New York City vs DC United Winner?
This contract is priced at 21¢ on Kalshi. Current book: 19¢ bid, 21¢ ask, 2¢ spread.
Implied probability
Event outcomes
1
Family volume
$3K
Best sibling
—
Ticker
KXMLSGAME-26MAY03NYCDCU-DCU
Price history
21¢ current
+11¢Orderbook snapshot
19 / 21¢
Contract terms
Resolution, venue, and identifiers.
Resolution rules
If DC United wins the New York City vs DC United professional MLS soccer game originally scheduled for May 3, 2026 after 90 minutes plus stoppage time (does not include extra time or penalties), then the market resolves to Yes.
Venue
Kalshi
Closes
May 17, 2026
Identifier
KXMLSGAME-26MAY03NYCDCU-DCU
Event family
This market.
This view keeps the individual contract next to its sibling outcomes. For long-tail search traffic, this is the useful context: where the current price sits inside the event, how much volume exists around the family, and which outcomes have actual depth.
Total volume
$3K
Outcomes
1
Highest price
New York City vs DC United Winner 21¢
Current share
100%
New York City vs DC United Winner
kalshi · KXMLSGAME-26MAY03NYCDCU-DCU
Indicators
Yield, cliff risk, volatility, and regime.
Regime
neutral
Score
0.5
Full indicator table
Odds pages
Related prediction questions
Related readings
Matched from SimpleFunctions blog, opinions, technical guides, concepts, and learn pages.
Kalshi vs Polymarket: Which Prediction Market Should You Trade?
In-depth comparison of Kalshi and Polymarket for prediction market traders. Regulatory structure, liquidity, fees, API tooling, and cross-venue trading with SimpleFunctions.
Kalshi vs Polymarket: A Developer's Comparison of APIs, Orderbooks, and Liquidity
Data-driven comparison of Kalshi and Polymarket APIs, orderbooks, rate limits, and liquidity. Code examples for building on both prediction markets.
Maker / Taker Regime in Prediction Markets: How to Read the Orderbook State
Three regime states (maker-dominated, taker-dominated, neutral) and how to read which one a Kalshi or Polymarket contract is in. Strategy follows regime, not thesis.
Why Soccer Is the Best Sport for Live Market Making (And Basketball Is the Worst)
Soccer has 86 safe minutes per game and 4 dangerous minutes. Basketball has 200 scoring events. The numbers explain which sports work for live market making.
Prediction Market Orderbook Analysis: Reading Depth, Spread, and Liquidity
How to read prediction market orderbooks. Binary settlement, spread-as-percentage, depth asymmetry, executable edge calculation, and cross-venue arbitrage analysis.
MCP Servers for Prediction Markets: Connect Claude Code to Kalshi and Polymarket
Connect Claude Code, Cursor, or Cline to Kalshi and Polymarket prediction markets via MCP. One-line setup, 18 tools, real-time market data for AI agents.
SimpleFunctions context
Index, screen, query, and monitor.
Prediction Market Index
Market-wide volatility, geo risk, breadth, and activity around this contract.
Market Screener
Filter adjacent contracts by volume, expiry, IY, CRI, venue, and theme.
Event Probability API
Read 21% as a structured event probability object for agents and apps.
Realtime Data API
Prices, orderbooks, movement, heat, and liquidity indicators across venues.
World State API
Compact market-aware context packets for agent sessions and scheduled refresh.
Hedging Workflows
Map a thesis or exposure to candidate event markets and monitoring paths.