Files
winning-wallet-finder_github/live/validate_timing.py
T
jaxperro 4b9488be9d live: select sharps by copyability, not lead time (surfaces new holders)
Replace the blunt 24h lead gate with a copy-replay selection run on EVERY
conviction wallet: keep only those that are copy-positive AND have a
genuine hold-to-resolution edge (held_pnl>0, held win-rate>=55% over >=8
resolved held bets), active in 30d, with a light >=1h lead floor vs true
snipers. display_stats now splits copy P&L into scalp vs held legs and
uses fresh-positions resolution (clob fallback) so it's cheap enough to
run on all ~229 wallets.

Effect: drops scalper-traps whose win% looked great but lose copied
(ArbTrader, iohihoo, S888, ttj01) and the old lead gate's discards;
surfaces fast-resolving copy-positive holders it used to throw away
(raid3r, 0x6d1A94f4, 0xec1d07e5, mantaray, earthisgood, shisan...).
14 copy-positive holders now in watch_sharps.json.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-23 13:31:41 -06:00

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#!/usr/bin/env python3
"""Select the COPYABLE conviction wallets — by what a copier actually earns.
The earlier version gated on entry->resolution lead time (a proxy for "can we
mirror it"). That was too blunt: it kept scalpers whose position win% looks great
but lose when copied, and dropped fast-resolving holders that are perfect for a
small fast-recycling bankroll. The fix: run a full flat-$50 copy replay on every
conviction wallet and SELECT on copyability directly —
* copy_pnl > 0 — copying them actually makes money, AND
* held_pnl > 0 over >= MIN_HELD — their hold-to-resolution edge is real (the
latency-robust leg), not just scalp-sell timing
* active in 30d, median lead >= MIN_LEAD_H (light guard vs true sub-hour snipers)
This keeps Kruto (sells often but profitably) and surfaces copy-positive holders
the lead gate used to discard; it drops scalper-traps like a wallet that's only
positive via sells while its held bets lose.
"""
import json
import os
import ssl
import statistics as st
import time
import urllib.request
from concurrent.futures import ThreadPoolExecutor
import cache
import smart_money as sm
HERE = os.path.dirname(__file__)
COPYABLE_MED_LEAD = 24.0 # median lead (h) on winning conviction bets to count as copyable
JUN1 = time.mktime(time.strptime("2026-06-01", "%Y-%m-%d")) # portfolio copy-start
STAKE = 50.0 # flat $/trade the copy portfolio uses
_SSL = ssl._create_unverified_context()
_CLOB = {} # conditionId -> {token_id: winner-price 1/0/None}
def _clob_winner(cond, token):
"""Authoritative resolution for a token: 1 if it won, 0 if it lost, None if the
market hasn't resolved. Matched by token_id (exact, no outcome-name guessing)."""
if cond not in _CLOB:
try:
req = urllib.request.Request("https://clob.polymarket.com/markets/" + cond,
headers={"User-Agent": "Mozilla/5.0"})
m = json.loads(urllib.request.urlopen(req, timeout=20, context=_SSL).read())
_CLOB[cond] = {str(t.get("token_id")):
(1 if t.get("winner") is True else 0 if t.get("winner") is False else None)
for t in (m.get("tokens") or [])}
except Exception:
_CLOB[cond] = {}
return _CLOB[cond].get(str(token))
def _bet_pnl(b):
"""Resolved (outcome) P&L of one cache bet: a $size stake at avg price p pays
size/p if won, else $0 — so P&L = size·(1p)/p if won else size."""
p = max(0.001, min(0.999, b["p"] or 0))
return b["size"] * ((1 - p) / p if b["won"] else -1)
def display_stats(w):
"""Everything the dashboard's sharp table renders, precomputed so the page makes
ZERO per-wallet data-api calls.
conv win%/record/P&L : over the wallet's conviction (top-20%-stake) bets — a
POSITION stat from the cache (large 180d sample)
realized P&L : reconstructed P&L over the last 500 resolved bets
copy P&L : the TRUTH for a copier — what a flat-$50 copy of their
conviction bets ACTUALLY realizes since Jun 1: replays
their entries, mirrors their exits, settles held bets at
AUTHORITATIVE clob resolution (by token id). This exposes
scalpers whose position win% looks great but don't copy
(e.g. ArbTrader: ~100% conv win but $790 copy P&L).
