🏆
Sports OPEN

New York at Oklahoma City: Points

📊 $0 traded 🏦 Source: Kalshi
Total Volume
$0
Open Interest
0
Active Markets
42
Markets
42

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 (42)
Outcome Probability Yes Bid Yes Ask 24h Change Volume
Isaiah Hartenstein: 10+ 0%
$0 Trade →
Isaiah Hartenstein: 15+ 0%
$0 Trade →
Isaiah Hartenstein: 20+ 0%
$0 Trade →
Luguentz Dort: 10+ 0%
$0 Trade →
Luguentz Dort: 15+ 0%
$0 Trade →
Luguentz Dort: 20+ 0%
$0 Trade →
Shai Gilgeous-Alexander: 25+ 0%
$0 Trade →
Shai Gilgeous-Alexander: 30+ 0%
$0 Trade →
Shai Gilgeous-Alexander: 35+ 0%
$0 Trade →
Shai Gilgeous-Alexander: 40+ 0%
$0 Trade →
Mikal Bridges: 10+ 0%
$0 Trade →
Mikal Bridges: 15+ 0%
$0 Trade →
Mikal Bridges: 20+ 0%
$0 Trade →
Mikal Bridges: 25+ 0%
$0 Trade →
Jalen Brunson: 15+ 0%
$0 Trade →
Jalen Brunson: 20+ 0%
$0 Trade →
Jalen Brunson: 25+ 0%
$0 Trade →
Jalen Brunson: 30+ 0%
$0 Trade →
Jalen Brunson: 35+ 0%
$0 Trade →
OG Anunoby: 10+ 0%
$0 Trade →
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 →
Mitchell Robinson: 25+ 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 →
Jalen Williams: 10+ 0%
$0 Trade →
Jalen Williams: 15+ 0%
$0 Trade →
Jalen Williams: 20+ 0%
$0 Trade →
Jalen Williams: 25+ 0%
$0 Trade →
Chet Holmgren: 10+ 0%
$0 Trade →
Chet Holmgren: 15+ 0%
$0 Trade →
Chet Holmgren: 20+ 0%
$0 Trade →
Chet Holmgren: 25+ 0%
$0 Trade →

About This Market

This market centers on the points outcome for the New York at Oklahoma City game and is used to trade expectations about scoring in that specific matchup. It matters because scoring outcomes drive many short-term market moves and reflect how news and lineups shift in real time.

New York and Oklahoma City bring different offensive and defensive tendencies that shape scoring expectations: coaching style, roster construction, and recent form all influence how many points either team or the game as a whole produces. Historical head-to-head results can provide context, but season-to-season roster changes and in-season trends often have bigger effects on an individual game's scoring profile. The specific market rules on this platform (e.g., whether overtime counts or which team’s points are tracked) determine the exact payoff conditions.

Market prices reflect collective market views about plausible scoring ranges and update as new information arrives (injuries, rest, lineup changes, weather for travel, etc.). Treat prices as a real-time synthesis of available information and check liquidity and trade volume before acting.

Key Factors

Frequently Asked Questions

For the New York at Oklahoma City: Points market, when does trading typically close relative to tip-off?

This event lists a closing time of TBD; on many platforms markets close shortly before tip-off but exact close time is shown on the event page—check the platform for the authoritative timeline.

For the New York at Oklahoma City: Points market, does the event track a single team’s points or the combined game total?

The label 'Points' can refer to a team total or a combined total depending on the contract specification; consult the event description on Kalshi to confirm whether it is tracking New York’s points, Oklahoma City’s points, or the game total.

For the New York at Oklahoma City: Points market, will points scored in overtime count toward the outcome?

Whether overtime counts depends on the event’s stated rules; many markets explicitly note 'regulation only' or 'including overtime'—refer to the event terms to determine counting rules.

For the New York at Oklahoma City: Points market, how do late injuries or lineup changes affect the market?

Late injuries and lineup news typically move prices quickly as traders rebalance expectations; markets can become more volatile and liquidity may change as bettors react to last-minute information.

For the New York at Oklahoma City: Points market, how should I use historical matchup and pace stats when evaluating this event?

Use head-to-head and pace metrics to set a baseline for expected scoring, but adjust for current-season roster changes, recent form, projected starters, and any game-specific factors (rest, travel, injuries) that materially alter expected possessions or efficiency.

Related Markets