| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Sebastian Baez | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Vilius Gaubas | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks which player will win the first set in the Sebastian Báez vs Vilius Gaubas match; first-set outcomes often shape live match dynamics and early in-play markets.
Sebastian Báez is an established tour player known for consistent baseline play and match experience on the professional circuit, while Vilius Gaubas is a younger player often described as a rising prospect with an aggressive style. Their head-to-head history and recent form can differ depending on surface and tournament level, so first-set dynamics may reflect short-term form as much as overall ability.
Market odds are the crowd’s aggregated view of who is most likely to take the first set and will update as new information arrives; interpret them as a summary of current expectations and market sentiment rather than a fixed prediction.
The market resolves in favor of whichever player is recorded as winning the first completed set on the official match scoreboard; if the set is decided by a tiebreak, the tiebreak winner counts as the set winner.
The listed close time is TBD; typically these markets close at or shortly before first serve, so check the market page for the exact close and any updates before the match begins.
Resolution follows the tournament’s official result and the platform’s rules: if a player withdraws before play starts markets are commonly voided, while retirements during the match are handled according to whether the first set was completed and by the market operator’s specific policies—check KALSHI’s resolution rules for final determination.
Monitor both players’ warm-up reports, recent first-set records in their last several matches, any reported niggles or travel fatigue, head-to-head set-level notes if available, and the announced court/surface for the fixture.
Head-to-head is useful but often limited by small sample sizes and differing contexts; focus on set-level results, surfaces, and recent form rather than relying solely on overall meetings to predict the first set.