Guido Andreozzi / Manuel Guinard vs Romain Arneodo / Valentin Vacherot prediction for April 30, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects Romain Arneodo / Valentin Vacherot 0 - Guido Andreozzi / Manuel Guinard 0. Romain Arneodo / Valentin Vacherot is favored with a 54.5% win probability.
Romain Arneodo / Valentin Vacherot
1500
Clay Elo
VS
Clay • ATP
Guido Andreozzi / Manuel Guinard
1500
Clay Elo
Match Win Probability
Romain Arneodo / Valentin VacherotGuido Andreozzi / Manuel Guinard
Clay
Surface
ATP Madrid - Doubles
Tournament
10,000
Simulations
Calibrated accuracy at this confidence: 58.6% (1,386 games)
Match Context
Tournament
ATP Madrid - Doubles
Surface
Clay
Format
Best of 3 · ATP
Surface Elo Ratings (Clay)
Guido Andreozzi / Manuel Guinard
Romain Arneodo / Valentin Vacherot
Guido Andreozzi / Manuel Guinard leads by 0 Elo points on Clay
Serve & Return Analysis
Serve Points Won % (SPW) is the single most predictive metric in tennis. ATP average on Clay: 63.5%
Guido Andreozzi / Manuel Guinard SPW
60.1%
Below tour avg
Romain Arneodo / Valentin Vacherot SPW
60.3%
Below tour avg
● Serve statistics are nearly identical — expect a close match
Market Odds & Model Edge
Guido Andreozzi / Manuel Guinard ML
-153
Model: 46%
Edge: -15.0%
Romain Arneodo / Valentin Vacherot ML
+126
Model: 54%
Edge: +10.2%
Model Projection
Romain Arneodo / Valentin Vacherot ML +126 · +10.2% edge
Key Matchup Factors
- Players are closely matched (0-point Elo gap)
- Clay surface reduces serve dominance — expect more breaks of serve and longer rallies
- Romain Arneodo / Valentin Vacherot has the stronger serve profile on this surface
Surface Elo v1.0 · Barnett-Clarke serve model · 10,000 simulations · ATP
Edge Analysis
Moneyline
Romain Arneodo / Valentin Vacherot 54.5%
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More Projections Today
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. Full methodology →