A developer and his friend tried to replicate one of the most profitable bots on Polymarket — the one that made ~$32k by sniping stale orders in “Will Company XYZ Beat Earnings?” markets right after announcements.
Here’s what they learned.
The Target Strategy
The dominant bot waits for earnings releases, then instantly buys the winning side (YES or NO). Many retail traders forget to cancel their limit orders before the announcement, leaving stale liquidity for the bot to sweep.
It’s nearly risk-free when executed fast enough.
Technical Approach & Challenges
Infrastructure Choices:
- Hosted in Ireland (eu-west-1) — closest practical location to Polymarket’s CLOB in London (eu-west-2) without blocked UK IPs.
- Wrote the core in Rust for type safety and performance (though thoughtful Python could suffice).
- Avoided official Polymarket SDKs — they add too many helpful but slow network checks before placing orders.
Data Feed Problems:
- Tried scraping newswires → too slow
- Tried Benzinga low-latency feed → even slower
- Found a service delivering announcements in ~500ms → still too slow
The order book was already swept by the time their bot received the news.
Key Takeaways
- Network latency dominates — most of the delay is not in code but in getting the news faster than everyone else.
- Ultra-low-latency news feeds are expensive — the top bots may be using prohibitively costly services as a side project or have better proprietary access.
-
API granularity limits visibility — even with
nano_match_timefields, real resolution happens seconds later on-chain. - Partial success is possible — they caught some trades during EPS ambiguity or when faster bots hit size limits.
- Pure speed competitions are brutal — unless you have a real edge in data acquisition, you’re competing against professionals who treat this as serious business.
Lessons for Bot Builders in 2026
- Optimize ruthlessly — eliminate every unnecessary network call and SDK abstraction.
- Data acquisition is the real moat — faster news, better parsing, or alternative signals matter more than language choice.
- Rust (or highly optimized code) helps, but thoughtful architecture in Python/Node.js is often “fast enough” for most strategies.
- Start with easier edges — late-cycle microstructure, regime-aware trading, or copy-trading proven wallets often yield better results than pure speed races.
- Expect iteration — even strong ideas can fail due to invisible infrastructure advantages held by top players.
The project was eventually mothballed, but the learning experience was invaluable. It highlights a core truth in prediction market automation: the highest edges often hide in information speed and operational discipline, not just clever algorithms.
If you’re building low-latency bots on Polymarket, focus first on your data pipeline and news acquisition. Everything else is secondary.
If you have more questions, please feel free to contact me at any time: https://t.me/FatherSon97
Tags: #Polymarket #TradingBots #LowLatency #EarningsTrading #PredictionMarkets #DeFi #Web3 #QuantitativeTrading #Rust #Fintech
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