Wimbledon Great Britain Grass Grand Slam Round of 64

Alejandro Davidovich Fokina vs Fabian Marozsan: AI Prediction | Games, Spread, Aces & Double Faults

VS

Fabian Marozsan

Rank: #53
43%
Expected Total Games: 36.8
Predicted Winner: Alejandro Davidovich Fokina

Why the Model Favors Alejandro Davidovich Fokina

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

Overall strength +6.0 Alejandro Davidovich Fokina
Serve & return game +5.8 Alejandro Davidovich Fokina
Recent form +2.1 Alejandro Davidovich Fokina
Head-to-head +2.0 Fabian Marozsan
Fatigue & recent workload +1.2 Alejandro Davidovich Fokina

Starting from an even matchup, these factors move the model to 57% for Alejandro Davidovich Fokina. Computed with gradient-based attribution on our neural network — not editorial opinion. How to read this →

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Player Metrics

Alejandro Davidovich Fokina

Form Index: 58.7
ELO Rating: 1779.1
Glicko2 Rating: 1773.8
Current Fatigue (minutes): 174.0
Surface Strength:
Hard: 29.9
Clay: 25.7
Grass: 32.9
Serve Rating: 96.7
Return Rating: 94.9

Fabian Marozsan

Form Index: 51.9
ELO Rating: 1651.4
Glicko2 Rating: 1692.1
Current Fatigue (minutes): 174.0
Surface Strength:
Hard: 24.0
Clay: 17.5
Grass: 17.2
Serve Rating: 96.2
Return Rating: 85.8

Recent Matches

Alejandro Davidovich Fokina

Fabian Marozsan

Head-to-Head (Last 2 Seasons)

1
Alejandro Davidovich Fokina
vs
0
Fabian Marozsan
Hard
0 - 0
Clay
0 - 0
Grass
1 - 0

Key Prediction Insights

At Wimbledon in London, Round of 64 on grass, Alejandro Davidovich Fokina is narrowly favoured over Fabian Marozsan in this grand slam meeting. The model projects Davidovich Fokina to win with a 56.94% probability to Marozsan’s 43.06%, and expects roughly 36.78 games in the match.

Match Analysis

The model’s edge for Davidovich Fokina is driven mainly by overall strength and the serve-and-return matchup. Davidovich sits 23rd in the rankings with an Elo of 1779.1 and a form index of 58.7; Marozsan is 53rd with an Elo of 1651.4 and a form index of 51.9. Fatigue is identical in the dataset (174 minutes on court for both), but the explainability engine still nudges Davidovich forward on cumulative workload. Surface strength index favors Davidovich (32.9) over Marozsan (17.2), suggesting Davidovich’s game translates better to grass in the model. Statistically the two have very similar serving profiles — mean serve indices are 96.72 (Davidovich) and 96.20 (Marozsan), a negligible gap — so neither gains a clear serving ace advantage. The larger difference is in return ability: Davidovich’s mean return index (94.95) comfortably outstrips Marozsan’s (85.83) by more than five points, and that is likely to produce more break opportunities on a fast surface. Over the last three matches Davidovich arrives unbeaten in this sample (wins in Mallorca and a straight-sets win in the Wimbledon opener), while Marozsan has two recent wins but dropped the Mallorca meeting to Davidovich — a nuance the model still offsets slightly in Marozsan’s favour on head-to-head, per the explainability output.

Total Games Predictions

🎾
Expected Total Games in Match 36.8 Most likely outcome: 36 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Alejandro Davidovich Fokina versus Fabian Marozsan. 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 Alejandro Davidovich Fokina versus Fabian Marozsan. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Alejandro Davidovich Fokina - Fabian Marozsan) +0.8 Most likely spread: 0 (even number of games won)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Alejandro Davidovich Fokina versus Fabian Marozsan. Positive values indicate Alejandro Davidovich Fokina winning more games, negative values indicate Fabian Marozsan winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Alejandro Davidovich Fokina versus Fabian Marozsan. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

The aces prediction for this grass match is relatively high: the model’s predicted aces total is 15.72. Given grass favors big, flat serving and quick points, a healthy ace count fits historical patterns. The double faults prediction (expected double faults) sits at 5.67 for the contest. Since neither player shows a significantly higher serve rating, the predicted aces are likely to be shared rather than dominated by one player.
🎯
Expected Total Aces 15.7 Most likely: 15 aces
Expected Total Double Faults 5.7 Most likely: 5 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Alejandro Davidovich Fokina versus Fabian Marozsan. 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 Alejandro Davidovich Fokina versus Fabian Marozsan. 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 Alejandro Davidovich Fokina versus Fabian Marozsan. Clay surface matches tend to produce more double faults due to fatigue in longer rallies.
Cumulative Probability (CDF)

Probability of double faults ≤ X

Cumulative distribution function chart for double faults in Alejandro Davidovich Fokina versus Fabian Marozsan. 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

37.0% Predicted: No tiebreak

Exact Score Distribution BO5

Probability of each set-by-set outcome (Alejandro Davidovich Fokina's perspective)

3-0 Most likely set score (27.6%)
Probability distribution of the final set score from Alejandro Davidovich Fokina's perspective. Format: BO5.

Final Prediction

Davidovich Fokina’s lead comes most from his overall strength metric and superior return index, which the model sees as decisive on grass. Key factor to watch: return points and break conversion — if Marozsan can neutralize Davidovich’s returns early, he can flip the close probability in his favour.

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