Highlights

• • Saye listed at 1.26 (implied ~79%); our conservative estimate: 72%.
• • No value for either side at current prices given the uncertainty.

Pros

• + We adopt a conservative probability to avoid overreacting to bookmaker short prices.
• + Avoids wagering on a market where sample data is insufficient and uncertainty high.

Cons

• - If Saye is underpriced by the market (true chance >>72%), we may be passing on value.
• - Lack of any profile for Nathan Gold in research increases uncertainty and reduces precision.

Details

We see bookmakers make David Saye a heavy favorite at 1.26 (implied ~79%). The only player-specific data available is Saye's extremely small pro sample (1-1, two matches on hard). With such limited direct evidence and no profile for Nathan Gold in the research, we conservatively estimate Saye carries a clear edge but discount the bookmaker's extremity to account for sample size and uncertainty. Using a 72% win probability for Saye (28% for Nathan) produces negative expected value on Saye at 1.26 (EV ≈ -0.093) and also no exploitable value on Nathan at 3.55 (home implied 28.2% ≈ our home estimate). Given the sparse data and the market pricing, there is no positive expected value at the quoted prices, so we recommend no wager.

Key factors

• • Very limited professional match data available (only Saye: 2 matches, 1-1 on hard).
• • Bookmakers price Saye strongly (1.26), implying ~79% win chance.
• • High uncertainty due to tiny sample sizes and no data on Nathan Gold in the research.