MaxBetto
< Back

Selina Atay vs Vivien Sandberg

Tennis
2025-09-11 00:40
Start: 2025-09-11 09:00

Summary

Pick: home
EV: 0.01

Current Odds

Home 1.85|Away 1.962
Best Odds

Match Info

Match key: Selina Atay_Vivien Sandberg_2025-09-11

Analysis

Summary: We see a marginal value on Selina Atay at 2.02 versus our 50% win estimate (fair price 2.00), yielding ~1% EV; this is a small, low-margin opportunity sensitive to estimation error.

Highlights

  • Market offers Selina Atay at 2.02 while our fair price is ~2.00
  • Edge is very small (~1% ROI) and relies on a symmetric assessment of both players

Pros

  • + Decimal price (2.02) is slightly above our fair threshold (2.00)
  • + Simple, conservative model driven by mirrored player profiles reduces overfitting risk

Cons

  • - EV is very small and easily negated by slight misestimation or line movement
  • - Limited and similar data for both players (no H2H, surface or injury edge) increases uncertainty

Details

Both players present nearly identical profiles (10-21 records, similar surfaces and recent form) with no clear injury or H2H edge in the supplied research. Given symmetry, we estimate a true win probability close to 50% for each player. The market prices Selina Atay (home) at 2.02 (implied 49.5%) and Vivien Sandberg (away) at 1.699 (implied 58.9%). Using a 50% true probability, the fair decimal price is 2.00. The available home price of 2.02 exceeds that fair price, producing a small positive expected value (EV) of +0.01 (1% ROI) on a 1-unit stake. The edge is marginal and sensitive to small errors in our probability estimate and the bookmaker overround, so this is a low-margin value play rather than a strong advantage.

Key factors

  • Both players show nearly identical career records and recent form in the provided data
  • No injuries, surface advantages, or H2H information present to create a clear edge
  • Market prices give the home player a slight overlay vs our 50% fair estimate (2.02 vs 2.00)
  • Bookmaker overround (market implied probabilities >100%) increases sensitivity to estimation error