Kalshi price data

Kalshi Price Data

Kalshi price data combines stored yes/no ladders, up to 100 levels per side, with a preceding Binance reference when a valid ASOF join exists. The archive contains more than 170 million observations and its earliest series reach January 2026.

Kalshi price data combines each stored yes/no ladder with a separately sourced reference series. Because a yes bid at p implies a yes offer at 1 minus the best no bid, both sides are required to derive the visible spread. The reference join is timestamp-based and nullable.

Kalshi price data, measured

Computed directly from our live capture — not brochure numbers.

170M
order-book snapshots

Kalshi yes/no archive, since January 2026

900,000+
markets captured

distinct Kalshi crypto markets

96 / 97
levels per side

median yes / no depth — up to the full 100

~156,000
contracts resting

median book depth on a BTC 15-min market

Measured directly from DepthFeed's live ClickHouse archive, June 21, 2026.

Anatomy of a real Kalshi snapshot

This is one real yes/no book from a BTC 15-minute market — every field below is what the API actually returns.

Yes bidsNo bids (a no bid at p = a yes offer at 1 − p)0.326,6450.311,1290.301,0250.291,5350.67635.10.661,3510.652,6450.642,310
Resting size at each price level — KXBTC15M-26JUN211530 (Kalshi). Bar length ∝ size.

A yes bid at price p is a no offer at 1 − p, so the implied yes ask is 1 − the best no bid.full-depth REST poll.

yes_prices / yes_sizes
The yes side of the book — every resting bid price with its size.
no_prices / no_sizes
The no side — a no bid at price p is an offer to sell yes at 1 − p.
ticker / series
KXBTC15M… — the series prefix gives the asset, market_type gives the window (15m / 1h / 24h / 1w).
recv_ts_ms
Epoch-millis capture time; joins to the underlying reference price.

Kalshi price data at a glance

Market price
Outcomes quoted 0–1 (implied probability)
Underlying
Binance spot/futures, joined per snapshot
Capture
Paced full-depth REST polling
Series
KX{ASSET}15M · KX{ASSET} · KX{ASSET}D
Assets
7 — BTC · ETH · SOL · XRP · DOGE · BNB · HYPE
Timestamps
Millisecond observation time; venue-specific source stamps
Underlying price
Nearest preceding Binance reference when available
History
7/30/90-day windows + full archive (Desk)
Delivery
REST history + normalized live WebSocket frames
Resolution
Raw stored observations or ?interval= 1s–1d

What Kalshi price data really is

Yes/no prices are implied probabilities

Every Kalshi crypto contract resolves yes or no, and each side trades between 0.01 and 0.99. The yes price is the market's implied probability that the condition resolves true. DepthFeed gives you the live best bid and ask on both sides — not a single last print — so the probability you read has a real spread and real size behind it.

The full yes/no ladder, both sides

Because a yes bid at price p is the same as offering no at 1 − p, the true market needs both ladders. DepthFeed captures the complete book — a median of 96 yes and 97 no levels, up to the full 100 per side — so you can reconstruct the exact mid, spread, and depth at any moment, not just the touch.

The underlying crypto price, joined

Historical queries ASOF-align the nearest preceding Binance reference for the asset (BTC, ETH, SOL, XRP, DOGE, BNB, and HYPE) when available. A missing match remains null instead of becoming a synthetic price.

Worked example: reading a Kalshi yes/no price

Kalshi prices are probabilities. Here is how to read one straight from a real captured book.

  1. 1Both sides quote the same market

    A real captured market, KXBTC15M-26JUN211530, had its best yes bid at 0.32 and its best no bid at 0.67. Because a no bid at 0.67 is the same as offering yes at 1 − 0.67 = 0.33, the yes contract was a one-cent market: 0.32 / 0.33.

  2. 2The price is the odds

    That 0.32–0.33 quote means the book was pricing roughly 32–33% odds that BTC finished up over those 15 minutes. Read the yes side for the probability, the no side for the other half, and the depth on each for how much conviction is actually resting there.

  3. 3Threshold markets work against a level

    Not every Kalshi market is up/down. A threshold market like KXHYPED-26JUN0717-T73.9999 asks whether HYPE settles above $73.9999 that day — a daily (24h) market in the KXHYPED series, still quoted yes/no from 0.01 to 0.99. Same price mechanic, different question.

  4. 4Depth you can trust

    DepthFeed captures both sides of that ladder — a median of 96 yes and 97 no levels, up to the full 100 — so every probability you read comes with the resting size behind it.

Precision notes — how the Kalshi book is captured

What each Kalshi price is, and how we record it.

The full 100-level book, both sides

We keep the complete yes and no ladder — a median of 96 and 97 levels, up to the full 100 per side — so every probability you read has its resting size attached, not just the top of book.

Continuous full-depth capture

The book is polled continuously at full depth from Kalshi's public REST orderbook, from a US region (Kalshi is a US-regulated exchange), so it is captured the way the exchange actually serves it.

Underlying joined per snapshot

Historical queries join the nearest preceding Binance reference by timestamp when available. The field can be null and is not described as an exchange-native Kalshi price.

Captured live, because depth can't be backfilled

Order-book history cannot be reconstructed after the fact, so we record it continuously — our Kalshi archive already spans 170 million snapshots reaching back to January 2026.

Inspect the data before integrating

Start with a bounded sample, verify the fields and timestamps, then choose the API or research workflow that matches the job.

Questions, answered.

Historical queries ASOF-align the nearest preceding Binance spot/futures reference when one exists. The field is nullable and uses the stored Kalshi receive timestamp for alignment.

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