hiberius/polymarket-bot-graveyard — explained in plain English
Analysis updated 2026-05-18
Learn what mistakes lead automated Polymarket trading bots to lose money.
Read a real dataset backed analysis of whether a retail trading edge exists on short duration prediction markets.
Study code snapshots of six different bot architectures before building your own.
| hiberius/polymarket-bot-graveyard | 0xallam/my-recipe | 0xhassaan/nn-from-scratch | |
|---|---|---|---|
| Stars | 0 | — | 0 |
| Language | Python | Python | Python |
| Last pushed | — | 2022-11-22 | — |
| Maintenance | — | Dormant | — |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 4/5 | 2/5 | 4/5 |
| Audience | researcher | general | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires a Polymarket account and API access to run any bot live, reading the analysis itself needs no setup.
This project is a detailed, honest write up of six automated trading bots the creator built and shut down over three months on Polymarket, a prediction market platform. Instead of showing off a bot that made money, this repository documents failure: none of the six bots ever found a real edge, and only a small amount of real money, about $45, was ever risked before the trading account got banned for sending too many orders too quickly. Every version after that ran only in a simulated, paper trading mode. Each bot tried a different strategy: copying other traders, market making, following short term Bitcoin price swings using multiple AI models to vote on a direction, scanning hundreds of slower moving markets, and using an oracle based price model. Every one of them ran into the same wall. Professional trading firms already price these markets efficiently within seconds, so there was no real gap left for a small trader to profit from. AI models were often too slow to act before prices moved. Static pricing models broke down once market conditions shifted. The last version in the series took a different approach: instead of trading right away, it measured whether a signal actually predicted outcomes correctly before letting the bot use real money. It concluded honestly that no edge existed, and refused to trade. The author treats that correct refusal as the actual success of the project, since it stopped further losses. The repository is organized as a step by step journal, one chapter per bot, plus a final analysis document explaining the common mistakes across all six attempts. Code snapshots for each bot are included with secrets removed. It is released under the MIT license for code and Creative Commons for the documentation. Anyone considering building a similar trading bot may find this useful as a warning about what does not work and why.
A detailed post mortem of six failed Polymarket trading bots, explaining why none of them found a profitable trading edge.
Mainly Python. The stack also includes Python, Polymarket API.
Code is MIT licensed, free to use, modify and distribute, documentation is CC BY 4.0, free to share with attribution.
Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
double-check against the repo, no cap.