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Sports OPEN

Towson at Charleston: Spread

📊 $156 traded 🏦 Source: Kalshi
Total Volume
$156
Open Interest
156
Active Markets
22
Markets
22

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

All Outcomes (22)
Outcome Probability Yes Bid Yes Ask 24h Change Volume
Charleston wins by over 1.5 Points 56%
52¢ 56¢ $156 Trade →
Charleston wins by over 8.5 Points 0%
97¢ $0 Trade →
Charleston wins by over 7.5 Points 0%
97¢ $0 Trade →
Charleston wins by over 16.5 Points 0%
97¢ $0 Trade →
Charleston wins by over 10.5 Points 0%
97¢ $0 Trade →
Towson wins by over 14.5 Points 0%
97¢ $0 Trade →
Towson wins by over 1.5 Points 0%
95¢ $0 Trade →
Charleston wins by over 4.5 Points 0%
36¢ 46¢ $0 Trade →
Charleston wins by over 2.5 Points 0%
43¢ 53¢ $0 Trade →
Towson wins by over 7.5 Points 0%
97¢ $0 Trade →
Towson wins by over 4.5 Points 0%
97¢ $0 Trade →
Towson wins by over 8.5 Points 0%
97¢ $0 Trade →
Charleston wins by over 14.5 Points 0%
97¢ $0 Trade →
Charleston wins by over 17.5 Points 0%
96¢ $0 Trade →
Charleston wins by over 11.5 Points 0%
97¢ $0 Trade →
Charleston wins by over 5.5 Points 0%
32¢ 43¢ $0 Trade →
Towson wins by over 10.5 Points 0%
97¢ $0 Trade →
Towson wins by over 13.5 Points 0%
97¢ $0 Trade →
Charleston wins by over 13.5 Points 0%
97¢ $0 Trade →
Towson wins by over 11.5 Points 0%
97¢ $0 Trade →
Towson wins by over 2.5 Points 0%
97¢ $0 Trade →
Towson wins by over 5.5 Points 0%
97¢ $0 Trade →

About This Market

This market asks which point-spread outcome will occur in the Towson at Charleston game; it matters because spread markets summarize how traders weigh team strength, injuries, and situational factors and can be used to gauge market expectations for the final margin.

Towson and Charleston are NCAA Division I programs whose matchups influence conference standings and postseason seeding; market prices incorporate team form, roster availability, and situational context such as travel and scheduling. The market lists 22 discrete spread outcomes, so traders are effectively choosing among a range of possible final-margin bands rather than a single binary result.

Interpret market prices here as the collective assessment of which margin bands are most likely given current information; prices shift as new information arrives (injuries, lineups, weather, etc.), so look for movement around key news events rather than treating a single price as fixed.

Key Factors

Frequently Asked Questions

What do the 22 outcomes represent in the Towson at Charleston: Spread market?

The 22 outcomes correspond to distinct point-margin bands for the final score (for example, different ranges for Charleston winning by X points or Towson covering by Y points). Each outcome resolves true if the final official margin falls inside that outcome’s defined range.

When will the Towson at Charleston: Spread market resolve if the game goes to overtime or is postponed?

Most spread markets resolve using the official final score after any regulation plus overtime play; if the game is postponed or canceled, resolution depends on the platform’s rules (often requiring an official completed contest or a specific reschedule window), so check the market’s rulebook or announcements for this event.

How should I treat last-minute lineup or injury reports for Towson or Charleston when evaluating this market?

Late injury or lineup news can substantially shift expected margins; assess the on-court impact by position (e.g., loss of a primary scorer or rebounder), compare depth at that position, and monitor market price movement immediately after verified reports to see how traders are updating expectations.

Does this market already account for Charleston’s home-court advantage and, if so, how much should I weigh it?

Market prices typically incorporate home-court and rest advantages as information arrives; you should weigh home-court alongside other factors like travel schedule, recent home/away splits, and matchup-specific vulnerabilities rather than treating it in isolation.

How relevant are historical head-to-head results between Towson and Charleston for this specific spread market?

Head-to-head history can reveal matchup patterns (e.g., one team consistently exploiting a stylistic weakness), but prioritize recent meetings, roster continuity, and current-season metrics because personnel and coaching changes make older results less predictive for a single-game spread.

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