WNBA historical data
WNBA is a Polymarket sports series with markets recurring daily. Marketlens has captured 91 markets since August 2, 2026, of which 91 resolved, with $163.1K in traded volume. Order books are stored at full depth, with every individual price change captured at millisecond resolution on the most actively traded markets, alongside trades, candles, and the final resolution outcome.
Data as of 2026-08-16 · series slug wnba
Markets by bet type
Market counts by bet type across the series. Pass any of these as subtype= to backtest that type on its own.
Markets in this series
The most recently resolved of 91 markets.
A'ja Wilson: Points O/U 25.5
closed 2026-08-16 · resolved Yes
Courtney Williams: Assists O/U 4.5
closed 2026-08-16 · resolved No
Natasha Howard: Assists O/U 3.5
closed 2026-08-16 · resolved No
Backtest this series
from marketlens import MarketLens
client = MarketLens()
result = client.backtest(
MyStrategy(), "wnba", subtype="moneyline",
after="2026-08-09", before="2026-08-17", initial_cash=1_000,
)
result.show() # inspect the run in the dashboardAvailable datasets
Common questions
How many WNBA markets are in the archive?
91 markets from August 2, 2026 through August 16, 2026, of which 91 have resolved.
What data exists for each WNBA market?
Full depth L2 order book snapshots at regular intervals and the resolution outcome, with the full price change stream, trades, and candles on the most actively traded markets in the series. All of it is queryable by the series slug "wnba" through the API and Python SDK, or downloadable as Parquet.
How much does a typical WNBA market trade?
Average traded volume is $3.9K per market, $163.1K across the series.
Can I backtest strategies on WNBA?
Yes. Pass the slug "wnba" to client.backtest() in the Python SDK. Execution mode replays order books against real historical depth; Alpha mode, one bar per market, covers every market in the series and suits its longer horizons. This series mixes several bet types, so pass subtype= (e.g. "moneyline") to backtest one type at a time.
Related series: FIFA World Cup, MLB, ATP, WTA, UFC, FA Community Shield, or all sports series.
Try it
Pull WNBA books in one call
The free tier includes 5M rows per day with full API and full archive access, no card required.
$ pip install marketlens