National LeaguePolymarket historical data and price history
National League: a Polymarket sports series with markets recurring daily. Marketlens has captured 1,617 markets since September 18, 2026, of which 1,655 resolved, with $808.2K 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.
For the sports archive as a whole, see Polymarket sports odds history.
Data as of 2026-10-12 · Polymarket series National League · slug soccer-enl
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 1,691 markets.
Backtest this series
from datetime import datetime, timedelta, timezone
from marketlens import MarketLens, Strategy
class MyStrategy(Strategy):
def on_market_start(self, ctx, market, book):
ctx.buy_yes(size=10)
client = MarketLens()
end = datetime.now(timezone.utc) - timedelta(days=1)
result = client.backtest(
MyStrategy(), "soccer-enl", subtype="moneyline",
after=end - timedelta(minutes=15), before=end, initial_cash=1_000,
)
result.show() # inspect the run in the dashboardAvailable datasets
Common questions
How many National League markets are in the archive?
1,617 markets from September 18, 2026 through now, of which 1,655 have resolved and 36 are active.
What data exists for each National League market?
Full depth L2 order book snapshots at regular intervals, individual trades, OHLC candles, and the resolution outcome, with the full price change stream at millisecond resolution on the most actively traded markets in the series. All of it is queryable by the series slug "soccer-enl" through the API and Python SDK, or downloadable as Parquet.
How much does a typical National League market trade?
Average traded volume is $882 per market, $808.2K across the series.
Can I backtest strategies on National League?
Yes. Pass the slug "soccer-enl" 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, ATP, MLB, WTA, NFL 2026, Premier League 2025, or all sports series.
Try it
Pull National League 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