Files
winning-wallet-finder_github/README.md
T
jaxperro 3d0bc7f001 Add live/ skilled-wallet scanner + cache; document clean OOS finding
live/: operationalizes the LBS/Yale "skilled ~3%" result against the live
data-api. Enumerate recent liquid markets -> top traders -> candidate pool;
cache every wallet's resolved bets once in DuckDB (~26k wallets / 12.5M bets,
keyed by per-bet resolution time so any cutoff re-scores in seconds); 5-gate
skill funnel (n>=15, z>0, BH-FDR, split-half OOS, MM/bot cap); dashboard +
daily refresh.

Key finding: copying the high-win-rate "favorite-rider" cohort looks +23.6%
in-sample but loses -7.4% once selected on pre-June-1 data only (99% -> 68%
win rate) — selection bias, reproducing the paper's "lucky winners revert"
result on live data. Win rate != edge, again.

wide/: bulk subgraph->DuckDB scanner (survivorship-bias-free over all wallets),
but the public subgraph is frozen at Jan 2026 -> historical tool only.

Large local data (*.duckdb, candidates.json, *_scored.json, history/) gitignored.
README + FINDINGS updated with the current logic and the clean result.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-18 11:16:20 -06:00

11 KiB
Raw Blame History

🏆 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.md for 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 (~25s), 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.

  1. Discord webhook → set DISCORD_WEBHOOK env (or config.json).
  2. Deploy the receiver to an always-on host (Railway / Fly / a $5 VPS — not Render free, it sleeps). Procfile, requirements.txt, nixpacks.toml included; binds to $PORT, exposes /alchemy (POST) and /health (GET).
  3. Alchemy → create an Address Activity webhook (Polygon mainnet), add the watch.json addresses, point it at https://your-host/alchemy, set the signing key as ALCHEMY_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 replays every watched-wallet trade since inception, enters when they enter (if there's cash), holds each bet to resolution, then settles (win → payout, loss → $0) and frees the cash. Shows Liquid (cash), Invested (open bets marked to market), Realized (settled P&L), a Current Bets table with per-bet entry / mark / P&L / settle date, and — crucially — Missed P&L: the profit left on the table from trades skipped because the bankroll was fully deployed (the real cost of a small account). It runs 100% client-side off Polymarket's public API (CORS-open) — zero backend, zero added cost.

What the tracker taught us: $1,000 across many hyperactive wallets gets fully deployed almost instantly — you can follow only a few percent of their trades. Concentrating on a handful of high-conviction wallets with bigger stakes is the only way a small bankroll meaningfully mirrors them.


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 betsz > 0 (beats its entry prices) → BenjaminiHochberg FDR @5%split-half out-of-sample persistsnot 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.


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.