Highlights

• • Market strongly favors Kraus (1.426), but our relative-strength model finds a slight edge on Burillo at 2.68
• • Estimated ROI is small (~2.0%) and comes with high uncertainty because Burillo's career sample is small

Pros

• + Home price (2.68) is slightly higher than the fair price implied by our model (min required ~2.627)
• + Clear, transparent methodology using the available career win-rate data

Cons

• - Very small edge — vulnerable to volatility and match-specific factors not present in the provided data
• - Burillo's limited career sample and recent results increase model uncertainty (higher downside risk)

Details

We base our probability model on the two players' career win rates provided. Sinja Kraus has a long track record (559–507, win rate ≈52.5%) while Irene Burillo Escorihuela has a much smaller sample and weaker record (10–21, win rate ≈32.3%). Converting those win rates into a relative-probability model (p_home = WR_home / (WR_home + WR_away)) yields an estimated true probability for Burillo of ~38.1%. The market odds (Home 2.68, Away 1.426) imply probabilities of ~37.3% and ~70.1% respectively. Our estimate for Burillo (≈38.1%) is slightly higher than the market-implied probability for the home player (≈37.3%), producing a small positive edge. Using the current home decimal price (2.68) we calculate EV = 0.38068 * 2.68 - 1 ≈ 0.020 (2.0% ROI on a 1-unit stake). We note high uncertainty because Burillo's career sample is very small and recent form shown in the research is poor for both players; therefore this is a marginal, higher-risk value opportunity rather than a strong play.

Key factors

• • Large difference in career sample sizes and overall records (Kraus much more experienced)
• • Relative win-rate model gives Burillo ~38.1% chance vs market-implied ~37.3%
• • High uncertainty due to Burillo's small match sample and mixed recent form for both players