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Hayato Matsuoka vs Leo Vithoontien

Tennis
2025-09-08 17:33
Start: 2025-09-09 01:00

Summary

Pick: away
EV: 0.556

Current Odds

Home 1.49|Away 39.72
Best Odds

Match Info

Match key: Hayato Matsuoka_Leo Vithoontien_2025-09-09

Analysis

Summary: We recommend the away (Leo Vithoontien) because the current price (2.77) appears to understate his win probability versus a career-win-rate based estimate, producing a large positive EV.

Highlights

  • Market prices favor home heavily despite Vithoontien having the better career win rate in the supplied data
  • At an estimated true win probability of ~56.2%, the away price 2.77 yields EV ≈ +0.556 (55.6% ROI)

Pros

  • + Clear numerical discrepancy between market odds and career-win-rate-based estimate
  • + Large positive EV at current widely-available price

Cons

  • - Data is limited: no head-to-head, limited surface-specific recent form in the provided research
  • - Small sample sizes and recent mixed results increase variance and model risk

Details

We find value backing Leo Vithoontien at the current away price (2.77). Market-implied probability for Hayato Matsuoka (home) at 1.407 is ~71%, which conflicts with the underlying career win rates in the supplied data: Matsuoka 14/40 (35.0%) vs Vithoontien 22/49 (≈44.9%). Normalizing those career win rates to a head-to-head estimate gives Vithoontien an estimated true win probability of ~56.2% while the market implies ~36% for the away side. Using that estimate, the away decimal price (2.77) yields a large positive expected value (EV ≈ 0.556 per unit staked). We note limited match-level detail (no direct H2H, sparse surface-specific form) which increases uncertainty, but on the available objective metrics the price on Vithoontien appears materially mispriced and offers strong value.

Key factors

  • Career win-rate normalization: Matsuoka 14/40 (35.0%) vs Vithoontien 22/49 (≈44.9%)
  • Market-implied probabilities diverge strongly from career-based estimate (away implied ≈36% vs our ≈56%)
  • Limited additional information (no H2H, sparse surface/form detail) increases uncertainty