Indian Wells CA, U.S.A. Hard Masters 1000 Round of 128

Fabian Marozsan vs Roberto Bautista Agut: AI Prediction | Games, Aces & Double Faults

Fabian Marozsan

Rank: #50
66%
VS

Roberto Bautista Agut

Rank: #85
34%
Expected Total Games: 23.2
Predicted Winner: Fabian Marozsan

Ranking Trends

Fabian Marozsan

  • Current Rank: #50 (2026-02-23)
  • 3 Months Ago: #51 (2025-12-01)
  • 6 Months Ago: #53 (2025-08-25)
  • 9 Months Ago: #56 (2025-05-26)
  • 12 Months Ago: #54 (2025-03-03)

Roberto Bautista Agut

  • Current Rank: #85 (2026-02-23)
  • 3 Months Ago: #92 (2025-12-01)
  • 6 Months Ago: #47 (2025-08-25)
  • 9 Months Ago: #49 (2025-05-26)
  • 12 Months Ago: #50 (2025-03-03)

Player Metrics

Fabian Marozsan

Form Index: 36.6
ELO Rating: 1175.6
Glicko2 Rating: 1611.2
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 8.2
Clay: 9.1
Grass: 8.1
Serve Rating: 77.4
Return Rating: 49.7

Roberto Bautista Agut

Form Index: 21.0
ELO Rating: 589.9
Glicko2 Rating: 1597.1
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 6.1
Clay: 7.4
Grass: 8.0
Serve Rating: 97.6
Return Rating: 90.2

Recent Matches

Fabian Marozsan
❌ ❌ ✅ ❌ ✅

  • Last Match: ❌ vs Arthur Rinderknech (1-2) hard Dubai 113 min
  • 2nd Last Match: ❌ vs Andrey Rublev (0-2) hard Doha 67 min
  • 3rd Last Match: ✅ vs Ugo Humbert (2-0) hard Doha 57 min
  • 4th Last Match: ❌ vs Daniil Medvedev (2-3) hard Australian Open 174 min
  • 5th Last Match: ✅ vs Kamil Majchrzak (3-0) hard Australian Open 174 min

Roberto Bautista Agut
❌ ❌ ✅ ❌ ❌

  • Last Match: ❌ vs Cameron Norrie (0-2) hard Rotterdam 114 min
  • 2nd Last Match: ❌ vs Martin Damm (0-2) hard Montpellier 55 min
  • 3rd Last Match: ✅ vs Christopher O'Connell (2-1) hard Montpellier 168 min
  • 4th Last Match: ❌ vs Juncheng Shang (1-3) hard Australian Open 174 min
  • 5th Last Match: ❌ vs Giovanni Mpetshi Perricard (0-2) hard Auckland 96 min

Head-to-Head (Last 2 Seasons)

0
Fabian Marozsan
vs
1
Roberto Bautista Agut
Hard
0 - 1
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

At Indian Wells in California, the 2026 masters_1000 opening round on hard courts pits rising Fabian Marozsan against veteran Roberto Bautista Agut. The model favors Marozsan, projecting him to win with a 65.71% probability to Bautista Agut’s 34.29%, and expects a relatively short match of about 23.22 total games.

Match Analysis

Marozsan arrives as the higher-ranked player (No. 50) with a substantially stronger Elo (1,175.59) and a cleaner recent form index (36.58) than Bautista Agut (rank 85, Elo 589.88, form 21.03). Both players show no tournament fatigue. Marozsan’s surface strength index (8.25) is modestly higher than Bautista Agut’s (6.11). On serve and return metrics there are large gaps: Bautista Agut’s mean serve index (97.59) tops Marozsan’s (77.37) by more than 20 points, and his mean return index (90.25) similarly outpaces Marozsan’s (49.66) by over 40 points — a striking statistical contrast for a hard-court matchup. Looking at recent results, Marozsan has one win (Ugo Humbert in Doha) and two defeats (Andrey Rublev in Doha and Arthur Rinderknech in Dubai), with matches largely on hard courts and mixed durations. Bautista Agut’s last three show one victory (Christopher O’Connell in Montpellier) and two losses (to Martin Damm in Montpellier and Cameron Norrie in Rotterdam). Both players’ recent form has been inconsistent, but Marozsan’s higher Elo and ranking reflect stronger underlying performance in the metrics provided.

Total Games Predictions

🎾
Expected Total Games in Match 23.2 Most likely outcome: 23 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Cumulative Probability (CDF)

Probability of total games ≤ X

Aces and Double Faults Predictions

The aces prediction for the match is fairly high: the model’s predicted aces total is 19.38, reflecting Bautista Agut’s very high serve index likely driving many free points. The expected double faults are 5.72, a modest figure consistent with hard courts’ medium pace. Given the surface and Bautista Agut’s serve rating, the predicted aces should be concentrated more on his service games.
🎯
Expected Total Aces 19.4 Most likely: 19 aces
❌
Expected Total Double Faults 5.7 Most likely: 5 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

New to probability charts? Learn how to interpret distribution and CDF curves

Final Prediction

Marozsan’s edge comes from superior Elo, higher ranking and the slightly better form and surface strength shown in the data, which outweigh Bautista Agut’s standout serve and return indices in the model’s forecast. Watch the serve-vs-return matchup closely: if Bautista Agut converts his serve power into aces and holds, he can shorten the match; if Marozsan sustains baseline consistency and breaks through early, the statistics favor him to close it out.

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