SimpleFunctions

Karen Bass receive between 35% and 40% of the popular vote in the first round of the Los Angeles mayoral election

35% - 40% is priced at 23¢ on Kalshi. Current book: 22¢ bid, 24¢ ask, 2¢ spread. This outcome ranks #2 of 9 inside Will Karen Bass receive.

Price history

23¢ current

+1¢
10¢20¢
May 21, 2026May 26, 2026

Contract brief

If the certified percentage of the popular vote received by Karen Bass in the first round of the Los Angeles mayoral election is 35% to 39.99%, inclusive of both endpoints, then the market resolves to Yes.

Outcome

35% - 40%

Rank

#2 of 9

Leader

30% - 35% 29¢

Range

1¢-29¢

Family volume

$553

Identifier

KXVOTEPRIMARY-LAMAYOR1R26KBASKBAS-37

May 27, 2026, 10:08 PM UTC · 26m ago

Implied probability

23¢
Latest venue quote
May 27, 2026, 10:08 PM UTC · 26m ago

Bid

22¢

Ask

24¢

Spread

Reported volume

$731

Family rank

#2 of 9

9 outcomes · Will Karen Bass receive

Closes

Jun 2, 2027

Family volume

$553

Orderbook snapshot

22 / 24¢

Kalshi
2¢ spread
BidSize
22¢5
21¢100
17¢100
15¢281
11¢45
AskSize
24¢55
25¢100
26¢200
31¢71
82¢1.1K

Contract terms

What resolves this market.

YES condition

If the certified percentage of the popular vote received by Karen Bass in the first round of the Los Angeles mayoral election is 35% to 39.99%, inclusive of both endpoints, then the market resolves to Yes.

Venue

Kalshi

Closes

Jun 2, 2027

Identifier

KXVOTEPRIMARY-LAMAYOR1R26KBASKBAS-37

SF Signal
SF Index
174.57
Regime
neutral

Indicators

Yield, cliff risk, volatility, and regime.

IY (Yes)

349.1%

IY (No)

27.8%

Adj IY

175%

CRI

4

Overround

-0.0%

Regime

neutral

Score

0.5

Full indicator table

349.1%
27.8%
Adj IY
175%
4
Overround
-0.0%

Related readings

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

Browse library
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.

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.

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.

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.

Conceptmethodology

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.

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.