SimpleFunctions

How much will new Steam Machine cost

How much will new Steam Machine cost is priced at 99¢ on Kalshi. Current book: 0¢ bid, 100¢ ask, 100¢ spread. This page tracks a standalone prediction-market contract.

Price history

99¢ current

+18¢
75¢100¢
May 28, 2026Jun 22, 2026

Contract brief

If the first price announced for new Steam Machine by Valve Corporation is at least $700, then the market resolves to Yes.

Outcome

How much will new Steam Machine cost

Rank

Standalone

Leader

Range

Family volume

$27K

Identifier

KXSTEAMPRICE-27-700

Jun 27, 2026, 9:33 PM UTC · 0m ago

Implied probability

99¢
Latest venue quote
Jun 27, 2026, 9:33 PM UTC · 0m ago

Bid

Ask

100¢

Spread

100¢

Reported volume

$27K

Family rank

Standalone

Standalone contract

Closes

Jun 23, 2026

Family volume

$27K

Orderbook snapshot

0 / 100¢

Kalshi
100¢ spread
No public depth snapshot is cached for this contract yet.

Contract terms

What resolves this market.

YES condition

If the first price announced for new Steam Machine by Valve Corporation is at least $700, then the market resolves to Yes.

Venue

Kalshi

Closes

Jun 23, 2026

Identifier

KXSTEAMPRICE-27-700

SF Signal
Regime
neutral

Event family

This market.

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

Total volume

$27K

Outcomes

1

Highest price

How much will new Steam Machine cost 99¢

Current share

100%

Indicators

Yield, cliff risk, volatility, and regime.

Regime

neutral

Score

0.409

Observability

medium

Event type

cultural

Related readings

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

Browse library
Technicalrisk

Reading Prediction Market Orderbooks: Liquidity, Spread, and When to Enter

How to read prediction market orderbooks on Kalshi. Covers bid-ask spread analysis, liquidity scoring, executable edge calculation, and when thin markets are opportunities vs traps.

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

How to Scan Prediction Market Orderbooks: Spread, Depth, and Liquidity Analysis

Practical guide to analyzing orderbook data from Kalshi and Polymarket. Learn spread, depth, liquidity scoring, and executable edge calculation.

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.

Blogmacro

US Recession 2025? What 1% Prediction Market Odds Get Right—and Wrong—About the Cycle

Prediction markets put 2025 US recession odds near 1%, while yield curves, economic indicators, and institutional forecasts point to much higher risk. This deep dive compares market pricing to historical base rates, Federal Reserve policy, and forecasting models to see if investors are underpricing recession risk.

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.

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.