Match: vs Arthur Fils (1-2) hard Toronto 98 min
  • 2nd Last Match: vs Denis Shapovalov (1-1) hard Toronto 100 min
  • 3rd Last Match: vs Aleksandar Vukic (0-2) hard Washington 50 min
  • 4th Last Match: vs Cruz Hewitt (1-1) hard Washington 97 min
  • 5th Last Match: vs Stefan Kozlov (2-0) hard Washington 103 min

Mattia Bellucci

Head-to-Head (Last 2 Seasons)

0
Zachary Svajda
vs
0
Mattia Bellucci
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

Cincinnati, OH — Round of 128 on hard courts at a Masters 1000 event. The model leans to Mattia Bellucci to upset Zachary Svajda: Bellucci 53.80% vs Svajda 46.20%, with a predicted total of about 26.99 games (roughly a straight‑sets match with one competitive set).

Match Analysis

The model's edge for Bellucci is driven primarily by recent form (+6.3 percentage points) and a small serve/return tilt (+0.7). Those model drivers sit against a set of modest advantages for Svajda — recent record by level (+2.0), overall record & opposition quality (+0.7), and surface fit (+0.6) — producing a close projection. On paper the two are finely matched: Bellucci is ranked 80 to Svajda’s 87, while Svajda carries the higher Elo (1670.9 vs 1573.7). Both players arrive fresh with zero minutes of tournament fatigue and strong serving profiles (mean serve indexes 94.23 for Svajda and 95.73 for Bellucci); the serve and return gaps are not large enough to be decisive. Stat lines underline the marginal nature of this matchup. Svajda’s form_index is 43.46 versus Bellucci’s 34.69, and Svajda also posts a stronger surface strength index (23.55 to 11.76) — factors that nudge the projection back toward him. Recent results are mixed: Svajda is 1–2 in his last three (including a win over Denis Shapovalov and losses to Arthur Fils and Aleksandar Vukic), while Bellucci has lost his last three matches (to Sebastian Baez, Ugo Humbert and Raphael Collignon), with two of those defeats coming on grass.

Total Games Predictions

🎾
Expected Total Games in Match 27.0 Most likely outcome: 27 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Zachary Svajda versus Mattia Bellucci. 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 Zachary Svajda versus Mattia Bellucci. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Zachary Svajda - Mattia Bellucci) -0.5 Most likely spread: -1 (Mattia Bellucci wins 1 more games)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Zachary Svajda versus Mattia Bellucci. Positive values indicate Zachary Svajda winning more games, negative values indicate Mattia Bellucci winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Zachary Svajda versus Mattia Bellucci. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

Aces prediction: the match is expected to produce about 14.4 aces in total; predicted aces are moderate given a medium‑paced hard court. Double faults prediction: the expected double faults total is about 7.07. Hard courts generally yield a balanced ace profile — not as many as grass but more than clay — and since neither player has a markedly higher serve rating, neither is expected to dominate ace production.
🎯
Expected Total Aces 14.4 Most likely: 14 aces
Expected Total Double Faults 7.1 Most likely: 7 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Zachary Svajda versus Mattia Bellucci. 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 Zachary Svajda versus Mattia Bellucci. 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 Zachary Svajda versus Mattia Bellucci. The chart shows the predicted probability for each double-fault count.
Cumulative Probability (CDF)

Probability of double faults ≤ X

Cumulative distribution function chart for double faults in Zachary Svajda versus Mattia Bellucci. 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

41.7% Predicted: No tiebreak

Exact Score Distribution BO3

Probability of each set-by-set outcome (Zachary Svajda's perspective)

0-2 Most likely set score (31.9%)
Probability distribution of the final set score from Zachary Svajda's perspective. Format: BO3.

Final Prediction

Bellucci’s slight edge comes chiefly from the model’s assessment of his recent form. The key factor to watch will be how Bellucci’s recent form translates to serve consistency and clutch points early in sets; that, more than rankings or raw serve numbers, will likely decide the match.

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