Polymarket self-calibrating weather-trading Python bot (Full Guide) run the... smartest weather-trading bot with 0 coding knowledge after reading this article: what's inside: > github with full Python code > trading 20 cities & 4 continents > 3 forecast sources {ECMWF, HRRR, METAR} > EV+ automatic calculation for each trade > auto-sizing based on the Kelly Criterion > full-data storage {forecast, trade, resolution} > self-calibration based on snapshots & data logic of the bot: • get 3 type of forecasts from Open-Meteo API • compare station data to 1h forecasts to get real data • calculate +EV per $1 using the {min_ev} parameter • detemine size based on Kelly Criterion • run a 1000$ test-simulation using the strategy • snapshot each trade, forecast, and resultion • auto-calibrates every 30 forecasts per city This bot won't print you $500 next day after setup, but it will give you a sandbox for testing own strategies.show more

8 free Polymarket Trading Bots on GitHub (from Beginner... Friendly to Advanced Level). Each of these repos comes with a detailed step by step setup and usage guide in English. > Beginner Level - 5 min setup 1. This bot includes 120 ready to use strategies and tools for trading on prediction markets (Binance-Polymarket latency, Smart Routing, Penny Clipper, Momentum, DCA bots, Expiry Fade and more). It was built by a Cambridge computer science student who won a hackathon with this bot. GitHub: 2. A trading bot with a Smart Money strategy - it finds top traders in selected markets, filters them by Pnl, win rate, stable performance and then creates a list for automated copy trading. GitHub: 3. This is a bot toolkit that includes Polymarket - Kalshi arbitrage, whale alerts, market making, spread farming, sports trading and more. GitHub: 4. A weather trading bot from Chinese dev that analyzes different sources in real time, like forecasts, airport data and aviation observations (METAR + SPECI) to get the latest temperature data and generate a detailed weather report for a specific city and day. GitHub: 5. A huge collection of 30+ free trading bots and services for prediction markets. GitHub: > Advanced bot setup 1. This bot analyzes the real trading behavior of any Polymarket trader. It finds repeated patterns in his trades, shows which strategies he uses and helps you understand how to adapt them to your own trading. GitHub: 2. A bot that automatically manages all your limit orders on Polymarket to maximize liquidity rewards. GitHub: > A full ML weather model 1. A machine learning weather model that learns from weather forecasting errors. Instead of blindly trusting forecasts, it analyzes how different weather sources have historically overestimated or underestimated temperature values in specific cities and conditions. Then it automatically adjusts new forecasts to produce more accurate predictions. GitHub: All of these bots also support Dry Run mode, so you can test them on real markets without risking any funds.show more

I rebuilt my Polymarket weather bot Launched a simulation... with $1,000 An hour later, it was already $1,250. Another hour later - $680 The problem was simple: the forecast changed, but the bot didn't know about it and continued to hold its position That's exactly what I'm fixing in version v2 What I'm adding: 1. Expected Value EV = (p · b) − (1 − p) Before every entry the bot calculates expected value. Negative EV - no trade. But EV is useless if p comes from nowhere 2. Kelly Criterion f* = (p · b − q) / b Determines exactly how much to bet based on real edge Small edge → small position. Large edge → larger. Fixed sizing can't do this 3. Brier Score BS = (1/n) · Σ(fₜ − oₜ)² Measures how accurate our probabilities actually are. If the bot assigned 80% but the outcome won 40% of the time - Brier Score catches that 4. Calibration on own data After each trade the bot saves city, month, bucket, forecast at entry, final result History accumulates → bot calculates Brier Score on its own trades → if Chicago in March is consistently off - p for that city and month gets adjusted automatically 5. Adding new data sources Instead of relying on a single source, the bot will draw on several sources at once, and if the forecasts match, it will enter into a trade Every cycle of v2: - scan markets - check station forecast - apply calibration - calculate EV - apply Kelly - enter or skip - monitor every minute - close if forecast changes Btw, here's a short video clip showing the terminal in action A major update is coming soonshow more

