Democratic party · SENATEME-26
Democratic party is priced at 65¢ on Kalshi. Current book: 65¢ bid, 66¢ ask, 1¢ spread. This outcome ranks #1 of 2 inside SENATEME-26.
Price history
65¢ current
−5¢Contract brief
If a representative of the Democratic party is sworn in as a Senator of Maine for the term beginning in 2027, then the market resolves to Yes.
Outcome
Democratic party
Rank
#1 of 2
Leader
Democratic party 65¢
Range
33¢-65¢
Family volume
$33K
Identifier
SENATEME-26-D
May 28, 2026, 1:38 AM UTC · 16m ago
Implied probability
Bid
65¢
Ask
66¢
Spread
1¢
24h volume
$13K
Family rank
#1 of 2
2 outcomes · SENATEME-26
Closes
Nov 3, 2027
Family volume
$33K
Orderbook snapshot
65 / 66¢
Contract terms
What resolves this market.
YES condition
If a representative of the Democratic party is sworn in as a Senator of Maine for the term beginning in 2027, then the market resolves to Yes.
Venue
Kalshi
Closes
Nov 3, 2027
Identifier
SENATEME-26-D
Event family
SENATEME-26.
The same race as a probability stack: rank, volume, and where this contract sits against the other outcomes.
Total volume
$33K
Outcomes
2
Highest price
Democratic party 65¢
Current share
41%
Democratic party
kalshi · SENATEME-26-D
Republican party
kalshi · SENATEME-26-R
Indicators
Yield, cliff risk, volatility, and regime.
Regime
neutral
Score
0.341
Observability
low
Event type
political
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.
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.
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.
Liquidity Availability Is the Real Edge in Prediction Markets
Implied yield, cliff risk, and overround all describe what to trade. Liquidity Availability Score describes whether the orderbook can absorb the trade. Why LAS is the indicator that decides who actually books P&L.
Implied Yield vs Raw Probability: Why Bond-Adjacent Prediction Markets Need a Different Lens
Why fixed-income-adjacent prediction-market contracts need to be priced in implied yield, not raw probability, with two real Kalshi Fed-decision contracts as a case study.
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 65% 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.
How we compute these odds
SimpleFunctions aggregates live prediction-market contracts from Kalshi and Polymarket. Each slug groups contracts that resolve on the same underlying event, identified by venue event_id.
For binary slugs, the headline probability is the liquidity-weighted mid-price across all bound contracts. For multi-outcome slugs (e.g. elections with 3+ candidates), the headline is the leader’s price; we never arithmetically average disjoint outcomes — that would produce a number with no real-world meaning.
Snapshots refresh every 5 minutes during market hours; daily aggregates are computed at 04:00 UTC. The 30-day sparkline is drawn from per-ticker daily means stored in market_indicator_daily; 24h delta and movement events are derived from the same source.