Highlights

• • Market implies ~85.5% for the away favorite (1.17); we estimate ~82%
• • Both sides fail to clear a +EV threshold given our conservative probabilities

Pros

• + Avoids wagering when the market price suggests no clear edge
• + Conservative approach limits exposure to model/knowledge risk

Cons

• - If our conservative probability underestimates Wolff substantially, value might exist on the favorite
• - Lack of match-specific data increases uncertainty; this is a conservative non-bet rather than a targeted opportunity

Details

We have no external data beyond the posted prices, so we apply a conservative prior. The market prices imply P(away) = 1/1.17 = 85.47% and P(home) = 1/4.5 = 22.22% (they sum >100% due to rounding/juice). Given the extreme favorite price for Vivian Wolff (1.17), to beat the market price we'd need to believe her true win probability exceeds ~85.5%. Conservatively we estimate Vivian Wolff's true win probability at 82% (0.82) and Dasha Ivanova at 18% (0.18) based on the imbalance and lack of corroborating information. At p=0.82 the expected value on the away moneyline 1.17 is 0.82*1.17 - 1 = -0.041 (a loss of ~4.1% per unit), so the price does not offer value. Similarly, the underdog price 4.50 requires a true win probability >22.22% to be +EV; our conservative 18% estimate is below that threshold, so the underdog also lacks value. Therefore we recommend no bet.

Key factors

• • No independent data available; using conservative prior probabilities
• • Market implies Vivian Wolff is ~85.5% likely to win (1.17), which requires a true edge to bet
• • Underdog would need >22.2% true win chance to be +EV at 4.50; our estimate is below that