| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Trey Murphy III: 2+ | 43% | 39¢ | 43¢ | — | $28 | Trade → |
| Trey Murphy III: 1+ | 77% | 70¢ | 77¢ | — | $11 | Trade → |
| Trey Murphy III: 3+ | 0% | 13¢ | 20¢ | — | $0 | Trade → |
| Zion Williamson: 2+ | 0% | 1¢ | 55¢ | — | $0 | Trade → |
| Zion Williamson: 1+ | 0% | 0¢ | 86¢ | — | $0 | Trade → |
| Zion Williamson: 3+ | 0% | 1¢ | 25¢ | — | $0 | Trade → |
This market asks which steals outcome will occur in the Washington at New Orleans game; it matters because steals are a key defensive stat that can swing possessions and influence in-game momentum and payouts.
Steals are recorded when a defensive player legally takes the ball away from the opponent, and team totals reflect a combination of defensive scheme, individual quickness, and opponent ball security. Washington and New Orleans bring different defensive profiles and primary ball-handlers, so matchups, rotations, and recent form shape expectations heading into the contest.
Prices in this market summarize traders' aggregated expectations about the steals outcome and update as new information arrives (injuries, lineup changes, game tempo). Use the market as a real-time synthesis of available public information rather than a fixed prediction.
The close time is listed as TBD for this event; markets like this commonly close before tip-off or at a platform-specified moment. Check the KALSHI event page for the confirmed closing time before trading.
Whether overtime steals count depends on the market rules for this specific event—some markets include overtime and some do not. Confirm the event’s rule text on the platform to see if overtime is included.
The players who most influence steals are typically Washington’s primary perimeter defenders and ball-hawking wings or guards who play significant minutes; monitor the announced starting lineup and any late rotation changes to see who will be on the floor.
In-game injuries, sudden foul trouble for key defenders or ball-handlers, unexpected substitutions, and a clear shift in tempo (for example, a team pushing in transition) are the fastest ways to change expectations and market prices.
Head-to-head history can reveal matchup tendencies (e.g., one team forcing more turnovers), but its predictive value is limited by roster turnover and small sample size—give greater weight to recent defensive metrics, current rosters, and injury news for this specific game.