Highlights

• • Bookmaker-implied probability for Julia (1.09) ≈ 91.7%; our estimate ≈ 32%
• • To be +EV on Julia we'd need decimal odds ≥ 3.125, well above current 1.09

Pros

• + We are conservative: our model is anchored to documented career record and recent form
• + Avoids wagering into a clear negative-expectation market price

Cons

• - Limited information on the home player (Isabeli) prevents detection of hidden value on the underdog
• - If there are unpublished factors (injury to Julia, walkover, etc.) our assessment could be off

Details

We estimate Julia Konishi Camargo Silva's true win probability materially below the market-implied price. Julia's career record (10-22, ~31% win rate) and clearly poor recent form suggest a realistic win probability around 32%, not the ~91.7% implied by the 1.09 decimal. Using our probability, a bet on Julia at 1.09 yields a large negative expectation. The home player (Isabeli Andreola) lacks publicly provided data in the research, increasing uncertainty; the large underdog price (7.0) could look attractive only if we believed her win chance was substantially higher than ~14.3%, but we lack evidence to justify that. Given the disconnect between the bookmaker price and our conservative estimate, there is no positive expected value on either side at the quoted odds, so we recommend no bet.

Key factors

• • Julia's career win rate is low (10-22, ~31%), indicating a true probability well below the market-implied 91.7%
• • Recent match results in the research show multiple recent losses, reinforcing downward form momentum
• • No reliable data provided for Isabeli Andreola, increasing uncertainty and preventing confident backing of the 7.0 underdog