Wimbledon Great Britain Grass Grand Slam Round of 128

Alex Michelsen vs Jacob Fearnley: AI Prediction | Games, Spread, Aces & Double Faults

Alex Michelsen

Rank: #46
68%
VS

Jacob Fearnley

Rank: #159
32%
Expected Total Games: 36.2
Predicted Winner: Alex Michelsen

Why the Model Favors Alex Michelsen

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

Overall strength +8.7 Alex Michelsen
Surface fit +6.8 Alex Michelsen
Overall record & opposition quality +3.3 Alex Michelsen
Fatigue & recent workload +2.8 Alex Michelsen
Recent record by level +2.0 Jacob Fearnley

Starting from an even matchup, these factors move the model to 68% for Alex Michelsen. Computed with gradient-based attribution on our neural network — not editorial opinion. How to read this →

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Player Metrics

Alex Michelsen

Form Index: 39.6
ELO Rating: 1732.0
Glicko2 Rating: 1777.0
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 33.6
Clay: 18.6
Grass: 14.1
Serve Rating: 96.4
Return Rating: 93.1

Jacob Fearnley

Form Index: 34.1
ELO Rating: 1497.0
Glicko2 Rating: 1490.4
Current Fatigue (minutes): 0.0
Surface Strength:
Hard: 16.7
Clay: 18.8
Grass: 8.7
Serve Rating: 94.7
Return Rating: 88.0

Recent Matches

Alex Michelsen

Jacob Fearnley

Head-to-Head (Last 2 Seasons)

0
Alex Michelsen
vs
0
Jacob Fearnley
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

At Wimbledon in Great Britain, Round of 128 on grass, the model projects Alex Michelsen to prevail over Jacob Fearnley. The predicted winner is Alex Michelsen (67.54%); Jacob Fearnley is given a 32.46% chance. The model forecasts about 36.16 total games in the match.

Match Analysis

The model's edge for Michelsen comes mainly from his overall strength (+8.7 percentage points) and his better surface fit on grass (+6.8). Michelsen is the higher-ranked player (No. 46 vs No. 159), carries a higher Elo (1729.8 vs 1497.0) and a stronger form index (39.36 vs 33.76), which supports the overall-strength advantage. His surface strength index (14.06) also exceeds Fearnley’s (8.73), aligning with the surface-fit lift in the model. Fatigue is neutral for both (0.0 minutes on court in this event), but the model still credits Michelsen a small workload advantage (+2.8). Looking at the serving and returning profiles, both players have high serve indexes (Michelsen 96.41, Fearnley 94.70); the difference is small and not a decisive gap. Michelsen’s mean return index (93.11) is roughly five points higher than Fearnley’s (88.01), a noticeable edge that helps explain his break potential on quick grass courts. Recent form: Michelsen has two wins and a five-set loss at Roland Garros in his last three matches; he showed resilience in earlier rounds. Fearnley is 1–2 in his last three, including a straight-sets defeat at Roland Garros and a prior loss in Rome, which the model treats as a modest negative (-2.0 toward Fearnley for recent record by level).

Total Games Predictions

🎾
Expected Total Games in Match 36.2 Most likely outcome: 36 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Alex Michelsen versus Jacob Fearnley. 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 Alex Michelsen versus Jacob Fearnley. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Alex Michelsen - Jacob Fearnley) +2.8 Most likely spread: +2 (Alex Michelsen wins 2 more games)

📊 Games Spread Probability Distribution

Distribution

Probability of each games spread outcome

Probability distribution chart for games spread in Alex Michelsen versus Jacob Fearnley. Positive values indicate Alex Michelsen winning more games, negative values indicate Jacob Fearnley winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Alex Michelsen versus Jacob Fearnley. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

The aces prediction for this grass match is 16.54 total; the predicted aces reflect grass’s favoring of big servers. The double faults prediction sits at 11.13 expected double faults overall. With both players posting strong serve indices, the expected aces are elevated but there’s not a single server far above the other to drive a lopsided ace count.
🎯
Expected Total Aces 16.5 Most likely: 16 aces
Expected Total Double Faults 11.1 Most likely: 11 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Alex Michelsen versus Jacob Fearnley. 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 Alex Michelsen versus Jacob Fearnley. 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 Alex Michelsen versus Jacob Fearnley. 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 Alex Michelsen versus Jacob Fearnley. 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

41.9% Predicted: No tiebreak

Exact Score Distribution BO5

Probability of each set-by-set outcome (Alex Michelsen's perspective)

3-0 Most likely set score (30.9%)
Probability distribution of the final set score from Alex Michelsen's perspective. Format: BO5.

Final Prediction

Michelsen’s edge stems primarily from his overall strength metric, reinforced by better surface fit on grass. Watch his return performance and ability to convert break chances—those factors should decide whether the forecasted 67.5% outcome becomes reality.

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