| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Gabriel Diallo | 0% | 1¢ | 99¢ | — | $0 | Trade → |
| Andrey Rublev | 0% | 1¢ | 99¢ | — | $0 | Trade → |
This market forecasts which player will win the second set of the tennis match between Andrey Rublev and Gabriel Diallo. It matters for traders and bettors who focus on in-match swings and set-level outcomes rather than the final match result.
Andrey Rublev is a well-established tour player with extensive experience in best-of-three matches, while Gabriel Diallo is a younger professional seeking to upset higher-ranked opponents. Surface, match context (e.g., tournament round), and recent form for both players can materially affect how the second set plays out.
Market odds reflect the collective, real-time view of participants about who will win set 2 and will move as match events occur. Treat the market as a dynamic signal—useful for gauging sentiment but not a substitute for match observation or official results.
The outcome is the player who is officially recorded as winning the second set by the tournament's scorers; if Set 2 is decided by a tiebreak, the tiebreak winner is the set winner.
If Set 2 is not played or not completed, the market will be settled according to the exchange's official resolution policy using the tournament's official match records; consult the platform's rules for exact handling of retirements and walkovers.
Yes—breaks of serve, injuries, momentum shifts and clear tactical changes in Set 1 typically move the market quickly, as participants update expectations for Set 2 in real time.
If the second set reaches a tiebreak, the player who wins that tiebreak is credited with winning Set 2 and the market settles to that official result.
Market closure is tied to the match timeline and will occur once Set 2 is completed and the official result is posted by tournament scorers; because match timings vary, the listing may show 'closes: TBD' until the event proceeds and the platform receives official data.