ATP Tennis: Shanghai, China WinnerPolymarket historical data and price history
ATP Tennis: Shanghai, China Winner: a standalone Polymarket sports event with 37 markets and $82.2K 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 October 13, 2026 through October 18, 2026.
Data as of 2026-10-19
Top 5 of 37 markets
Query this event
from datetime import datetime, timedelta, timezone
from marketlens import MarketLens
client = MarketLens()
[event] = client.events.list(q="ATP Tennis: Shanghai, China Winner", 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 "ATP Tennis: Shanghai, China Winner"?
37 markets with full depth L2 order book history recorded since October 13, 2026, market metadata with lifetime traded volume, and the winning outcome for each market once it resolves.
How much has "ATP Tennis: Shanghai, China Winner" traded on Polymarket?
$82.2K in cumulative traded volume across the event's markets. Per market volumes are listed in the table on this page.
How do I download "ATP Tennis: Shanghai, China Winner" data?
Query it through the REST API or the Python SDK (pip install marketlens): search events for "ATP Tennis: Shanghai, China Winner", 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.
Related events: F1 Drivers' Champion, Pro Football: 2027 Champion, UEFA Champions League: 2027 Champion, or the full event list.
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