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Anastasia Abbagnato vs Nanari Katsumi

Tennis
2025-09-11 13:09
Start: 2025-09-11 13:02

Summary

Pick: away
EV: 0.56

Current Odds

Home 1.45|Away 47.28
Best Odds

Match Info

Match key: Anastasia Abbagnato_Nanari Katsumi_2025-09-11

Analysis

Summary: Given near-parity in form and no injury or surface edge, the away price of 3.25 looks mispriced versus our ~48% win estimate, producing attractive EV.

Highlights

  • Market implies ~77% for home which is implausible given available data
  • Away at 3.25 offers substantial positive EV under a conservative 48% win estimate

Pros

  • + Clear positive EV at current odds
  • + Simple, conservative model based on parity and absent negative info

Cons

  • - Limited distinguishing data and no H2H or venue context increases model risk
  • - Bookmaker margin and unknown factors (e.g., travel, late injury) could flip value

Details

Both players present nearly identical profiles (10-21 records, similar recent results and surface history) with no injury or H2H edge reported. Market prices, however, make the home player a heavy favorite at 1.30 (implied ~77% win chance), which is difficult to justify given the parity in profiles and recent form. We estimate the away player has a near-even chance (~48%) to win; at current decimal odds of 3.25 this represents positive expected value (EV = 0.48 * 3.25 - 1 = 0.56). The required fair odds for that probability would be ~2.083, so the market price of 3.25 is a clear mispricing opportunity under our model. We remain cautious due to limited distinguishing data and potential bookmaker margin, but the current away price offers significant value versus our probability estimate.

Key factors

  • Nearly identical career records and recent form for both players (no clear performance edge)
  • No reported injuries or conditioning differences in the research provided
  • Bookmaker market heavily favors the home player at 1.30 despite parity
  • Surface history (clay/hard) similar for both, offering no tactical advantage
  • Lack of H2H or additional contextual data increases uncertainty