Valorant historical data
Valorant is a Polymarket esports series with markets recurring daily. Marketlens has captured 223 markets since August 15, 2026, of which 206 resolved, with $974.4K in traded volume. Every market's order book is stored in full: periodic L2 snapshots plus every individual price change with a millisecond timestamp, alongside trades, candles, and the final resolution outcome.
Data as of 2026-08-16 · series slug valorant
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 223 markets.
Valorant: GIANTX GC vs SK Nebula - Map 1 Winner
closed 2026-08-16 · volume $1.2K · resolved SK Nebula
Games Total: O/U 2.5
closed 2026-08-16 · volume $177 · resolved Under
Map 1 Rounds Handicap: Fire Flux Esports (-2.5) vs Joblife (+2.5)
closed 2026-08-16 · resolved Fire Flux Esports
Backtest this series
from marketlens import MarketLens
client = MarketLens()
result = client.backtest(
MyStrategy(), "valorant", subtype="moneyline",
after="2026-08-15", before="2026-08-17", initial_cash=1_000,
)
result.show() # inspect the run in the dashboardAvailable datasets
Common questions
How many Valorant markets are in the archive?
223 markets from August 15, 2026 through August 16, 2026, of which 206 have resolved and 17 are active.
What data exists for each Valorant market?
Full L2 order book history (snapshots plus every price change at millisecond resolution), individual trades, OHLC candles, and the resolution outcome. All of it is queryable by the series slug "valorant" through the API and Python SDK, or downloadable as Parquet.
How much does a typical Valorant market trade?
Average traded volume is $8.5K per market, $974.4K across the series.
Can I backtest strategies on Valorant?
Yes. Pass the slug "valorant" to client.backtest() in the Python SDK. Execution mode replays every market's order book tick by tick and fills simulated orders against real historical depth with queue priority, latency, and fee modelling; Alpha mode replays one bar per market for slower signals over long windows. This series mixes several bet types, so pass subtype= (e.g. "moneyline") to backtest one type at a time.
Related series: Dota 2, League of Legends, Counter Strike, or all esports series.
Try it
Replay Valorant tick by tick
The free tier includes 5M rows per day with full API and full archive access, no card required.
$ pip install marketlens