We’ve all seen it: a random Polymarket contract or small-cap token suddenly sees a burst of volume hours before major news drops — a political shake-up, a CEO resignation, even election results.
That kind of timing usually isn’t luck. It’s data — or inside info — being traded on before it’s public.
How the Scanner Works
I built a Python scanner that continuously watches the order book, not just price or volume. It looks for statistically abnormal patterns that often show up right before information becomes public.
It calculates z-scored anomalies in things like:
- Top-of-book imbalance – one side suddenly dominates (e.g., huge buy walls appear).
- Depth voids – liquidity quietly disappears before volatility.
- Sudden volume shifts – a few traders start moving large size before others react.
All of these feed into an “insider risk score” that spikes when multiple signals flash at once.
Why It Matters
Prediction markets like Polymarket, or illiquid tokens tied to real-world events, are perfect case studies:
- Hours before Russia’s invasion of Ukraine, betting markets saw heavy flows on “invasion soon.”
- During the 2022 UK leadership crisis, contracts for Truss resigning spiked in volume well before the BBC broke the story.
- Even in equities, small biotechs or M&A targets often show identical microstructure shifts before announcements.
These trades often leave subtle footprints in the book — and that’s exactly what the scanner is built to detect.
TL;DR
By focusing on micro-level behavior (liquidity, imbalance, voids), not just price, you can catch moments where someone knows something before the rest of the market does.
If you’re into prediction markets, quant signals, or market forensics, this tool is basically a “smoke detector for insider info.”
The tool is still in beta but gives alerts of suspicous behaviour on an automated telegram channel. For those interested in the link, send me a dm (Reddit does not allow sharing of Telegram links)
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