Hugo Nys / Edouard Roger-Vasselin vs Daniel Evans / Henry Searle prediction for July 1, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Daniel Evans / Henry Searle 0 - Hugo Nys / Edouard Roger-Vasselin 0. Hugo Nys / Edouard Roger-Vasselin is favored with a 57.2% win probability.
Daniel Evans / Henry Searle
1500
Grass Elo
VS
Grass • ATP
Hugo Nys / Edouard Roger-Vasselin
1500
Grass Elo
Match Win Probability
Daniel Evans / Henry SearleHugo Nys / Edouard Roger-Vasselin
Grass
Surface
ATP Wimbledon Doubles
Tournament
10,000
Simulations
Calibrated accuracy at this confidence: 54.4% (6,507 games)
Match Context
Tournament
ATP Wimbledon Doubles
Surface
Grass
Format
Best of 5 · ATP
Surface Elo Ratings (Grass)
Hugo Nys / Edouard Roger-Vasselin
Daniel Evans / Henry Searle
Hugo Nys / Edouard Roger-Vasselin leads by 0 Elo points on Grass
Serve & Return Analysis
Serve Points Won % (SPW) is the single most predictive metric in tennis. ATP average on Grass: 63.5%
Hugo Nys / Edouard Roger-Vasselin SPW
65.6%
Above tour avg
Daniel Evans / Henry Searle SPW
65.6%
Above tour avg
● Serve statistics are nearly identical — expect a close match
Market Odds & Model Edge
Hugo Nys / Edouard Roger-Vasselin ML
-498
Model: 57%
Edge: -26.1%
Daniel Evans / Henry Searle ML
+366
Model: 43%
Edge: +21.4%
Model Projection
Daniel Evans / Henry Searle ML +366 · +21.4% edge
Key Matchup Factors
- Players are closely matched (0-point Elo gap)
- Grass surface amplifies serve advantage — expect fewer breaks, more tiebreaks
- Daniel Evans / Henry Searle has the stronger serve profile on this surface
Surface Elo v1.0 · Barnett-Clarke serve model · 10,000 simulations · ATP
Edge Analysis
Moneyline
Hugo Nys / Edouard Roger-Vasselin 57.2%
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How this prediction was generated: This page shows output from the Olympus Bets ATP/WTA Tennis Monte Carlo engine. Each game is simulated 10,000 times using real-time team data, injury reports, and current odds. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →