Update the dev-facing docs so others can follow the current system: - live/README: copy-positive-holder selection (replaces lead-time gate), Copy P&L as the copyability metric, new Paper portfolio (portfolio.py) + Dashboard feeds (watch_sharps.json / portfolio.json) sections, the full 8-step daily flow, the cache rolling-180d/replace retention gotcha, and a Copy execution (copybot/sync_floors, separate WIP) note. - README: top portfolio is now precomputed off the cache (correct recycling), judge by Copy P&L not win%, copy execution is separate. - FINDINGS: capital-recycling / $1k-book section + repo-layout refresh. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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🏆 Winning Wallet Finder
Find Polymarket wallets with a real, statistically-verifiable edge, test whether copying them actually makes money, get pinged the moment they trade, and watch a live $1,000 paper portfolio follow them in real time.
This started as "copy the smart money." Along the way we tested — and ruled out — six systematic public-data strategies, and found that the only signal that holds up is statistical improbability: wallets that win far more than the prices they paid imply. This repo is the tooling for finding and watching those wallets, plus an honest record of everything that didn't work.
Read
FINDINGS.mdfor the full story. TL;DR: detection of edge wallets works; profitably copying them is unproven (it survived a naive backtest but collapsed to one-wallet variance out-of-sample). Treat this as a research + monitoring tool, not a money printer.
The core idea: z-score, not win rate
Every Polymarket bet has an entry price that is the market's estimate of its odds (a YES at 30¢ ⇒ market thinks 30%). If you have no edge, over many bets you win about the sum of your entry prices — call it expected wins.
z = (actual wins − expected wins) / standard deviation
- z = 0 → you won exactly what your prices implied → no edge.
- z = 3 → ~1-in-740 by luck. z = 5 → ~1-in-3.5M. z = 9 → astronomical.
p(luck)is z as a probability: the chance a no-edge bettor does this well by chance.
Why this beats win rate: a wallet that bets longshots and wins 14% when the odds implied 8% has a huge edge (high z) despite a low win rate. A wallet buying 90¢ favorites and winning 90% has z≈0 — no edge, just paying for favorites. z measures beating the prices you paid.
Two refinements separate signal from noise:
- Lifetime trade count — high z + tens of thousands of trades = a market-maker bot, not an insider. Real edge wallets have concentrated edge over a few thousand trades.
- Pre-resolution timing + fresh wallet — entering minutes/hours before resolution on a new account is the insider fingerprint (the Bubblemaps / 60 Minutes pattern).
How the pieces fit
data layer detection hunting validation live system
────────── ───────── ─────── ────────── ───────────
smart_money.py ─▶ insider.py ──▶ hunt.py / huntwide ▶ copyback / oos.py ▶ webhook_receiver.py ─▶ Discord ping
(Polymarket API, (z-score, timing, (sweep markets, (does copying them (Alchemy webhook)
true win rate) freshness, funding surface edge actually pay? in- & trading/ (paper) ────▶ live $1k
clustering) wallets) out-of-sample) jaxperro.com/trading portfolio
| File | Role |
|---|---|
insider.py |
The detector. z-score/p-value, pre-resolution timing, fresh-wallet & sizing flags, and Alchemy funding-cluster ring detection. --scan / --market / --wallet. |
smart_money.py |
Data foundation + dashboard. Survivorship-corrected true win rate. |
hunt.py |
Ring-hunt sweep over a fixed list of news-driven event markets. |
huntwide.py |
Wide sweep — source wallets from ~100 markets, score each, tier by z. |
copyback.py |
Backtest: copy edge wallets' entries from a date, weighted, compounding. |
oos.py |
Out-of-sample test — select wallets on pre-period data, copy forward. The honesty gate. |
webhook_receiver.py |
Push-based live watcher: Alchemy on-chain webhook → enrich → Discord. |
watch.json |
The tracked wallet set + edge weights (shared by the watcher and the tracker). |
| paper tracker | Client-side $1,000 running portfolio → jaxperro.com/trading (page lives in the personal site repo). |
live/ |
The current scanner — find & track the skilled ~3% from the live API at scale: enumerate → cache → 5-gate skill funnel → dashboard → daily refresh. Caches ~26k wallets / 12.5M bets locally so every re-score is seconds. (live/README) |
wide/ |
Bulk subgraph→DuckDB scanner: survivorship-bias-free over all 1.76M wallets, but the public subgraph is frozen at Jan 2026, so it's a historical tool only. (wide/README) |
archive/ |
The six strategies that didn't work, kept for reference (details). |
Quickstart
Zero dependencies — Python 3 stdlib only (no pip install). macOS python.org
builds lack CA certs, so the code falls back to unverified SSL for these public
read-only APIs.
git clone https://github.com/jaxperro/winning-wallet-finder
cd winning-wallet-finder
cp config.example.json config.json # then edit (see Config below)
python3 insider.py --scan 40 # score the top-40 leaderboard wallets
python3 insider.py --market <slug> # score a market's traders + detect rings
python3 insider.py --wallet 0xABC… # deep-profile one wallet
python3 huntwide.py # wide sweep → huntwide.csv (tiered by z)
python3 oos.py # the out-of-sample copy test
python3 smart_money.py # dashboard at http://localhost:8899
Config (config.json, gitignored — holds your secrets)
{
"discord_webhook": "https://discord.com/api/webhooks/…", // alerts
"alchemy_key": "…", // Polygon RPC for funding-cluster detection
"alchemy_signing_key": "…", // verifies inbound webhook POSTs (live watcher)
"watch": [ {"wallet": "0x…", "name": "Famecesgoal"}, … ] // wallets to track
}
Data sources
| Source | Used for |
|---|---|
data-api.polymarket.com |
positions, trades, leaderboard, activity, true win rate |
gamma-api.polymarket.com |
market metadata, resolution times, best bid/ask |
clob.polymarket.com |
order books, prices, liquidity-reward configs |
api.elections.kalshi.com |
Kalshi prices (cross-venue arb research) |
| Alchemy (Polygon) | on-chain USDC funding traces + the live trade webhook |
The live system
Two always-on pieces, both running on near-zero infrastructure cost. The wallets
they track live in watch.json (currently the 4 sharpest, followable
wallets — high z, not bots, not in-game — re-weighted by z).
1. Discord watcher — pinged on every trade (webhook_receiver.py)
Push-based, no polling. The instant a tracked wallet's proxy transacts on
Polygon (~2–5s), Alchemy POSTs the receiver, which enriches the trade via the
data-API and pings Discord: 🟢 Famecesgoal BUY Yes @ 0.34 ($120) — <market>.
It's a tiny stdlib HTTP server that idles at ~zero CPU between trades.
- Discord webhook → set
DISCORD_WEBHOOKenv (orconfig.json). - Deploy the receiver to an always-on host (Railway / Fly / a $5 VPS — not
Render free, it sleeps).
Procfile,requirements.txt,nixpacks.tomlincluded; binds to$PORT, exposes/alchemy(POST) and/health(GET). - Alchemy → create an Address Activity webhook (Polygon mainnet), add the
watch.jsonaddresses, point it athttps://your-host/alchemy, set the signing key asALCHEMY_SIGNING_KEY(turns on HMAC verification).
Keep the two wallet lists in sync: Alchemy's address list (what triggers) and
watch.json (what names the alert).
2. Live paper portfolio — trading/ → jaxperro.com/trading
A $1,000 paper account that behaves like real money: it mirrors each followed wallet's conviction bets (top 20% of their own stake sizes) at $50/trade, enters when they enter (if there's cash), holds to resolution, then settles and frees the cash. Shows Liquid, Invested, Realized, a Current Bets table, and Missed P&L (profit skipped when the bankroll was fully deployed — the cost of a small account).
It's now precomputed server-side off the cache (live/portfolio.py →
portfolio.json) rather than replayed in the browser: the cache stores each bet's
resolution time, so capital recycles at the true resolution moment (the
client replay used to phantom-lock capital when the data-api lacked resolution
dates). The page is a static renderer of portfolio.json + watch_sharps.json,
with the old client-side replay kept as a fallback.
What the tracker taught us: $1,000 across many hyperactive wallets saturates instantly — concentrate on a few wallets that fit the bankroll. And win% lies about copyability: judge candidates by Copy P&L (the sharps table's headline column — actual flat-$50 copy result, scalpers exposed), not win rate. Actually placing the trades is a separate in-progress system (
copybot.py); this repo is selection + paper tracking.
The skilled-wallet scanner (live/)
The newest pipeline operationalizes the LBS/Yale finding that ~3% of accounts are genuinely skilled. It scans the live data-api at scale and tracks the survivors forward.
The 5-gate funnel — a wallet is "skilled" only if it clears all five:
n ≥ 15 resolved bets → z > 0 (beats its entry prices) → Benjamini–Hochberg FDR @5% → split-half out-of-sample persists → not a market-maker/bot. Win
rate is never a gate.
The cache makes it cheap. Each wallet's full resolved-bet history is pulled
once into cache.duckdb (~26k wallets / 12.5M bets), keyed with per-bet
resolution times — so any cutoff (pre-June-1, full-window, archetypes) re-scores
in seconds instead of hours of API pulls.
The clean out-of-sample result (June 2026). Copying the "favorite-rider" skilled wallets, $1000, no execution lag:
| Selection | Win rate | Forward P&L (June 1+) |
|---|---|---|
| In-sample (peeks at test window) | 99% | +23.6% |
| Clean (pre-June-1 data only) | 68% | −7.4% (−19% on settled) |
The +23.6% was pure selection bias. Selected honestly, the favorites lose —
exactly the paper's "~60% of lucky winners become losers out-of-sample." High
win rate ≠ edge, again. (The value/longshot archetype — wallets that beat
underdog prices — is the one worth testing next.) Full pipeline in
live/README.md.
What does work (the repeatable find). Scoring wallets on their high-
conviction bets — the top 20% by stake size (per-wallet p80, not a flat $200) —
which win 70–80% on genuinely-uncertain (~0.4–0.6)
markets — trained pre-June and validated June: 62/83 stayed profitable forward
(p≈0). A lead-time gate (validate_timing.py) then drops wallets whose wins come
too close to resolution to mirror — "last-minute" entries (median lead <24h), which
may be genuine insiders or just fast-market specialists — plus anyone inactive >30d,
leaving ~31 validated copyable sharps (watch_sharps.json), surfaced live on
jaxperro.com/trading.
The catch — position win% ≠ copyability. A high conviction win% (a position
snapshot) doesn't mean you profit copying the wallet: a scalper buys ~$0.50 and sells
for ~+$1, which the snapshot scores as a "win" though he never held to resolution. So
the feed also precomputes Copy P&L — the authoritative flat-$50 copy result
(replay entries, mirror exits, settle held bets at clob resolution). It's the real
signal: ArbTraderRookie shows ~100% win but −$790 to copy; of the ~31, only a
few are copy-positive (Kruto2027 +$1,184, fortuneking +$430 — true holders). The
live tracker follows those two. Execution lag/fees and ongoing forward validation
still gate turning it into real money.
The honest verdict
- Detection works. z-score + timing + funding-cluster reliably surfaces statistically anomalous wallets (the 60-Minutes use case).
- Copying them is not proven. In-sample a weighted, compounding copy returned +545%; out-of-sample (select pre-May, copy forward) it was +168% — but driven entirely by one longshot lottery wallet, with the strongest signals contributing nothing. That's variance, not a durable, fundable edge.
- No turnkey public-data edge survived — copy-trading, win-rate ranking, LP
reward farming, binary/multi-outcome arb, and cross-venue arb all came back
efficient or illusory. See
FINDINGS.md.
Use this to find and watch edge wallets and gather forward data — not as a green light to bet size on copying them.