name / last-bet : from the /activity pull
"""
# ---- position win%/record/P&L from the cache (large, survivorship-corrected) ----
bets = [b for b in cache.get_bets(w) if (b["size"] or 0) > 0]
thr = cache.conv_cutoff(b["size"] for b in bets)
conv = [b for b in bets if b["size"] >= thr]
won = sum(1 for b in conv if b["won"])
recent = sorted(bets, key=lambda b: b["res_t"] or 0, reverse=True)[:500]
cut30 = time.time() - 30 * 86400
conv30 = [b for b in conv if (b["res_t"] or 0) >= cut30]
won30 = sum(1 for b in conv30 if b["won"])
out = {
"conv_win": round(100 * won / len(conv), 1) if conv else None,
"conv_won": won, "conv_lost": len(conv) - won,
"conv_pnl": round(sum(_bet_pnl(b) for b in conv)),
"conv30_win": round(100 * won30 / len(conv30), 1) if conv30 else None,
"conv30_won": won30, "conv30_lost": len(conv30) - won30,
"conv30_pnl": round(sum(_bet_pnl(b) for b in conv30)),
"realized_pnl": round(sum(_bet_pnl(b) for b in recent)),
"avg_bet": round(sum(b["size"] for b in conv) / len(conv)) if conv else 0,
"copy_pnl": 0, "held_pnl": 0, "held_won": 0, "held_lost": 0, "sold": 0,
"name": None, "last_trade": 0, "last_conv_bet": 0,
}
# ---- resolution map from a FRESH positions pull (curPrice extreme = resolved);
# cheap, so the copy replay can run on every conviction wallet. clob fills gaps.
resmap = {}
for p in (sm.get_json("/closed-positions", {"user": w, "limit": 500,
"sortBy": "TIMESTAMP", "sortDirection": "DESC"}) or []) + \
(sm.get_json("/positions", {"user": w, "limit": 500, "sizeThreshold": 0}) or []):
cp = p.get("curPrice", 0) or 0
if (cp <= 0.001 or cp >= 0.999) and p.get("asset") and p["asset"] not in resmap:
resmap[p["asset"]] = 1 if cp >= 0.5 else 0
# ---- activity: name, last-bet, and the flat-$50 copy replay ----
a = []
for off in range(0, 4000, 500):
pg = sm.get_json("/activity", {"user": w, "type": "TRADE", "limit": 500, "offset": off}) or []
a += pg
if len(pg) < 500 or (pg and (pg[-1].get("timestamp", 0) < JUN1)):
break
if a:
out["last_trade"] = a[0].get("timestamp", 0)
out["name"] = next((t.get("name") for t in a if t.get("name")), None)
# position-level conviction: each market's TOTAL buy stake, top-20% (p80)
mkt = {}
for t in a:
if t.get("side") == "BUY" and t.get("conditionId"):
mkt[t["conditionId"]] = mkt.get(t["conditionId"], 0) + (t.get("usdcSize", 0) or 0)
cthr = cache.conv_cutoff(mkt.values())
for t in a:
if t.get("side") == "BUY" and mkt.get(t.get("conditionId"), 0) >= cthr:
out["last_conv_bet"] = t.get("timestamp", 0)
