Dallas Daily Weather historical data
Dallas Daily Weather is a Polymarket weather series with markets recurring daily. Marketlens has captured 297 markets since March 1, 2026, of which 275 resolved, with $718.5K 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 dallas-daily-weather
Resolution outcomes
Outcomes across 275 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 Dallas be between 100-101°F on August 4?
- Will the highest temperature in Dallas be between 112-113°F on August 4?
- Will the highest temperature in Dallas be 116°F or higher on August 4?
Backtest this series
from marketlens import MarketLens
client = MarketLens()
result = client.backtest(
MyStrategy(), "dallas-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 Dallas Daily Weather markets are in the archive?
297 markets from March 1, 2026 through August 5, 2026, of which 275 have resolved and 22 are active.
What data exists for each Dallas 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 "dallas-daily-weather" through the API and Python SDK, or downloadable as Parquet.
How often do Dallas Daily Weather markets resolve No?
Of 275 resolved markets with a recorded outcome, 248 resolved No (90.2%) and 27 resolved Yes.
How much does a typical Dallas Daily Weather market trade?
Average traded volume is $3.3K per market, $718.5K across the series.
Can I backtest strategies on Dallas Daily Weather?
Yes. Pass the slug "dallas-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 Dallas 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