DFB-Pokal historical data
DFB-Pokal is a Polymarket sports series with markets recurring daily. Marketlens has captured 69 markets since August 7, 2026, of which 69 resolved, with $1.1M in traded volume. Every market's order book is captured as full depth L2 snapshots at regular intervals, alongside trades, candles, and the final resolution outcome.
Data as of 2026-09-04 · series slug dfb-pokal
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 69 markets.
Backtest this series
from marketlens import MarketLens
client = MarketLens()
result = client.backtest(
MyStrategy(), "dfb-pokal", subtype="total",
after="2026-08-26", before="2026-09-03", initial_cash=1_000,
)
result.show() # inspect the run in the dashboardAvailable datasets
Common questions
How many DFB-Pokal markets are in the archive?
69 markets from August 7, 2026 through September 2, 2026, of which 69 have resolved.
What data exists for each DFB-Pokal market?
Full depth L2 order book snapshots at regular intervals, individual trades, OHLC candles, and the resolution outcome. All of it is queryable by the series slug "dfb-pokal" through the API and Python SDK, or downloadable as Parquet.
How much does a typical DFB-Pokal market trade?
Average traded volume is $18.5K per market, $1.1M across the series.
Can I backtest strategies on DFB-Pokal?
Yes. Pass the slug "dfb-pokal" 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. "total") to backtest one type at a time.
Related series: FIFA World Cup, MLB, ATP, WTA, UFC, WNBA, or all sports series.
Try it
Pull DFB-Pokal 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