League of LegendsPolymarket historical data and price history

League of Legends: a Polymarket esports series with markets recurring daily. Marketlens has captured 4,725 markets since August 15, 2026, of which 4,855 resolved, with $70.9M 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 esports archive as a whole, see Polymarket esports data.

Data as of 2026-09-28 · Polymarket series League of Legends · slug league-of-legends

Markets
4,856
Resolved
4,855
Traded volume
$70.9M
Avg volume / market
$19.1K
Cadence
daily
Coverage from
2026-08-15
Data through
now
Category
Esports

Markets by bet type

spread580
moneyline512
segment_winner:game1425
segment_winner:game2423
segment_winner:game3210
segment_winner:game4201

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 4,856 markets.

LoL: Cloud9 vs Team Liquid - Game 4 Winner

closed 2026-09-28 · resolved Team Liquid

Total Kills Over/Under 24.5 in Game 2?

closed 2026-09-28 · volume $2.6K · resolved Under

LoL: Cloud9 vs Team Liquid - Game 2 Winner

closed 2026-09-28 · volume $28 · resolved Team Liquid

Backtest this series

python
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(), "league-of-legends", subtype="moneyline", after=end - timedelta(minutes=15), before=end, initial_cash=1_000, ) result.show() # inspect the run in the dashboard

Available datasets

Order book snapshots and deltasfull L2 depth, millisecond price changes
Tradesindividual fills with side and size
CandlesOHLC at multiple resolutions
Bulk Parquet exportsfull markets for offline research
Backtestingtick level replay with realistic fills

Common questions

How many League of Legends markets are in the archive?

4,725 markets from August 15, 2026 through now, of which 4,855 have resolved and 1 are active.

What data exists for each League of Legends 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 "league-of-legends" through the API and Python SDK, or downloadable as Parquet.

How much does a typical League of Legends market trade?

Average traded volume is $19.1K per market, $70.9M across the series.

Can I backtest strategies on League of Legends?

Yes. Pass the slug "league-of-legends" 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: Counter Strike, Dota 2, Valorant, or all esports series.

Try it

Pull League of Legends books in one call

The free tier includes 2M data rows and every market open in the last 7 days, no card required.

bash
$ pip install marketlens