| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Nuno Borges | 53% | 53¢ | 98¢ | — | $2 | Trade → |
| Emilio Nava | 0% | 39¢ | 98¢ | — | $0 | Trade → |
This market predicts which player will win the first set in the match between Nuno Borges and Emilio Nava. First-set markets matter because the opening set often sets momentum and is a short-term trading opportunity tied closely to serve, form, and match conditions.
Nuno Borges and Emilio Nava are touring professional tennis players who meet in a best-of-sets match; the event-level context (tournament stage, court surface, and conditions) can shift the balance between them. Both players’ recent form, match load, and any pre-match injury or withdrawal information are relevant background factors to check before trading or placing a position.
Market prices reflect the collective expectation for who will win set 1 and update as new information (lineups, injuries, weather, warm-up reports) arrives. Treat prices as indicators of consensus sentiment that can move quickly around match start.
The market's close time is listed as TBD for this event; on many platforms such markets close around the scheduled start of the first set or at first ball — check the KALSHI event page for the exact, up-to-date closing timestamp.
The outcome is determined by the official match score for the first set as recorded by tournament officials — if the set is decided by a tiebreak, the tiebreak winner is the set winner; resolution follows the official result.
Resolution in those cases follows KALSHI's event rules: if no official first-set result is produced, the platform’s stated settlement policy applies (which may void or resolve the market); always consult the event rules on the platform for specifics.
Check the confirmed match start time, warm-up reports, last-minute withdrawals/injury news, official lineups, surface type, weather/wind, and recent first-set performance for each player — these tend to move short-term prices.
Head-to-head can reveal matchup tendencies, but small sample sizes and differing surfaces/conditions reduce its predictive power; prioritize recent, surface-specific first-set form and current fitness alongside any H2H insights.