How to build your own weather trading bot Every... weather trader making money on Polymarket follows the same 7 steps. Free data. Simple formula. Repeat daily Traders making $20k-$180k all started here free APIs, basic math the crowd ignores, and patience Here's the playbook: Step 1: Pick 2-3 cities Don't try to trade everything. Start with NYC, Chicago, and one international city. Learn how the forecast behaves for those exact locations. Fewer cities = faster feedback loop Start copy-trading any trader even with $10 → Step 2: Pull free forecast data Open-Meteo API free, no API key, updates every 6 hours. NOAA official US government forecasts, 85-90% accurate at 1-2 days. Windy / Ventusky, visual model viewers to sanity-check your data These are the same data sources the top weather traders use. All free. All public Step 3: Turn forecasts into probabilities The market shows 8-12 temperature buckets (25°C, 26°C, 27°C). Your job: calculate the real probability for each bucket based on the forecast Simple method: > take the forecast daily max > assume ±1.5°C error range > simulate 50,000 scenarios > count how many land in each bucket > that's your probability per bucketshow more

I found 7 free Polymarket trading bots on GitHub... for 7 different trading situations… Each of these bots comes with a detailed step by step setup and usage guide in English: 1. This bot includes 118+ ready to use strategies and tools for trading on prediction markets (Momentum, Binance-Polymarket latency, Penny Clipper, Smart Routing, Expiry Fade, DCA bots and more). Built by a Cambridge computer science student who won a hackathon with this trading bot. GitHub: 2. This bot automatically manages all your Polymarket limit orders to maximize liquidity rewards. GitHub: 3. A weather bot from a Chinese dev, that analyzes multiple sources in real time, like forecasts, airport data and aviation observations (METAR + SPECI) to get the most accurate temperature data and generate a detailed weather report for a specific city and day. GitHub: 4. A bot that automatically searches for arbitrage opportunities between Polymarket and Kalshi. GitHub: 5. This is a bot-toolkit that includes copy trading, arbitrage, market making, whale alerts, spread farming, sports trading and more… GitHub: 6. A smart money trading bot - it looks for the most successful traders in selected markets, filters them by Pnl + win rate, and then creates a list for automated copy trading. GitHub: 7. A large collection of 20+ free trading bots for prediction markets. GitHub: Every bot here has a Dry Run mode, so you can test it on real markets without risking any funds.show more

The best Polymarket Quant bot for copy-trading with a... 99.3% win rate. backtested strategy on 72M Polymarket/Kalshi trades to hit +$805K PnL on 27,000 predictions. bot doesn't gamble - it uses math and statistics in its algo to consistently hit 99% win rate. his algo decoded: 1. Mispricing formula based on 72M trades data, traders constantly overpay for cheap contracts (0.1¢–50¢) most of the edge sits in (80¢-99¢) contracts - that's the range where the bot mostly trades • formula: δ = actual win rate - implied probability bot applies this to every trade to find the edge. // 2. Expected value calculation EV tells you whether a bet is worth taking, regardless of the outcome of any single trade. • formula: EV = (P win × Payout) - (P lose × Cost) bot calculates it to understand if the trade is worth the risk. // 3. Kelly Criterion sizing most powerful position sizing formula ever discovered for gambling, trading and prediction markets it tells the algo what % of your portfolio to size into each bet to win long term. • formula: f* = (p * b - q) / b mispricing found → EV calced → kelly sizing → enter profile: start copy trading the bot with as little as $10 using Ares: 2 more formulas behind its algo revealed in the article below ↓show more

THIS OPENCLAW BOT TURNED $50 INTO $27,000 TRADING WEATHER... MARKETS ON POLYMARKET. IT USES METEOROLOGICAL DATA HOURS BEFORE PUBLIC FORECASTS.show more

