Polymarket esports historical data
Polymarket prices professional esports matches across League of Legends, Dota 2, Counter-Strike, and Valorant: match winner markets for every fixture, with map and game winner markets on the bigger series. Odds reprice through picks, drafts, and every fight, and tournament schedules produce a steady stream of statistically similar matches.
Marketlens captures these books the same way it captures traditional sports: full order book depth through every match, with the winner stored once the platform settles. Esports coverage starts August 15, 2026, so this is a young archive that grows with every match day.
Data as of 2026-09-11
All esports series
Counter Strike
daily · 7,244 markets · $66.9M
League of Legends
daily · 3,563 markets · $59.3M
Dota 2
daily · 877 markets · $51.3M
Valorant
daily · 1,348 markets · $5.8M
Query this category
from marketlens import MarketLens
client = MarketLens()
for market in client.markets.list(category="Esports", subtype="moneyline", take=50):
print(market.question, market.winning_outcome)
# the order book of any market, at any moment of its life
[market] = client.markets.list(
series_id="counter-strike", status="resolved", take=1,
)
book = client.orderbook.get(market.id, at=market.close_time)
print(book.best_bid, book.best_ask, book.midpoint)Common questions
How many Polymarket esports markets does Marketlens have data for?
The archive covers 13,032 esports markets across 4 recurring series, of which 12,969 have resolved. Coverage runs from August 15, 2026 through September 11, 2026.
What data is available for each esports market?
Most markets have full L2 order book history (snapshots plus every price change with millisecond timestamps), trades, and candles; the longest dated books carry full depth snapshots at regular intervals alongside their trades and candles. Every market stores its final resolution outcome. Data is served through the REST API and Python SDK, with bulk Parquet exports for offline work.
How much do these markets trade?
Combined traded volume across the category is $183.2M. Per series volumes are listed in the table on this page.
Can I backtest strategies on esports markets?
Yes. Pass any series slug from this page to client.backtest() in the Python SDK. Execution mode replays the order books tick by tick and fills simulated orders against real depth with queue priority, latency, and fee modelling; Alpha mode replays one bar per market for slower signals over long windows.
Other categories: crypto, sports, weather, or the full catalog.
Try it
Pull esports books in one call
The free tier includes 25M rows per day with full API and full archive access, no card required.
$ pip install marketlens