Wimbledon Wimbledon, GBR Grass Grand Slam Quarterfinals

Linda Noskova vs Elise Mertens: AI Prediction | Games, Spread, Aces & Double Faults

Linda Noskova

Rank: #12
58%
VS

Elise Mertens

Rank: #27
42%
Expected Total Games: 24.2
Predicted Winner: Linda Noskova

Why the Model Favors Linda Noskova

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

Age +2.9 Linda Noskova
Recent record by level +2.5 Linda Noskova
Fatigue & recent workload +2.2 Linda Noskova
Surface fit +1.5 Elise Mertens
Overall strength +1.2 Linda Noskova

Starting from an even matchup, these factors move the model to 58% for Linda Noskova. Computed with gradient-based attribution on our neural network — not editorial opinion. How to read this →

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Player Metrics

Linda Noskova

Form Index: 60.6
ELO Rating: 1983.5
Glicko2 Rating: 1925.8
Current Fatigue (minutes): 480.0
Surface Strength:
Hard: 48.5
Clay: 32.0
Grass: 56.8
Serve Rating: 97.3
Return Rating: 91.2

Elise Mertens

Form Index: 63.3
ELO Rating: 1869.9
Glicko2 Rating: 1830.0
Current Fatigue (minutes): 480.0
Surface Strength:
Hard: 40.6
Clay: 28.6
Grass: 51.7
Serve Rating: 96.1
Return Rating: 88.2

Recent Matches

Linda Noskova

  • Last Match: vs Madison Keys (2-0) grass Wimbledon 120 min
  • 2nd Last Match: vs Sorana Cirstea (2-1) grass Wimbledon 120 min
  • 3rd Last Match: vs Camila Osorio (2-1) grass Wimbledon 120 min
  • 4th Last Match: vs Ella Seidel (2-0) grass Wimbledon 120 min
  • 5th Last Match: vs Elena-Gabriela Ruse (0-2) grass Bad Homburg 61 min

Elise Mertens

  • Last Match: vs Marie Bouzkova (2-0) grass Wimbledon 120 min
  • 2nd Last Match: vs Elena Rybakina (2-0) grass Wimbledon 120 min
  • 3rd Last Match: vs Maria Timofeeva (2-1) grass Wimbledon 120 min
  • 4th Last Match: vs Laura Siegemund (2-0) grass Wimbledon 120 min
  • 5th Last Match: vs Naomi Osaka (0-2) grass Bad Homburg 67 min

Head-to-Head (Last 2 Seasons)

0
Linda Noskova
vs
0
Elise Mertens
Hard
0 - 0
Clay
0 - 0
Grass
0 - 0

Key Prediction Insights

Quarterfinals at Wimbledon in London set up a compelling grass-court clash between Linda Noskova and Elise Mertens. The model backs Linda Noskova to win (57.98% probability) over Elise Mertens (42.02%), with an expected total of about 24.2 games in the match.

Match Analysis

The model’s edge for Noskova stems primarily from age and recent-level form: younger age and solid recent results push the forecast her way. Noskova is the higher-ranked player (No. 12 vs No. 27), carries a higher Elo (1983.5 to 1869.9) and a strong form index (60.65) through three straight wins at this Wimbledon. Her surface strength index (56.8) and mean return index (91.23) suggest she handles grass returns well. Mertens, meanwhile, arrives with a slightly higher form index (63.26) and pedigree, but a lower Elo and surface index (51.74) that temper her upside on grass. Fatigue and recent workload also favor Noskova in the model — despite both players logging the same cumulative minutes (480) this tournament, Noskova’s path included tough three-set wins early and a straight-sets victory over Madison Keys in the last round, indicating resilience. Mertens has been consistent too: three wins at Wimbledon, including a straight-sets victory over Elena Rybakina, but the model marks surface fit as a modest advantage for Mertens (1.5 percentage points) given her experience and flat-hitting style on faster courts. Serve and return profiles are close: Noskova’s mean serve index (97.30) edges Mertens (96.08) but not by a large margin, and return indexes are not separated by more than five points.

Total Games Predictions

🎾
Expected Total Games in Match 24.2 Most likely outcome: 24 games

📊 Total Games Probability Distribution

Distribution

Probability of each total games outcome

Probability distribution chart for total games in Linda Noskova versus Elise Mertens. 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 Linda Noskova versus Elise Mertens. The curve rises from 0% to 100%, showing the cumulative probability for each games total threshold.

Games Spread Predictions

📈
Expected Games Spread (Linda Noskova - Elise Mertens) +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 Linda Noskova versus Elise Mertens. Positive values indicate Linda Noskova winning more games, negative values indicate Elise Mertens winning more games.
Cumulative Probability (CDF)

Probability of spread ≤ X

Cumulative distribution function chart for games spread in Linda Noskova versus Elise Mertens. The curve shows the cumulative probability for each spread threshold.

Aces and Double Faults Predictions

The aces prediction for the tie is moderate — a predicted aces total of 9.1 — reflecting grass as the fastest surface where serve rewards are higher. The double faults prediction (expected double faults 8.53) is also notable; both players carry strong serve metrics but neither posts a significantly higher serve rating, so the ace count should be shared rather than dominated by one server. On grass, these serve outcomes will weigh heavily on pivotal games.
🎯
Expected Total Aces 9.1 Most likely: 9 aces
Expected Total Double Faults 8.5 Most likely: 8 double faults

🎯 Aces Probability Distribution

Distribution

Probability of each ace count outcome

Probability distribution chart for total aces in Linda Noskova versus Elise Mertens. 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 Linda Noskova versus Elise Mertens. 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 Linda Noskova versus Elise Mertens. 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 Linda Noskova versus Elise Mertens. 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

32.2% Predicted: No tiebreak

Exact Score Distribution BO3

Probability of each set-by-set outcome (Linda Noskova's perspective)

2-0 Most likely set score (33.8%)
Probability distribution of the final set score from Linda Noskova's perspective. Format: BO3.

Final Prediction

Noskova’s projected edge comes mainly from age and recent-level performance, supported by a superior Elo and slightly better surface and return indices. The key factor to watch is how both handle serve moments on grass — clean service games and few double faults will decide who advances.

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