I found 6 free Polymarket trading bots on GitHub... for 6 different trading situations… Each of these repos comes with a detailed step by step setup and usage guide in English. > Easy 5 min setup 1. This bot includes 118 ready to use trading strategies and tools for prediction markets (Binance-Polymarket latency, Penny Clipper, DCA bots, Smart Routing and more). Additionally, it can trade autonomously across hundreds of different markets on major prediction platforms, DEXs and EVM chains. You can see this bot in action in the demo below. 2. A huge trading bot toolkit that includes Polymarket-Kalshi arbitrage, general arbitrage, copy trading, whale tracking, sports arbitrage, spread farming and more. 3. A weather trading bot that collects the latest temperature data from different sources (forecasts, public airport data and aviation observations like METAR) to generate a detailed weather report for a specific city and day. > Advanced setup 4. This bot can automatically manage all your limit orders on Polymarket to maximize liquidity rewards. 5. A trader behavior analysis bot that finds repeated patterns in his trades, shows which strategies he uses and helps you understand how to adapt them to your own trading. 6. A trading bot with a Smart Money strategy - it finds the best pnl traders in selected markets, filters them by win rate and consistency, and then creates a list for automated copy trading. All of these bots also support dry run mode, so you can test them on real markets but without risking any finds.show more

Weather trading bots making thousands $ on Polymarket by... simple arbitrage. > Scanning weather markets every 2 mins and comparing data to NOAA forecast for location/date > If they see undervalued temperature bucket (<0.15¢), they buy it and flip for profit. Start testing with small sum $2-5 to calibrate your bot and give it data for analysis. Scale it when you see $20-50 of consistent revenue for several days. Check out this example of a bot account raking in over $65k profit from automated weather trades on Polymarketshow more

Claude Opus 4.7 + Polymarket - the best trading... bot setup $388 → $93,000 in one month Bot scans Polymarket weather markets every 60 min Pulls 3 independent forecasts per city: ECMWF, HRRR, NOAA METAR Matches predictions to market buckets (14°C Seoul, 48–49°F Chicago) Buys YES at 5¢ when models agree, Kelly-sized Nightly: Opus reads journal & rewrites per-city rules Fastest way to copy-trade him even with $10 using: The Stack Hermes agent (body) + Claude Opus 4.7 (brain) + Hetzner $5 VPS + Telegram gateway + Visual Crossing API. Open-source repo: alteregoeth-ai/weatherbot. Funding – $10 min / $50 recommended in USDC.e – 2 POL for gas (~$1) – Approve 3 Polymarket contracts (CTF Exchange, Neg Risk, Router) Setup Time ~30 minutes. No code required. Just copy-paste 8 prompts into Hermes CLI Profile:show more

I launched a weather trading bot on Polymarket with... $100 -> $8,000 here is how it works and how to copy it most people on polymarket price weather markets randomly based on vibes or a phone app but there is NOAA - a government agency that publishes free forecasts with 94%+ accuracy the result? you regularly see something like this: > NOAA gives a 94% probability that NYC will reach 74°F on Saturday > polymarket prices it at 11¢ the bot buys at 11¢ sells when the market corrects to 45¢ that is 4x on an almost guaranteed outcome how to launch it in 5 steps: > install OpenClaw on your pc > connect it to ChatGPT Plus + a telegram bot > create an agent on simmer markets deposit $100 > install the weather trading skill with: clawhub install simmer-weather > send the config to the bot and it starts trading the bot scans 6 cities every 2 minutes non-stop example of a real trader: profile: +$75,055 just from weather markets zero emotions. fully automated the window is still open but not forevershow more

avg $1,230/day on Polymarket. it comes from changes in... the weather forecast, which is free and open to everyone. the setup guide is in this post the market already prices the forecast itself pretty accurately. the money shows up the moment the forecast changes and the price hasn't yet. how it works in practice: when a new forecast for the next day comes out and the temperature in it moved by at least 0.5°C, you buy the option one degree closer to the new forecast. say the morning forecast promised 16.8°C in London, so the 17°C option is the priciest. in the afternoon a new forecast comes out with 15.8°C. your job is to buy 16°C while it's still cheap. the buy range where the EDGE holds: 5¢ to 60¢. the faster you do it, the higher your ROI how to set it up: 1 - get forecasts for free on Open-Meteo. it has the american GFS model and the european ECMWF. use the airport coordinates, that's where Polymarket measures the temperature. 2 - the bot should check on a timer whether a new forecast is out, and if it is, compare it to the previous one. 3 - if tomorrow's high moved by 0.5°C or more, the bot buys the option one degree closer to the new forecast. 4 - keep each trade under $25. cheap sellers on these markets are thin, and more size will eat the edge. one bot trades these forecast shifts across 50 cities every hour. in september that's avg $1,230/day here's the profile:show more

