SimpleFunctions

Ralph Norman in the 2026 South Carolina Republican Senate special primary

Ralph Norman is priced at 32¢ on Kalshi. Current book: 32¢ bid, 79¢ ask, 47¢ spread. This outcome ranks #2 of 6 inside Who will win the 2026 South Carolina Republican Senate special primary.

Price history

32¢ current

+30¢
0¢25¢
Jul 13, 2026Jul 13, 2026

Contract brief

If Ralph Norman wins the 2026 South Carolina Republican Senate special primary, then the market resolves to Yes.

Outcome

Ralph Norman

Rank

#2 of 6

Leader

Pamela Evette 43¢

Range

1¢-43¢

Family volume

$34K

Identifier

KXSCRSENS-26-RNOR

Jul 13, 2026, 1:38 AM UTC · 0m ago

Implied probability

32¢
Latest venue quote
Jul 13, 2026, 1:38 AM UTC · 0m ago

Bid

32¢

Ask

79¢

Spread

47¢

24h volume

$30

Family rank

#2 of 6

6 outcomes · Who will win the 2026 South Carolina Republican Senate special primary

Closes

Aug 11, 2027

Family volume

$34K

Orderbook snapshot

32 / 79¢

Kalshi
47¢ spread
BidSize
100¢2.0K
32¢29
2¢100
AskSize
79¢590
84¢12
96¢150
97¢202
98¢1.0K

Contract terms

What resolves this market.

YES condition

If Ralph Norman wins the 2026 South Carolina Republican Senate special primary, then the market resolves to Yes.

Venue

Kalshi

Closes

Aug 11, 2027

Identifier

KXSCRSENS-26-RNOR

SF Signal
Regime
neutral

Event family

Who will win the 2026 South Carolina Republican Senate special primary.

The same race as a probability stack: rank, volume, and where this contract sits against the other outcomes.

Total volume

$34K

Outcomes

6

Highest price

Pamela Evette 43¢

Current share

0%

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
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

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.

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.

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.

Blogpolitics

US Midterm Elections 2026 Prediction Markets: Trading the Battle for Congress

A deep‑dive guide for prediction market traders on the 2026 US midterm elections: House and Senate control odds, key races, Trump’s impact, economic and approval scenarios, polling accuracy, and data‑driven trading strategies.

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.