🏆
Sports OPEN

New York at Charlotte: Points

📊 $0 traded 🏦 Source: Kalshi
Total Volume
$0
Open Interest
0
Active Markets
37
Markets
49

Trade This Market

Yes Bid
Yes Ask
Last Price
Prev Close
Buy YES → Buy NO

Prices in cents (1¢ = 1%). Trade on Kalshi.

All Outcomes (49)
Outcome Probability Yes Bid Yes Ask 24h Change Volume
Kon Knueppel: 15+ 0%
$0 Resolved
Kon Knueppel: 20+ 0%
$0 Resolved
Kon Knueppel: 25+ 0%
$0 Trade →
Kon Knueppel: 30+ 0%
$0 Trade →
Brandon Miller: 10+ 0%
$0 Resolved
Brandon Miller: 15+ 0%
$0 Resolved
Brandon Miller: 20+ 0%
$0 Trade →
Brandon Miller: 25+ 0%
$0 Trade →
Brandon Miller: 30+ 0%
$0 Trade →
Moussa Diabaté: 10+ 0%
$0 Trade →
Moussa Diabaté: 15+ 0%
$0 Trade →
Moussa Diabaté: 20+ 0%
$0 Trade →
Coby White: 10+ 0%
$0 Resolved
Coby White: 15+ 0%
$0 Trade →
Coby White: 20+ 0%
$0 Trade →
Coby White: 25+ 0%
$0 Trade →
Miles Bridges: 10+ 0%
$0 Resolved
Miles Bridges: 15+ 0%
$0 Trade →
Miles Bridges: 20+ 0%
$0 Trade →
Miles Bridges: 25+ 0%
$0 Trade →
LaMelo Ball: 10+ 0%
$0 Resolved
LaMelo Ball: 15+ 0%
$0 Resolved
LaMelo Ball: 20+ 0%
$0 Trade →
LaMelo Ball: 25+ 0%
$0 Trade →
LaMelo Ball: 30+ 0%
$0 Trade →
Jalen Brunson: 15+ 0%
$0 Resolved
Jalen Brunson: 20+ 0%
$0 Resolved
Jalen Brunson: 25+ 0%
$0 Trade →
Jalen Brunson: 30+ 0%
$0 Trade →
Jalen Brunson: 35+ 0%
$0 Trade →
OG Anunoby: 10+ 0%
$0 Resolved
OG Anunoby: 15+ 0%
$0 Trade →
OG Anunoby: 20+ 0%
$0 Trade →
OG Anunoby: 25+ 0%
$0 Trade →
Mitchell Robinson: 10+ 0%
$0 Trade →
Mitchell Robinson: 15+ 0%
$0 Trade →
Mitchell Robinson: 20+ 0%
$0 Trade →
Karl-Anthony Towns: 15+ 0%
$0 Trade →
Karl-Anthony Towns: 20+ 0%
$0 Trade →
Karl-Anthony Towns: 25+ 0%
$0 Trade →
Karl-Anthony Towns: 30+ 0%
$0 Trade →
Josh Hart: 10+ 0%
$0 Trade →
Josh Hart: 15+ 0%
$0 Trade →
Josh Hart: 20+ 0%
$0 Trade →
Josh Hart: 25+ 0%
$0 Trade →
Mikal Bridges: 10+ 0%
$0 Resolved
Mikal Bridges: 15+ 0%
$0 Trade →
Mikal Bridges: 20+ 0%
$0 Trade →
Mikal Bridges: 25+ 0%
$0 Trade →

About This Market

This market asks which points-related outcome will occur in the New York at Charlotte game, aggregating trader expectations about scoring outcomes for that specific matchup. It matters because it summarizes collective views on game tempo, offense, and player availability that drive scoring.

New York and Charlotte meet in an NBA regular-season matchup where scoring depends on each team’s roster, style, and matchup on the night. Historical encounters, venue (home-court), and season context (rest, schedule density, injuries) shape expected scoring patterns even as individual-game variance is high. Markets like this capture how new information—lineup news, scratches, or in-game developments—shifts collective expectations about total or player points.

Market prices reflect the crowd’s consensus expectation for the labeled points outcomes and will move as new information arrives; treat prices as real-time signals rather than fixed forecasts. Compare prices across outcomes and monitor news (injuries, rotations, coach comments) to understand why the market moves.

Key Factors

Frequently Asked Questions

What exactly do the 25 outcomes in 'New York at Charlotte: Points' represent?

Each listed outcome corresponds to a specific points-based result as defined on the market page—commonly ranges or exact totals for the game or for individual players; consult the outcome labels on the market to see the exact scoring intervals or totals covered.

When will trading close relative to the New York at Charlotte tip-off?

This market’s close time is listed as TBD; typically markets for a specific game close at or just before tip-off, but you should monitor the market page for the official close time and any platform announcements.

Which player-level developments should I watch before trading this points market?

Watch pregame injury reports, official starting lineups, minutes guidance from coaches, and any late scratches for primary scorers or ball-handlers—those items are the most likely to alter expected points outcomes.

How do coaching strategies and matchups between New York and Charlotte affect points outcomes?

Coaches’ tendencies (pace-up vs slow-down, defensive matchups, playing small/large lineups) and how each team defends key scorers influence scoring rates; adjustments during the game can also change projected totals as the market reacts to on-court matchups.

How should I treat historical head-to-head scoring between New York and Charlotte when evaluating this market?

Head-to-head history can inform tendencies—such as whether past matchups tended toward high- or low-scoring games—but use it alongside current-season form, roster changes, and situational factors (rest, injuries) because team composition and style can change season to season.

Related Markets