Found a trader who turned $8 into $56,000 trading... weather on Polymarket his strategy looks dumb until you see the math His profile: How he does it: -> only trades weather markets (temperature in London, Milan, Paris, Sao Paulo) -> waits until the day before resolution when the forecast is locked -> buys outcomes at 99c that resolve at $1 = +1c per trade -> 4,103 predictions, mostly micro-trades -> compounds tiny edges into 5 figures The part most people miss: his edge isn't predicting the weather -> it's noticing that on resolution day, the market still trades at 99c instead of $1 The math behind this is in the article below: the script from the article + free NASA data lets you run the same logic on any monthly weather, CPI or temperature market 👇 Copy him with me:show more

I’m making $2,200/weekly from Weather Arbitrage. I’m not posting... this as clickbait. If you can’t replicate it, feel free to unfollow me. About a month ago, I found a Polymarket Account using a clever strategy: Weather Arbitrage. It caught my attention. After digging into how it works, I saw that this trader focuses only on daily temperature markets for cities like NYC, LA, Atlanta, Denver, Chicago, Seoul, London, Shanghai, San Francisco, and Munich. The key insight is that each Polymarket weather market resolves based on a specific airport weather station, for example NYC = LaGuardia / KLGA, Dallas = Love Field / KDAL, while most retail traders rely on city center data. The temperature difference between those can be 3–8°F. According to his profile: > He built a bot that profits from this gap between official weather data and uninformed retail traders. I figured I wasn’t skilled enough to build something like that myself, so I set up a copy trading bot with 0% fees and 100 ms latency: > This copy trading bot is the best solution on the market, at least because it doesn’t charge any fees. Now I copy his trades exactly and made almost $10,000 in a month. It actually works, guys. Check it out. This isn’t clickbait or a joke.show more

+$8,500 IN 30 SECONDS. THIS FUCKING GENIUS BUILT HIS... OWN TRADING BOT WITH AI 🤯 He didn’t spend months learning how to code. He used an AI tutorial to build a bot that analyzes the market, finds setups, and executes trades based on his strategy. Now that tutorial is basically helping him automate his trading. Here’s how he did it ↓ → Picked one simple trading strategy → Used AI to turn the rules into a trading bot → Added entry + exit conditions → Backtested the strategy → Automated the execution → Let the bot scan for setups The key part: He didn’t ask AI to magically “make money.” He gave it a clear strategy and used AI to turn those rules into an automated system. One trade reportedly made him +$8,500 in around 30 seconds. Obviously, this doesn’t mean every trade will look like that. But the idea is powerful: You don’t necessarily need to become a programmer to start building your own trading tools. AI can help turn a trading idea into something you can actually test and automate. Here’s the full strategy + how he built the botshow more

I OPEN-SOURCED MY CRYPTO TRADING BOT ON GITHUB. 100%... FREE It's called Cabbage. A spot trading bot you can backtest, paper-trade and run live, one command each. Full step-by-step setup guide. It runs on two models: > Astra (GPT-6) built it. Smart but slow. It thinks, writes the code, explains every decision. > Jev runs it. Jev doesn't talk. One word and a probability, in milliseconds. BUY, HOLD or SELL. Under 0.80 it waits. Here's what's inside: 1. Signal engine RSI 14 + EMA 12/26 confluence. It only reads closed candles, so no fake signals from a candle that's still moving. 2. Hard risk rules Fixed ticket size and a percentage stop-loss on every entry. The bot can't size up because it "feels confident". 3. Backtest → HTML report Event-driven backtest that replays history candle by candle, like it's trading live. You get a full HTML report at the end. 4. Paper trading Real exchange data, local fills, zero money at risk. Run one iteration to test, then leave it running. 5. Live trading Real orders on any exchange CCXT supports. Your keys stay in your own .env file. 6. Doctor command Checks your config and exchange connection before you trade. No orders placed. State is saved in SQLite per market and pair, so a restart doesn't wipe your positions. Built on Investing Algorithm Framework 9. Apache-2.0, fork it and make it yours.show more

