SimpleFunctions

Margin of victory for Sharif Street in the 2026 Pennsylvania 3rd Congressional District Democratic primary above 25%

Sharif Street, ≥25% is priced at 1¢ on Kalshi. Current book: 0¢ bid, 1¢ ask, 1¢ spread. This outcome ranks #3 of 13 inside Will the margin of victory.

Price history

1¢ current

0¢5¢
May 25, 2026May 25, 2026

Contract brief

If the margin of victory for Sharif Street in the 2026 Pennsylvania 3rd Congressional District Democratic primary falls within 25% to 100%, inclusive of its lower bound and exclusive of its upper bound, then the market resolves to Yes.

Outcome

Sharif Street, ≥25%

Rank

#3 of 13

Leader

Chris Rabb, 15-20% 96¢

Range

1¢-96¢

Family volume

$56

Identifier

KXPRIMARYMOV-PA3D26-SSTR-P62

May 25, 2026, 3:29 AM UTC · 0m ago

Implied probability

1¢
Latest venue quote
May 25, 2026, 3:29 AM UTC · 0m ago

Bid

Ask

Spread

Reported volume

$187

Family rank

#3 of 13

13 outcomes · Will the margin of victory

Closes

May 19, 2027

Family volume

$56

Orderbook snapshot

0 / 1¢

Kalshi
1¢ spread
BidSize
AskSize
45¢1.5K
99¢96
100¢28K

Contract terms

What resolves this market.

YES condition

If the margin of victory for Sharif Street in the 2026 Pennsylvania 3rd Congressional District Democratic primary falls within 25% to 100%, inclusive of its lower bound and exclusive of its upper bound, then the market resolves to Yes.

Venue

Kalshi

Closes

May 19, 2027

Identifier

KXPRIMARYMOV-PA3D26-SSTR-P62

SF Signal
Regime
neutral

Browse this series

2026 Primary Margin of Victory Markets
Per-series collection — every live contract in the KXPRIMARYMOV series on Kalshi, sorted by 24h volume.

Indicators

Yield, cliff risk, volatility, and regime.

Regime

neutral

Score

0.5

Related readings

Matched from SimpleFunctions blog, opinions, technical guides, concepts, and learn pages.

Browse library
Blogmarkets

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.

Opinioncomparison

Kalshi vs Polymarket: Mechanics, Fees, Regulation, Liquidity (2026)

Side-by-side comparison of Kalshi and Polymarket in 2026. Fee math, calibration data, withdrawal speed, and a decision tree for picking the right venue.

Blogmarkets

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.

Technicalguide

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.

Opinionanalysis

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.

Opinionanalysis

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.

SimpleFunctions context

Index, screen, query, and monitor.

Open index

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.