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Sports OPEN

San Antonio at Philadelphia: Points

📊 $12K traded 🏦 Source: Kalshi
Total Volume
$12K
Open Interest
11,918
Active Markets
32
Markets
32

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 (32)
Outcome Probability Yes Bid Yes Ask 24h Change Volume
VJ Edgecombe: 20+ 41%
40¢ 41¢ $2K Trade →
Victor Wembanyama: 25+ 54%
51¢ 54¢ $1K Trade →
Tyrese Maxey: 30+ 55%
56¢ 58¢ $1K Trade →
VJ Edgecombe: 25+ 19%
16¢ 19¢ $1K Trade →
VJ Edgecombe: 15+ 68%
64¢ 68¢ $937 Trade →
De'Aaron Fox: 15+ 56%
53¢ 56¢ $654 Trade →
Stephon Castle: 15+ 61%
58¢ 61¢ $572 Trade →
Devin Vassell: 15+ 43%
39¢ 43¢ $483 Trade →
Tyrese Maxey: 25+ 74%
73¢ 78¢ $460 Trade →
Victor Wembanyama: 30+ 28%
26¢ 30¢ $416 Trade →
Devin Vassell: 20+ 19%
19¢ $389 Trade →
Tyrese Maxey: 40+ 16%
15¢ 19¢ $283 Trade →
De'Aaron Fox: 20+ 21%
26¢ $241 Trade →
Stephon Castle: 20+ 31%
29¢ 32¢ $183 Trade →
Tyrese Maxey: 20+ 88%
87¢ 88¢ $166 Trade →
Victor Wembanyama: 20+ 79%
72¢ 75¢ $152 Trade →
Tyrese Maxey: 35+ 32%
33¢ 36¢ $106 Trade →
VJ Edgecombe: 10+ 87%
85¢ 89¢ $104 Trade →
Devin Vassell: 10+ 75%
74¢ $101 Trade →
De'Aaron Fox: 25+ 12%
12¢ $96 Trade →
Victor Wembanyama: 35+ 12%
12¢ $78 Trade →
Stephon Castle: 10+ 87%
81¢ 87¢ $69 Trade →
Kelly Oubre Jr.: 15+ 58%
57¢ $31 Trade →
De'Aaron Fox: 10+ 83%
59¢ 83¢ $22 Trade →
Stephon Castle: 25+ 12%
12¢ 13¢ $12 Trade →
Kelly Oubre Jr.: 25+ 0%
12¢ $0 Trade →
Devin Vassell: 25+ 0%
$0 Trade →
Kelly Oubre Jr.: 10+ 0%
79¢ 84¢ $0 Trade →
Dylan Harper: 10+ 0%
55¢ 62¢ $0 Trade →
Dylan Harper: 15+ 0%
32¢ $0 Trade →
Kelly Oubre Jr.: 20+ 0%
30¢ $0 Trade →
Dylan Harper: 20+ 0%
11¢ $0 Trade →

About This Market

This market asks traders to predict the points outcome for the San Antonio at Philadelphia game and aggregates expectations about how many points will be scored. It matters because prices update as new information (injuries, rotations, rest) arrives, offering a real‑time measure of consensus on scoring.

San Antonio and Philadelphia bring different offensive and defensive profiles, home‑court effects, and rotation depths that shape scoring expectations. Recent schedule, travel and rest for both teams, plus any roster changes late in the day, can materially change likely point outcomes. The market has 32 discrete outcomes, so traders are choosing among many point ranges or thresholds rather than a single binary result.

Market prices represent the aggregate beliefs of traders about which point outcome will occur and can move quickly as lineup, injury, or game‑tempo news arrives. Treat prices as continuously updating signals, not guarantees, and confirm specific outcome definitions on the KALSHI event page before trading.

Key Factors

Frequently Asked Questions

What exactly do the 32 outcomes represent for 'San Antonio at Philadelphia: Points'?

The 32 outcomes correspond to the discrete point ranges or thresholds defined by the event on KALSHI; each outcome is mutually exclusive and maps to a specific scoring interval or exact total as listed on the market page.

When will this market close relative to the game start?

Close timing is listed on the KALSHI event page and is typically set to occur before official game start according to the platform’s rules; because this event shows 'Closes: TBD', check the market page for the final close time.

If a player is ruled out during warmups, will that affect this market?

Yes — if the market is still open, traders can react to warmup‑room news and prices will adjust; if the market has already closed, outcome resolution will use the official game statistics and the market will not change post‑close.

Does overtime count toward the points outcome for this market?

Resolution conventions vary by market, but most game‑points markets on exchanges use the official final score including overtime unless the event description explicitly states otherwise; confirm the event rules on KALSHI.

How should I use prior head‑to‑head scoring between San Antonio and Philadelphia to inform trades on this market?

Use head‑to‑head results as one input, but adjust for current season roster changes, injuries, coaching, venue, and recent pace trends — historical matchups can be informative but may be a small sample and less relevant if personnel or style has changed.

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