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Yafan Wang vs Caty Mcnally

Tennis
2025-09-12 18:29
Start: 2025-09-13 02:00

Summary

Pick: home
EV: 0.231

Current Odds

Home 67|Away 1.031
Best Odds

Match Info

Match key: Yafan Wang_Caty Mcnally_2025-09-13

Analysis

Summary: We recommend a value bet on Yafan Wang at 2.62 — our model estimates a 47% win probability versus the market-implied 38%, producing ~23% ROI.

Highlights

  • Market-implied probability for Wang: ~38.2%; our estimate: 47%
  • Positive EV of ~0.231 (23.1% ROI) at current odds 2.62

Pros

  • + Price margin is large versus our estimated true probability
  • + No evidence in the research to justify the market favoritism toward McNally

Cons

  • - Available data is limited and truncated; uncertainty around form/context increases variance
  • - Both players have poor recent records (10-21), increasing upset volatility in qualifiers

Details

We find value backing Yafan Wang at 2.62. The research shows both players with nearly identical career records (10-21) and similar recent form, suggesting this is closer to an even matchup than the market price implies. The book market prices Caty McNally at 1.498 (≈66.8% implied) and Wang at 2.62 (≈38.2% implied). Given the lack of a clear differentiator in the available data (surface experience is similar, no injury or H2H evidence favoring McNally), we assess Wang's true win probability substantially above the market-implied 38%. We estimate Wang's true probability at 47%, which produces positive expected value at the quoted 2.62 price. EV calculation: 0.47 * 2.62 - 1 = 0.231 (23.1% ROI). Minimum fair odds to justify a bet at our estimated probability are 2.128; the current 2.62 exceeds that threshold, so the selection is value-driven.

Key factors

  • Both players show nearly identical career records and recent form in the provided data (10-21), indicating a closer matchup than market pricing
  • Market strongly favors McNally (1.498) which implies ~66.8% — we view this as overstated given available evidence
  • No reported injuries, surface advantage, or head-to-head edge in the provided research to justify the market gap