David Qariaqus vs Chen Dong
Summary
Current Odds
Match Info
Analysis
Summary: We find clear value on the home player (David Qariaqus) because Chen Dong's documented win rate (~38.9%) is far below the market-implied probability for the favorite; the home price 6.25 implies a ~61.1% true win chance and yields large positive EV.
Highlights
- • Chen's documented career win-rate (38.9%) is inconsistent with a 1.10 market price.
- • At 6.25 for the home side, implied EV is strongly positive using the conservative probability estimate.
Pros
- + Large pricing discrepancy creates substantial theoretical edge at current odds.
- + Simple, transparent probability basis derived from the only available player data.
Cons
- - No direct data on David Qariaqus in the provided research — our estimate for him is a complement and subject to uncertainty.
- - Small sample size for Chen's career and limited recent-match detail reduce confidence in the precise probability estimate; market may reflect unobserved factors (injury, travel, late info).
Details
We estimate Chen Dong's true win probability based on his documented career record (7 wins in 18 matches = 38.9%), which implies the market price of 1.10 (≈90.9% implied) is extremely short relative to observable form. Treating the match as a two-player contest, the complement gives David Qariaqus an estimated true win probability of ~61.1%. At the available moneyline of 6.25 for the home player, that probability produces strong positive expectation. The core value comes from the large mismatch between Chen's documented win rate and the market-implied probability; however, this view is conditional on no additional information about David (we have no independent data on him in the provided research) and assumes match probability sums to 1 with no outside adjustments.
Key factors
- • Chen Dong career win-rate 7/18 (38.9%) - indicates weak baseline form
- • Market price for Chen is 1.10 (≈90.9% implied) — large discrepancy vs documented form
- • We have no independent data on David Qariaqus in the provided research, so we use probability complement (1 - Chen) to estimate David