Singapore Daily Weather historical data
Singapore Daily Weather is a Polymarket weather series with markets recurring daily. Marketlens has captured 275 markets since July 6, 2026, of which 242 resolved, with $578.6K 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 2026-08-05 · series slug singapore-daily-weather
Resolution outcomes
Outcomes across 242 resolved markets with a recorded winning outcome. Settlement in the archive is by winning outcome, not by final traded price.
Recent markets in this series
- Will the highest temperature in Singapore be 34°C on August 4?
- Will the highest temperature in Singapore be 29°C on August 4?
- Will the highest temperature in Singapore be 30°C on August 4?
Backtest this series
from marketlens import MarketLens
client = MarketLens()
result = client.backtest(
MyStrategy(), "singapore-daily-weather",
after="2026-07-29", before="2026-08-06", initial_cash=1_000,
)
result.show() # inspect the run in the dashboardAvailable datasets
Common questions
How many Singapore Daily Weather markets are in the archive?
275 markets from July 6, 2026 through August 5, 2026, of which 242 have resolved and 33 are active.
What data exists for each Singapore Daily Weather 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 "singapore-daily-weather" through the API and Python SDK, or downloadable as Parquet.
How often do Singapore Daily Weather markets resolve No?
Of 242 resolved markets with a recorded outcome, 220 resolved No (90.9%) and 22 resolved Yes.
How much does a typical Singapore Daily Weather market trade?
Average traded volume is $2.8K per market, $578.6K across the series.
Can I backtest strategies on Singapore Daily Weather?
Yes. Pass the slug "singapore-daily-weather" 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.
Related series: London Daily Weather, Hong Kong Daily Weather, Seoul Daily Weather, NYC Daily Weather, Shanghai Daily Weather, Paris Daily Weather, or all weather series.
Try it
Replay Singapore Daily Weather tick by tick
The free tier includes 5M events per day with full API and full archive access, no card required.
$ pip install marketlens