break
# replay a flat-$50 copy of their conviction markets since Jun 1. Split P&L into
# the SOLD (scalp) leg and the HELD-to-resolution leg — the held leg is the
# latency-robust edge; a wallet whose copy P&L is positive only via scalp sells
# (held leg negative) isn't a reliable copy target.
ev = sorted([t for t in a if t.get("timestamp", 0) >= JUN1], key=lambda t: t.get("timestamp", 0))
openp, entered, scalp, held = {}, set(), 0.0, 0.0
hw = hl = sold = 0
for t in ev:
c, pr, asset = t.get("conditionId"), t.get("price", 0) or 0, t.get("asset")
if not c or pr <= 0:
continue
if t.get("side") == "BUY":
if mkt.get(c, 0) < cthr or c in entered or c in openp:
continue
entered.add(c); openp[c] = {"sh": STAKE / pr, "a": asset}
elif c in openp: # mirror their exit (scalp)
scalp += openp[c]["sh"] * pr - STAKE; sold += 1; del openp[c]
for c, p in openp.items(): # settle held bets at resolution
wv = resmap.get(p["a"])
if wv is None:
wv = _clob_winner(c, p["a"]) # clob fallback for out-of-pull markets
if wv is None:
continue # not resolved yet -> exclude
held += (p["sh"] if wv else 0) - STAKE
hw += wv; hl += 1 - wv
out.update(copy_pnl=round(scalp + held), held_pnl=round(held),
held_won=hw, held_lost=hl, sold=sold)
return out
def lead_profile(w):
ent = cache.get_entries(w)
bets = cache.get_bets(w)
cut = cache.conv_cutoff(b["size"] for b in bets) # this wallet's top-20% stake cutoff
leads = [(b["res_t"] - ent[b["cond"]]) / 3600.0 for b in bets
if b["won"] and (b["size"] or 0) >= cut and b["cond"] in ent
and b["res_t"] and b["res_t"] >= ent[b["cond"]]]
if not leads:
return None
med = st.median(leads)
u6 = sum(1 for l in leads if l < 6) / len(leads)
verdict = ("last-minute" if (med < 6 or sum(1 for l in leads if l < 1) / len(leads) > 0.5)
else "borderline" if med < COPYABLE_MED_LEAD else "sharp")
return dict(n=len(leads), med=med, u6=u6, verdict=verdict)
MIN_HELD = 8 # need this many resolved held conviction bets to trust the held edge
MIN_HELD_WR = 0.55 # held bets must WIN a clear majority — excludes longshot-variance
# players (+EV but ~34% win) that don't fit the high-win-rate thesis
MIN_LEAD_H = 1.0 # light sniper guard: drop wallets whose median winning lead < 1h
def main():
conv = json.load(open(os.path.join(HERE, "conviction_wallets.json")))
print(f"copy-testing {len(conv)} conviction wallets…\n", flush=True)
# run the full copy replay on EVERY conviction wallet (cheap now: fresh-positions
# resolution, clob only fills gaps), then select on copyability — not lead time.
with ThreadPoolExecutor(max_workers=8) as ex:
stats = list(ex.map(lambda c: display_stats(c["wallet"]), conv))
cut30 = time.time() - 30 * 86400
sharps = []
for c, ds in zip(conv, stats):
c.update(ds)
if ds.get("name"):
c["name"] = ds["name"]
lp = lead_profile(c["wallet"])
c["med_lead_h"] = round(lp["med"], 1) if lp else None
held_n = ds["held_won"] + ds["held_lost"]
held_wr = ds["held_won"] / held_n if held_n else 0
# SELECT a copyable sharp: active, copy-positive, and a genuine hold-to-
# resolution edge — held leg positive AND winning a clear majority on a real
# sample, so the edge survives live latency and isn't longshot variance or
# all sell-timing. A light lead floor drops true sub-hour snipers.
if ((ds["last_trade"] or 0) >= cut30 and ds["copy_pnl"] > 0
and ds["held_pnl"] > 0 and held_n >= MIN_HELD and held_wr >= MIN_HELD_WR
and (c["med_lead_h"] is None or c["med_lead_h"] >= MIN_LEAD_H)):
sharps.append(c)
sharps.sort(key=lambda c: c["copy_pnl"], reverse=True)
print(f"copy-positive holders (copy>0, held>0, held_n>={MIN_HELD}, active, lead>={MIN_LEAD_H}h): "
f"{len(sharps)} of {len(conv)}\n")
h = f"{'copyP&L':>8}{'heldP&L':>8}{'held':>9}{'sold%':>6}{'medLeadH':>9} wallet"
print(h); print("-" * len(h))
for c in sharps[:35]:
n = c["held_won"] + c["held_lost"]
sp = 100 * c["sold"] / (c["sold"] + n) if (c["sold"] + n) else 0
ld = f"{c['med_lead_h']:.0f}" if c["med_lead_h"] is not None else "—"
print(f"{c['copy_pnl']:>+8}{c['held_pnl']:>+8}{(str(c['held_won'])+'-'+str(c['held_lost'])):>9}"
f"{sp:>5.0f}%{ld:>9} {(c.get('name') or c['wallet'][:10])}")
json.dump(sharps, open(os.path.join(HERE, "watch_sharps.json"), "w"), indent=2)
print(f"\n-> watch_sharps.json ({len(sharps)} copy-positive holders)")
if __name__ == "__main__":
main()