Highlights

• • Current home price 2.95 requires ≥33.9% true win chance to be profitable; we estimate 35.0%
• • Positive but small expected value (≈0.0325 per 1 unit staked)

Pros

• + Market strongly discounts the underdog, creating potential value if true win chance slightly exceeds implied threshold
• + Conservative probability estimate avoids overclaiming in absence of match-specific data

Cons

• - Edge is small and sensitive to the probability estimate; limited information increases model risk
• - Favorite at 1.35 would be profitable only with a very high true probability (>74%), which we cannot justify

Details

Market prices make Tom Zeuch a strong favorite at 1.35 (implied ~74.1%) while Filip Kosinski is priced at 2.95 (implied ~34.0%). No external data was available, so we adopt conservative assumptions: limited information increases uncertainty and raises the chance of underdog outcomes in tennis. We estimate Kosinski's true win probability at 35.0%, which is marginally above the break-even threshold for the available home price. At our estimate the required break-even probability for the home price (2.95) is 33.898% (1/2.95), so backing Kosinski at 2.95 yields a small positive edge. We use the current decimal odds for the EV calculation (odds_used_for_ev = 2.95). Given the lack of specific injury, surface, form, or H2H data, our model deliberately leans conservative and only claims a small value edge rather than a large one.

Key factors

• • Market strongly favors the away player (short favorite), creating potential value on the underdog
• • No match-specific data available — we apply conservative uncertainty and slight uplift for upset probability
• • Breakeven threshold for backing home at 2.95 is ~33.9%; our conservative estimate of 35.0% is just above that