Polymarket Ticker Data: The 24-Hour Snapshot Behind Every Market

• Last price (the most recent executable round-trip mid, reported in cents), 24h volume, and open interest are the ticker fields most apps render.
• 24h volume is a windowed rollup — recompute it from the frame record and it disagrees with the serve-time value if the window boundary is not the same second.
• Open interest on the ticker matches the frame OI only at the instant captured; the archive OI is a series, the ticker is a point.
• The ticker's price is a mid summary; the ladder levels and their sizes record what was executable at that timestamp.

Every ticker number is derivable from the archive, so ticker screenshots in… (historical notes) are testable: pull the market's frames for the claimed window and recompute the 24h rollup.

Because volume is cumulative per frame, the ticker's "24h volume" is the frame volume difference across the window — a one-line query on the archive that badges every screenshot as true or false.

The gap matters most at a reprice: the ticker mid, captured seconds ago, can sit on a ladder that already re-priced by a 99.6-cent bound; always tie a ticker claim to its timestamp.

• Density scans: the 24h volume per market across a series ranks the price-discovery candidates in one table.
• Ecosystem overviews: comparing ticker OI across markets shows where suspense is building before any frame-level analysis.
• Notification tests: a ticker poll at 1-minute cadence (96 samples/day) is the cheapest heartbeat; frame polling at 250ms is the audit.

• Sample the ticker for one market every minute for a day (1,440 samples) and store last price, 24h volume, and open interest at each poll.
• Join each sample to the archive frame at the same second and confirm the mid matches the ticker consistently; gaps isolate polling lag versus data error.
• Recompute the 24h volume from the frame record for the claimed window and compare to the served value; disagreement is a window-boundary note, not a bug.
• Then sample a second market by a different series type and compare how much each ticker mid moves between polls — the volatility difference is structural.

The ticker is the public face of a market, which means it is also the attack surface for inferred numbers: a stale mid on a re-priced ladder (documented one-second moves) misleads anyone who treats it as a realtime quote.

Treat the ticker as a headline and the archive as the byline; a headline without the article is how dashboard snapshots become wrong in a quiet way.

The biggest honesty win: recompute the ticker's rollups yourself from the frames and you can quality-check any third-party dashboard that cites the site.

The ticker feeds watchlists and digests; the frames feed studies. Your app should refresh watchlists from the ticker at minute cadence and studies from the archive on demand.

When you publish a ticker screenshot, pair it with the timestamp and the recompute path — the two sentences that make the number trustworthy.

The ticker is the headline you can audit: last price, 24h volume, and open interest — every one recomputable from the frame record for the same window, which makes any ticker screenshot either true or false.

Two disciplines keep ticker work honest: timestamping every poll to the second, and never citing a ticker mid on a market whose ladder just repriced (one-second moves are real and documented).

At one minute of polling you observe 1,440 states a day — a genuine sub-hour heartbeat — while the archive observes the 345,600 sub-minute frames those states summarize; the pair is the whole system.

Ship the watchlist and the recompute path together: a dashboard that shows the number and the query that proves it is a dashboard nobody has to take on faith.

• price data
• ohlc data
• market metrics data