Will Andy Beshear be the Democratic Presidential nominee in 2028
event base · KXPRESNOMD
Outcome probabilities
24 contracts at one resolution date
Analysis
The Will Andy Beshear be the Democratic Presidential nominee in 2028 slate has 24 mutually-exclusive contracts, all resolving on a single date. The current top-probability outcome is Gavin Newsom at 23.0%.
A bespoke narrative analysis is generated by an LLM on a 24h cron. If this paragraph is showing instead, the slate has either just appeared in the index or has not yet been queued.
Constituent markets
24 kalshi contracts
How to read this page
An outcome slate is a set of mutually-exclusive contracts that all settle on the same date. Their YES probabilities form a distribution over which outcome the market expects. Probabilities should roughly sum to 100% minus the venue’s overround.
Curve construction: each constituent contract is identified by its venue event_id (KXPRESNOMD on kalshi). Tenor is computed from the contract’s close_time minus snapshot time, rounded to days. We do not interpolate between tenors — every plotted point is a real, traded contract. Outcome-slate pages show price-as-probability for mutually-exclusive contracts; term-structure pages show price-as-probability vs days-to-resolution for the same underlying event.
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.