Polymarket NASCAR data: race-day pricing at 250ms

NASCAR sits in the motorsport long tail of the sports catalog, listed continuously alongside Formula 1 and other series. The coverage page reports these families as long tail rather than counted splits.

The record is identical regardless: any NASCAR market PolyOrderbooks lists stores as a full L2 book four times per second, while the official API serves only the live, current-moment ladder.

Race-winner and driver contracts trade as binaries, and each resolves to the shared record — bid and ask ladders with sizes, a captured_at timestamp, and the winning outcome once settled.

This page deliberately quotes no NASCAR-specific count: the long-tail families are reported as indicative sizes, and inventing a number would violate the site's measured-facts rule.

• Live ladder — official /book, free and keyless, current moment only (what the API serves).
• Historical depth — full L2 books at 250ms over REST, free Starter with 3 days, paid windows to 120 days.
• Discovery — /v1/series for motorsport events; /v1/markets for questions and slugs.
• Coverage — measured counts per sport on the sports data page.

A Sunday race reprises the winner market at the stage breaks and the late-race cautions, not in the mid-pack laps. The official API serves those live frames free; the archive preserves the last caution's ladder so the final two laps can be replayed exactly as traded.

NASCAR shares the motorsport long tail with Formula 1 inside the 700k+ catalog pool: race and driver questions, listed continuously, counted as part of the combined sports market count rather than a separate split.

Three patterns belong in any record-based study: the stage-end caution's effect on the favorite line, the pit-stop reprise when leaders pit off-sequence, and the overtime setup that converts a crashed leader into an instant favorite.

Practical access runs through /v1/series for the race weekends and /v1/markets for the night's questions, with the archive window around the final stage returning the complete 250ms book for the finish.

The volatility cluster is the late-race restart: the executable side flips inside two laps far more often than during green-flag runs.

As long tail, treat single races as case studies unless the whole season is archived into one query window.

Starter's 3 days capture a full race weekend; Pro stretches to 120 for season studies.

Study one: measure the winner-market reprise on each stage-break caution, counting how many frames separate the yellow flag from the new executable price.

Study two: replay a late-race restart and compare the favourite's floor before and after the leader pits; sub-second repricing is the documented norm elsewhere on the venue.

Study three: test whether overtime setups convert a crashed leader into an instant favourite faster than a mid-race caution does.

One race weekend fits the free tier; a full season in Pro's 120-day window is the scale at which any of these patterns starts to generalise.

The same record also supports the occasional pedagogical pull: a rain-delayed race, a fuel-mileage finish, and a stage break under caution draw three W-shaped books into one season's window, which is a fine standalone exhibit for anyone learning to read motorsport ladders.

Start with one stage break: pull the winner-market window around a stage-ending caution and count the frames between the yellow flag and the new executable price. The caution-to-reprice lag is the single most instructive number in the whole motorsport record.

Then pull an overtime restart from the same race and compare the favorite's floor before and after the leader pits; the two windows together show the difference between structured repricing and chaos repricing.

Resolve the race's markets and keep them queryable, then repeat for the full season in the Pro window — that accumulation is what turns a race weekend into a real dataset.

• Sports data
• Market data
• Order book data