Australian Open Australia Hard Grand Slam Round of 128

Karen Khachanov vs Alex Michelsen: AI Prediction | Games, Spread, Aces & Double Faults

Karen Khachanov

Rank: #17
41%
VS

Alex Michelsen

Rank: #37
59%
Expected Total Games: 37.9
Predicted Winner: Alex Michelsen

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Ranking Trends

Karen Khachanov

  • Current #17 2026-01-05
  • 3 mo ago #13 2025-10-20
  • 6 mo ago #16 2025-07-21
  • 9 mo ago #25 2025-04-21
  • 12 mo ago #19 2025-01-13

Alex Michelsen

  • Current #37 2026-01-05
  • 3 mo ago #34 2025-10-20
  • 6 mo ago #34 2025-07-21
  • 9 mo ago #38 2025-04-21
  • 12 mo ago #42 2025-01-13

Player Metrics

Karen Khachanov

Form Index: 13.3
ELO Rating: 2214.4
Glicko2 Rating: 1736.5
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 10.9
Clay: 17.3
Grass: 18.9
Serve Rating: 64.8
Return Rating: 63.9

Alex Michelsen

Form Index: 46.5
ELO Rating: 1291.9
Glicko2 Rating: 1631.9
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 10.3
Clay: 10.1
Grass: 11.0
Serve Rating: 98.2
Return Rating: 95.5

Recent Matches

Karen Khachanov
❌ ❌ ✅ ❌ ❌

  • Last Match: ❌ vs Michael Mmoh (0-2) hard Hong Kong 122 min
  • 2nd Last Match: ❌ vs Alex de Minaur (0-2) hard Paris 68 min
  • 3rd Last Match: ✅ vs Joao Fonseca (2-1) hard Paris 110 min
  • 4th Last Match: ❌ vs Tallon Griekspoor (1-2) hard Vienna 123 min
  • 5th Last Match: ❌ vs Jan-Lennard Struff (1-2) hard Almaty 139 min

Alex Michelsen
❌ ✅ ❌ ✅ ✅

Head-to-Head (Last 2 Seasons)

1
Karen Khachanov
vs
1
Alex Michelsen
Hard
1 - 1
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

The matchup between Karen Khachanov and Alex Michelsen at the 2026 Australian Open in the Round of 128 promises to be intriguing as both players seek to advance on the hard court surface. With Khachanov ranked 17th and Michelsen at 37th, the prediction leans towards Michelsen with a win probability of 58.55%, compared to Khachanov's 41.45%. The expected total number of games in this match is approximately 37.94, indicating a potentially competitive encounter.

Match Analysis

Karen Khachanov, currently ranked 17, exhibits a form index of 13.31 and an Elo rating of 2214.40. His performance has been inconsistent recently, with two consecutive losses in his last matches. Despite having a solid surface strength index of 10.86, Khachanov’s mean serve index stands at 64.82, while his return index is 63.94, suggesting a balanced skill set but not particularly dominant in either area. On the other hand, Alex Michelsen, ranked 37, shows a better form index of 46.55 and a significantly lower Elo rating of 1291.87, indicating he may be less experienced at this level. However, with a mean serve index of 98.16 and a mean return index of 95.52, Michelsen demonstrates a commanding advantage in both serving and returning capabilities, as the difference in serve indices exceeds 30 points. Recent performances show Michelsen won one of his last three matches, while Khachanov lost two, indicating a momentum shift in Michelsen’s favor.

Total Games Predictions

🎾
Expected Total Games in Match 37.9 Most likely outcome: 37 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Cumulative Probability (CDF)

Probability of total games ≤ X

Games Spread Predictions

📈
Expected Games Spread (Karen Khachanov - Alex Michelsen) +1.2 Most likely spread: +1 (Karen Khachanov wins 1 more games)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Cumulative Probability (CDF)

Probability of spread ≤ X

Aces and Double Faults Predictions

The match is expected to feature around 12.6 aces, consistent with the nature of hard courts that favor both strong servers and returners alike. Given Michelsen's high mean serve index, he may significantly contribute to the expected aces count. The predicted double faults are around 3.65, which reflects a typical match scenario on hard courts where players have more control over their serves compared to softer surfaces.
🎯
Expected Total Aces 12.6 Most likely: 12 aces
❌
Expected Total Double Faults 3.6 Most likely: 3 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

Michelsen's superior serve and return indices give him a distinct edge, particularly in a high-stakes Grand Slam setting. A key factor to observe will be how each player manages pressure moments, especially during crucial service games that could decide the match outcome.

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