| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Adam Fantilli: 3+ | 8% | 0¢ | 9¢ | — | $100 | Trade → |
| Artemi Panarin: 1+ | 64% | 64¢ | 70¢ | — | $73 | Trade → |
| Adrian Kempe: 2+ | 26% | 0¢ | 27¢ | — | $71 | Trade → |
| Alex Laferriere: 2+ | 14% | 0¢ | 14¢ | — | $62 | Trade → |
| Mason Marchment: 2+ | 19% | 0¢ | 19¢ | — | $61 | Trade → |
| Adam Fantilli: 1+ | 53% | 53¢ | 61¢ | — | $56 | Trade → |
| Charlie Coyle: 1+ | 55% | 0¢ | 55¢ | — | $53 | Trade → |
| Charlie Coyle: 2+ | 18% | 0¢ | 20¢ | — | $50 | Trade → |
| Anze Kopitar: 2+ | 20% | 0¢ | 22¢ | — | $45 | Trade → |
| Sean Monahan: 3+ | 3% | 0¢ | 4¢ | — | $31 | Trade → |
| Zach Werenski: 2+ | 33% | 0¢ | 33¢ | — | $28 | Trade → |
| Brandt Clarke: 1+ | 45% | 44¢ | 45¢ | — | $18 | Trade → |
| Anze Kopitar: 1+ | 56% | 0¢ | 58¢ | — | $17 | Trade → |
| Kirill Marchenko: 1+ | 69% | 0¢ | 69¢ | — | $12 | Trade → |
| Quinton Byfield: 1+ | 48% | 0¢ | 48¢ | — | $10 | Trade → |
| Charlie Coyle: 3+ | 5% | 0¢ | 7¢ | — | $9 | Trade → |
| Mason Marchment: 1+ | 56% | 0¢ | 56¢ | — | $8 | Trade → |
| Adrian Kempe: 1+ | 65% | 0¢ | 65¢ | — | $3 | Trade → |
| Alex Laferriere: 1+ | 0% | 0¢ | 46¢ | — | $0 | Trade → |
| Drew Doughty: 2+ | 0% | 0¢ | 8¢ | — | $0 | Trade → |
| Adam Fantilli: 2+ | 0% | 0¢ | 25¢ | — | $0 | Trade → |
| Brandt Clarke: 2+ | 0% | 0¢ | 14¢ | — | $0 | Trade → |
| Anze Kopitar: 3+ | 0% | 0¢ | 6¢ | — | $0 | Trade → |
| Ivan Provorov: 2+ | 0% | 0¢ | 10¢ | — | $0 | Trade → |
| Sean Monahan: 2+ | 0% | 0¢ | 14¢ | — | $0 | Trade → |
| Ivan Provorov: 1+ | 0% | 0¢ | 38¢ | — | $0 | Trade → |
| Adrian Kempe: 3+ | 0% | 0¢ | 10¢ | — | $0 | Trade → |
| Kirill Marchenko: 3+ | 0% | 0¢ | 11¢ | — | $0 | Trade → |
| Mason Marchment: 3+ | 0% | 0¢ | 6¢ | — | $0 | Trade → |
| Alex Laferriere: 3+ | 0% | 0¢ | 5¢ | — | $0 | Trade → |
| Artemi Panarin: 2+ | 0% | 0¢ | 34¢ | — | $0 | Trade → |
| Artemi Panarin: 3+ | 0% | 0¢ | 14¢ | — | $0 | Trade → |
| Drew Doughty: 1+ | 0% | 0¢ | 33¢ | — | $0 | Trade → |
| Quinton Byfield: 2+ | 0% | 0¢ | 15¢ | — | $0 | Trade → |
| Trevor Moore: 2+ | 0% | 0¢ | 10¢ | — | $0 | Trade → |
| Quinton Byfield: 3+ | 0% | 0¢ | 5¢ | — | $0 | Trade → |
| Sean Monahan: 1+ | 0% | 0¢ | 46¢ | — | $0 | Trade → |
| Kirill Marchenko: 2+ | 0% | 0¢ | 30¢ | — | $0 | Trade → |
| Zach Werenski: 3+ | 0% | 0¢ | 14¢ | — | $0 | Trade → |
| Brandt Clarke: 3+ | 0% | 0¢ | 5¢ | — | $0 | Trade → |
| Zach Werenski: 1+ | 0% | 0¢ | 72¢ | — | $0 | Trade → |
| Trevor Moore: 1+ | 0% | 0¢ | 37¢ | — | $0 | Trade → |
This prediction market offers contracts tied to the total points scored in the LA Kings at CBJ Blue Jackets game; it matters because it aggregates public expectations about how high- or low-scoring the game will be.
The market sits within an NHL game context where team styles, goaltending, and special-teams play strongly shape scoring outcomes. It lists 42 possible outcomes and has seen $707 in total volume traded, reflecting how traders are expressing granular expectations about the final combined point total.
Market prices reflect the collective, real-time expectation for the game’s point total and update as new information (lineups, injuries, goalie starts) becomes available; treat prices as a consensus signal, not a guarantee.
Close time is set by the platform (listed as TBD for this event); typically markets like this close at or shortly before puck drop, so check the KALSHI event page for updates.
Each outcome corresponds to a specific total points level or discrete point-range contract offered for the game; view the contract list on the event page to see the exact mapping of outcomes to point totals.
Those announcements often move the market quickly because they materially change expected scoring; traders typically react as soon as official lineup and goalie news is posted.
Home ice can influence factors such as line matchups, last-change advantages, and travel fatigue for the visitor, which together can alter scoring dynamics and thus the market’s expectations.
Head‑to‑head history provides context but should be weighed alongside current-season form, roster changes, and goaltender matchups; short sample sizes and changing rosters limit how predictive past games are on their own.