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Fumin Jiang vs Chase Ferguson

Tennis
2025-09-08 13:36
Start: 2025-09-09 02:30

Summary

Pick: away
EV: 0.176902

Current Odds

Home 2.19|Away 1.629
Best Odds

Match Info

Match key: Fumin Jiang_Chase Ferguson_2025-09-09

Analysis

Summary: Chase Ferguson represents value at 1.667 based on a higher career win rate and more hard-court experience; our model estimates ~70.6% win probability giving ~17.7% ROI at current odds.

Highlights

  • Away (Ferguson) implied win probability required to break even: 60.0% — our estimate is ~70.6%
  • Market price (1.667) is considerably above the minimum fair odds (1.416) implied by our estimate

Pros

  • + Positive expected value at current widely-available price
  • + Clear experience and sample-size advantage for Ferguson on hard courts

Cons

  • - Small-sample data for Jiang and limited recent-match detail increase uncertainty
  • - Recent individual match-level stats provided are noisy and do not include head-to-head or injury info

Details

We see clear value on Chase Ferguson (away). Fumin Jiang has a very limited record (1-4) on hard this season and appears outmatched in experience and win rate. Chase has played far more matches (13-14 record) and more hard-court events, making him the stronger and more battle-tested player here. Using a simple relative-strength conversion from career records (0.48 win rate for Ferguson vs 0.20 for Jiang) we estimate Ferguson's win probability at roughly 0.706. At the market decimal price of 1.667 this implies positive expected value (EV = 0.706*1.667 - 1 ≈ 0.177). The away price is well above the break-even decimal (1 / 0.706 ≈ 1.416), so we recommend taking the away moneyline at current odds while noting small-sample and recent-form noise.

Key factors

  • Chase Ferguson has a substantially larger match sample (27 matches) and higher win rate (13-14) versus Fumin Jiang (5 matches, 1-4)
  • Both players have hard-court experience, but Ferguson's broader recent match history on hard gives an edge
  • Small sample for Jiang and noisy recent stats increase variance — modelled via conservative relative-strength conversion