Highlights

• • Implied probability for Gamble at 1.17 is ~85.5%, which we consider overstated
• • Our estimated true win probability is ~65%, producing a negative EV at market odds

Pros

• + Gamble has recent hard-court match experience (matches recorded on hard)
• + Market confidence in Gamble may reflect public information not in our dataset

Cons

• - Insufficient sample size (only two recorded matches) creates high uncertainty
• - No information on the opponent prevents a justified tilt away from the bookmaker price

Details

We compare the market moneyline (Jon Gamble 1.17 implied ~85.5%) to our estimate of Jon Gamble's true win chance. Research shows Jon Gamble has an extremely small sample on record (two matches, 1-1) with hard-court play but no clear context about the opponent (Artem Alekseychuk) or recent form beyond those two results. Given the lack of opponent data and the tiny sample size, we remain cautious and assign a much lower true probability (65%) than the market implies. At the bookmaker price (1.17), backing Gamble produces a negative expected value (EV = 0.65*1.17 - 1 = -0.2395). The underdog line (4.6, implied ~21.7%) would require Artem to have a >21.7% true chance to be +EV; we have no evidence to support that despite the heavy favorite pricing. Therefore there is no value on either side at the current prices.

Key factors

• • Market heavily favors the home player (implied ~85.5%)
• • Very small sample size for Jon Gamble (2 matches) increases uncertainty
• • No opponent (Artem) data provided to justify the market split