Us Open NY, U.S.A. Hard Grand Slam Round of 128

Roman Safiullin vs Carlos Alcaraz: AI Prediction | Games, Spread, Aces & Double Faults

Roman Safiullin

Rank: #98
7%
VS

Carlos Alcaraz

Rank: #3
93%
Expected Total Games: 32.9
Predicted Winner: Carlos Alcaraz

Why the Model Favors Carlos Alcaraz

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

Overall strength +12.7 Carlos Alcaraz
Surface fit +10.1 Carlos Alcaraz
Recent record by level +9.3 Carlos Alcaraz
Serve & return game +3.4 Carlos Alcaraz
Overall record & opposition quality +2.9 Carlos Alcaraz

Starting from an even matchup, these factors move the model to 93% for Carlos Alcaraz. 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: 67.1
ELO Rating: 1777.0
Glicko2 Rating: 1759.1
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 14.8
Clay: 17.2
Grass: 23.5
Serve Rating: 96.0
Return Rating: 88.2

Carlos Alcaraz

Form Index: 36.3
ELO Rating: 2429.3
Glicko2 Rating: 2653.4
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 66.8
Clay: 95.5
Grass: 97.6
Serve Rating: 97.0
Return Rating: 91.8

Recent Matches

Roman Safiullin

  • Last Match: vs Hugo Grenier (1-2) hard Winston Salem 139 min
  • 2nd Last Match: vs Novak Djokovic (1-3) grass Wimbledon 174 min
  • 3rd Last Match: vs Joao Fonseca (3-0) grass Wimbledon 174 min
  • 4th Last Match: vs Botic van de Zandschulp (3-2) grass Wimbledon 174 min
  • 5th Last Match: vs Andrey Rublev (3-2) grass Wimbledon 174 min

Carlos Alcaraz

Head-to-Head (Last 2 Seasons)

0
Roman Safiullin
vs
0
Carlos Alcaraz
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

The US Open in New York opens its main draw on hard courts with Roman Safiullin facing Carlos Alcaraz in the round of 128. The model strongly favors Carlos Alcaraz, projecting a 93.41% chance of victory versus 6.59% for Safiullin, and expects about 32.9 games in the match.

Match Analysis

The model's edge for Alcaraz comes mainly from overall strength and surface fit. Overall strength contributes +12.7 percentage points in Alcarazs favor, reflected in his much higher Elo (2429 versus Safiullins 1777) and world rank (3 versus 98). Surface fit adds another +10.1 points. Alcaraz posts a surface strength index of 66.76 on hard courts compared with Safiullins 14.80, which explains why the model views this venue as highly favorable to Alcaraz despite Safiullins solid recent form index. Recent form by level also leans to Alcaraz (+9.3 points). Safiullin has a mixed run: a straight sets win at Wimbledon over Joao Fonseca, followed by two losses to Novak Djokovic and Hugo Grenier. Alcaraz has two recent wins and a loss against top opposition, showing the kind of results the model rewards. Serve and return considerations add a smaller advantage to Alcaraz (+3.4 points). Both players register high serve indices (Safiullin 95.96, Alcaraz 97.02) and strong return indices (Safiullin 88.16, Alcaraz 91.76), giving Alcaraz a modest edge in all-round play. Fatigue is not a factor for either player, both registering 0 minutes on court in this event.

Total Games Predictions

🎾
Expected Total Games in Match 32.9 Most likely outcome: 31 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

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

Games Spread Predictions

📈
Expected Games Spread (Roman Safiullin - Carlos Alcaraz) -7.4 Most likely spread: -8 (Carlos Alcaraz wins 8 more games)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Roman Safiullin versus Carlos Alcaraz. Positive values indicate Roman Safiullin winning more games, negative values indicate Carlos Alcaraz winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Roman Safiullin versus Carlos Alcaraz. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

The aces prediction for the match is 14.79 total, with predicted aces split at about 6.86 for Safiullin and 7.99 for Alcaraz. The double faults prediction is 7.41 total, with expected double faults of 3.72 for Safiullin and 3.69 for Alcaraz. On New York hard courts, a medium paced surface, those predicted aces align with balanced serving dynamics rather than an extreme server advantage.
🎯
Expected Total Aces 14.8 Most likely: 12 aces Per player: Roman Safiullin 6.9 + Carlos Alcaraz 8.0
Expected Total Double Faults 7.4 Most likely: 6 double faults Per player: Roman Safiullin 3.7 + Carlos Alcaraz 3.7

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Roman Safiullin versus Carlos Alcaraz. 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 Carlos Alcaraz. The curve shows the cumulative probability for each aces threshold.

🎯 Aces by Player

Roman Safiullin

Expected 6.9 aces

Probability distribution for the aces Roman Safiullin serves in this match.
Carlos Alcaraz

Expected 8.0 aces

Probability distribution for the aces Carlos Alcaraz serves in this match.

Double Faults Probability Distribution

Distribution

Probability of each double fault count outcome

Probability distribution chart for double faults in Roman Safiullin versus Carlos Alcaraz. 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 Roman Safiullin versus Carlos Alcaraz. The curve shows the cumulative probability for each double faults threshold.

Double Faults by Player

Roman Safiullin

Expected 3.7 double faults

Probability distribution for the double faults Roman Safiullin serves in this match.
Carlos Alcaraz

Expected 3.7 double faults

Probability distribution for the double faults Carlos Alcaraz serves in this match.

🎯 Match Format Predictions

Tiebreak Likelihood

Probability that any tiebreak is played in this match

31.9% Predicted: No tiebreak

Exact Score Distribution BO5

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

0-3 Most likely set score (64.4%)
Probability distribution of the final set score from Roman Safiullin's perspective. Format: BO5.

Final Prediction

Alcarazs margin comes primarily from overall strength as expressed in Elo and ranking, with surface fit the next biggest contributor. The clearest factor to watch is how Alcaraz exploits the hard court surface advantage, especially his ability to pressure Safiullins service games and convert break opportunities.

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