| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Zach Werenski: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Bo Horvat: 3+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Matthew Schaefer: 3+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Kirill Marchenko: 3+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Kirill Marchenko: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Tony DeAngelo: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Charlie Coyle: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Mason Marchment: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Matthew Schaefer: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Tony DeAngelo: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Sean Monahan: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Bo Horvat: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Kirill Marchenko: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Mathew Barzal: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Anders Lee: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Anders Lee: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Mathew Barzal: 3+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Charlie Coyle: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Matthew Schaefer: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Zach Werenski: 3+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Adam Fantilli: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Mason Marchment: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Bo Horvat: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Sean Monahan: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Mathew Barzal: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Zach Werenski: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Adam Fantilli: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks how assists will be distributed in the Columbus Blue Jackets at New York Islanders game and is useful for bettors and analysts tracking playmaking, power-play performance, and team offensive tempo.
Columbus and New York have contrasting styles that shape assist opportunities: Columbus often emphasizes transition and quick passing, while the Islanders typically rely on structured defenses and set offensive zones. Special teams, line matchups, and roster availability have historically had large effects on how many and which players generate assists in head-to-head matchups.
Market odds aggregate participant expectations about assist outcomes and update as new information arrives (lineups, injuries, in-game events). Treat odds as a real-time signal of market consensus rather than a guarantee of what will happen.
The platform sets the market close time; many game markets close shortly before puck drop or when rosters lock. For this event the close is listed as TBD, so monitor the Kalshi market page for the final close time.
Power plays concentrate possession and passing opportunities, so more power plays or a dominant power-play unit from either team typically increases assist counts—especially primary assists by unit quarterbacks and setup men.
Counting rules vary by platform. Common practice is that assists in regulation and overtime count, while shootout statistics are excluded; always confirm the Kalshi market rules for this specific event.
Official NHL scorers determine assists (up to two per goal) based on the last players who touched the puck prior to the goal, including plays that involve deflections; this market follows the official scoring decisions recorded in the game log.
Monitor each team’s top-line centers, their designated power-play quarterbacks, and forwards with high average ice time and strong playmaking reputations; check the official lines and power-play units announced before the game for the best indicators.