This guy made $600,000 on Polymarket using software, buying... markets for $20 His trading bot makes 2,774 trades per hour or 46 trades per minute. He trades the divergence between Binance/Chainlink data and people’s reaction on Polymarket. His strategy is simple: > Enters positions only with limit orders > Works as both maker and taker > Buys Up or Down while the probability on Polymarket has not yet caught up with the current price on Binance/Chainlink Here is the link to this guy’s account: You can track smart money via the TG bot:show more

Claude and a free weather API will earn you... $100k+. Success rate for beginners: 80%. Complete guide and algorithm for building Polymarket weather trading bot. Simple logic, a low entry budget and high ROI -that’s why weather bots are so clean. Onchain proof these bots exist: 1st bot: 2nd bot: I verified their profitability by myself copying every trade - each bot's win rate over time ranges from 80 to 90%. I grew my starting capital by +40% in just one week. You can copy their trades and see for yourself in two clicks through this bot: The alpha is simple: you're not trading weather. You're trading other people's ignorance. Gap between what the crowd prices and what 51 ensemble models say. Polymarket asks: "Will Atlanta hit 95°F tomorrow?" Normies bet on vibes. You bet on math. The core tool: Open-Meteo API. Free. No key needed. 51-model ensemble. Clean JSON. Cooked and ready. Update every 30 min. Hardcode your city coordinates - don't waste time on geocoding at runtime. This single endpoint beats most paid tools for what Polymarket actually needs. The edge in one sentence: Market is heavy on 16°C. Your 51-model ensemble points at 19°C. That's your trade. Find that gap systematically across every city market, every day - and you have a scanner. That's what separates consistent traders from gamblers. How to start: - Week 1: Open-Meteo + tropicaltidbits. Pick one city market. Track model vs market price daily. Don't trade yet — just watch where you'd have been right. - Weeks 2–3: Automate the pull. Log ensemble divergences. Build the scanner. - Week 4: Now you have an edge. Trade it. Most people want to skip to week 4. That's exactly why most people lose. Now you have the algorithm framework plus a complete guide to get started. All that's left is to actually do it. Bookmark this post so you can come back to it when you start building the bot.show more

$1,500 → $33,000 on 5min BTC markets in 2... days This is the new reality. It stops being gambling the moment you define an exact algorithm. Here are the recommendations on how to create the same trading bot: → Write your code in Rust – it offers C++ level speed, and there’s an official polymarket-client-sdk available. → Minimize Latency – your trading bot must be deployed in the same data center as Polymarket: AWS eu-west-2 (London). This ensures the lowest possible execution lag. → Price Discovery – Polymarket pulls prices from Chainlink, but Chainlink doesn’t "create" the price; it simply aggregates and broadcasts it. Use Binance – as the largest spot exchange, it is the primary source of price discovery. → Apply the Black-Scholes Model for binary options – this is exactly what will help you identify +EV opportunities by calculating all necessary Greeks and variables. → Don’t turn it into a casino – use the Kelly Criterion. It acts as your risk manager, calculating the optimal % of your bankroll for every single position. If you want to earn like trading bot devs – you need to think like them.show more

> you close your laptop for a few days... > leave $1,000 running on a Claude bot > come back > $1,000 → $55K > the agent was trading > pulling odds > comparing to live data > spotting mispriced contracts > 50–300% per trade > short-term BTC markets > setup time: ~15 minutes > you explained the idea once > Claude built the agent > it made the tradesshow more

Some trader withdrew all money from polymarket and came... back a month later deposited $2,000 with a new strategy now sitting at $137,000 profit he switched to weather markets every day collects data from 5 APIs simultaneously: → Open-Meteo (GFS, ECMWF models) → OpenWeatherMap → WeatherAPI → Tomorrow(.)io → Visual Crossing if 4 out of 5 models agree on one forecast edge exists but the most interesting part - temporal arbitrage cities with best liquidity: NYC, London, Atlanta, Dallas i'm copying his trades using PolyCop started with $500 address: 0xcbbc5e035504421b084ad9248b660f6e9618b5d0show more