Miami FL, U.S.A. Hard Masters 1000 Round of 64

Andrey Rublev vs Alejandro Tabilo: AI Prediction | Games, Aces & Double Faults

Andrey Rublev

Rank: #16
60%
VS

Alejandro Tabilo

Rank: #41
40%
Expected Total Games: 23.5
Predicted Winner: Andrey Rublev

Ranking Trends

Andrey Rublev

  • Current Rank: #16 (2026-03-16)
  • 3 Months Ago: #16 (2025-12-15)
  • 6 Months Ago: #14 (2025-09-15)
  • 9 Months Ago: #14 (2025-06-16)
  • 12 Months Ago: #9 (2025-03-17)

Alejandro Tabilo

  • Current Rank: #41 (2026-03-16)
  • 3 Months Ago: #81 (2025-12-15)
  • 6 Months Ago: #112 (2025-09-15)
  • 9 Months Ago: #55 (2025-06-16)
  • 12 Months Ago: #31 (2025-03-17)

Player Metrics

Andrey Rublev

Form Index: 44.4
ELO Rating: 2188.8
Glicko2 Rating: 1846.1
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 13.0
Clay: 19.6
Grass: 20.0
Serve Rating: 77.0
Return Rating: 56.7

Alejandro Tabilo

Form Index: 55.1
ELO Rating: 832.3
Glicko2 Rating: 1698.6
Current Fatigue (minutes): 77.0
Surface Strength:
Hard: 7.5
Clay: 7.4
Grass: 6.0
Serve Rating: 99.1
Return Rating: 90.1

Recent Matches

Andrey Rublev
❌ ❌ ✅ ✅ ✅

  • Last Match: ❌ vs Gabriel Diallo (1-2) hard Indian Wells 172 min
  • 2nd Last Match: ❌ vs Tallon Griekspoor (0-2) hard Dubai 105 min
  • 3rd Last Match: ✅ vs Arthur Rinderknech (2-0) hard Dubai 75 min
  • 4th Last Match: ✅ vs Ugo Humbert (2-1) hard Dubai 143 min
  • 5th Last Match: ✅ vs Valentin Royer (2-0) hard Dubai 89 min

Alejandro Tabilo
✅ ❌ ✅ ❌ ✅

  • Last Match: ✅ vs Francisco Comesana (2-0) hard Miami 77 min
  • 2nd Last Match: ❌ vs Daniil Medvedev (0-2) hard Indian Wells 70 min
  • 3rd Last Match: ✅ vs Rafael Jodar (2-0) hard Indian Wells 58 min
  • 4th Last Match: ❌ vs Sebastian Baez (0-2) clay Santiago 81 min
  • 5th Last Match: ✅ vs Thiago Agustin Tirante (2-1) clay Santiago 127 min

Head-to-Head (Last 2 Seasons)

0
Andrey Rublev
vs
0
Alejandro Tabilo
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

At the Miami Masters in Florida, Round of 64 on hard courts, Andrey Rublev is narrowly favored over Alejandro Tabilo. The model gives Rublev a 60.32% chance to win versus 39.68% for Tabilo, with a predicted total of about 23.48 games in the match.

Match Analysis

Rublev arrives as the higher-ranked player (No. 16) with a much stronger Elo (2188.8) compared to Tabilo (rank 41, Elo 832.27). His form index (44.38) is behind Tabilo’s (55.14), but Rublev shows a higher surface strength index (13.03 vs 7.52). Fatigue figures differ: Rublev registers 0.0 minutes in-tournament, while Tabilo shows 77 minutes on court already, a factor to monitor for recovery and movement late in rallies. Serve and return profiles diverge sharply. Tabilo’s mean serve index (99.15) is substantially higher than Rublev’s (77.03), a gap of more than 20 points that suggests Tabilo can produce more free points on serve. Likewise Tabilo’s mean return index (90.13) far exceeds Rublev’s (56.72) by over 33 points, indicating strong return capability when he’s on. Recent results underline the contrast: Rublev has one comfortable win (Rinderknech) and two losses (Griekspoor, Diallo, the latter a 172-minute battle), while Tabilo comes in with two wins at Miami and Indian Wells and a straight-sets loss to Medvedev. Match lengths for Tabilo’s recent wins were relatively short (58–77 minutes), though his Miami fatigue is nonzero.

Total Games Predictions

🎾
Expected Total Games in Match 23.5 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 this meeting sits at about 10.95 total aces, and the double faults prediction is roughly 5.02 expected double faults. Hard courts typically produce a moderate ace count—faster than clay but not as serving-dominant as grass—so the predicted aces reflect that balance. Given Tabilo’s significantly higher serve rating, he is likely to contribute a larger share of the predicted aces, which could swing short service games in his favor.
🎯
Expected Total Aces 10.9 Most likely: 10 aces
❌
Expected Total Double Faults 5.0 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

Rublev’s edge comes from his higher ranking and markedly superior Elo and surface strength metrics, offsetting Tabilo’s stronger serve and return indexes. The key factor to watch is whether Tabilo can convert his serve dominance into free points; if he does, the match could be tighter than the probabilities suggest.

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