Will Tropical Storm Lala make landfall in Hawaii as a hurricane?Polymarket historical data and price history
Will Tropical Storm Lala make landfall in Hawaii as a hurricane: a standalone Polymarket weather event with 1 market and $12.6K in lifetime traded volume. All markets have resolved, each with its winning outcome stored. Marketlens records every market's order book at full depth, coverage running since August 15, 2026 through August 19, 2026.
Data as of 2026-09-28
The market in this event
Query this event
from datetime import datetime, timedelta, timezone
from marketlens import MarketLens
client = MarketLens()
[event] = client.events.list(q="Will Tropical Storm Lala make landfall in Hawaii as a hurricane", take=1)
for market in client.events.markets(event.id, take=5):
print(market.question, market.outcomes[0].last_price)
# the order book behind any market, at any past moment
# a free key reads markets open in the last 7 days
book = client.orderbook.get(market.id, at=datetime.now(timezone.utc) - timedelta(days=2))
print(book.midpoint, book.bid_depth, book.ask_depth)Common questions
What data does Marketlens have for "Will Tropical Storm Lala make landfall in Hawaii as a hurricane"?
1 markets with full depth L2 order book history recorded since August 15, 2026, market metadata with lifetime traded volume, and the winning outcome for each market once it resolves.
How much has "Will Tropical Storm Lala make landfall in Hawaii as a hurricane" traded on Polymarket?
$12.6K in cumulative traded volume across the event's markets. Per market volumes are listed in the table on this page.
How do I download "Will Tropical Storm Lala make landfall in Hawaii as a hurricane" data?
Query it through the REST API or the Python SDK (pip install marketlens): search events for "Will Tropical Storm Lala make landfall in Hawaii as a hurricane", list the event's markets, then pull each market's order book history. Bulk Parquet exports cover full markets for offline work; the free tier reads markets open in the last 7 days and Pro the full archive.
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Try it
Pull this event's books in one call
The free tier includes 2M data rows and every market open in the last 7 days, no card required.
$ pip install marketlens