Fix survivorship-biased win rate; add backtest, per-position cap, Discord alerts

The scanner measured win rate over /closed-positions only, but Polymarket
only redeems winning shares — losers sit unredeemed in /positions at
curPrice 0 and never enter closed-positions. That made win rates wildly
inflated (e.g. 90.6% vs a true 48.3%). Win rate now unions both endpoints
over a 90-day window. With the honest metric, ~no top wallet exceeds ~60%;
true rates cluster near 50%.

Also:
- backtest.py: replay a watchlist over a recent window, fill at historical
  price, mark outcomes from resolution. A 7d run of 4 top wallets returned
  -48%, confirming flat-size entry-copying is -EV at ~50% hit rates.
- copytrade.py: add max_position_usd cap (proportional adds could otherwise
  balloon one position to the whole exposure limit) and Discord webhook
  alerts on every would-be trade.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

.claude/launch.json

@@ -0,0 +1,11 @@
+{
+  "version": "0.0.1",
+  "configurations": [
+    {
+      "name": "dashboard",
+      "runtimeExecutable": "python3",
+      "runtimeArgs": ["smart_money.py", "--port", "8899"],
+      "port": 8899
+    }
+  ]
+}

.gitignore

@@ -5,4 +5,5 @@ __pycache__/
 # never commit live credentials or runtime state
 config.json
 copytrade_state.json
+*.log
 *.tmp

README.md

@@ -28,14 +28,24 @@ python3 smart_money.py --scan --pool 300 # broader sweep
 1. **Candidates** — pulls the 7d, 30d, and all-time leaderboards from
    `data-api.polymarket.com/v1/leaderboard` and dedupes into a candidate pool
    (default 150 wallets).
-2. **Win rate** — for each wallet, pages through `/closed-positions` (up to
-   300 most recent resolved positions). A *win* is a resolved position with
-   `realizedPnl > 0`.
+2. **True win rate** — over resolved bets in the last 90 days. This is the
+   subtle part: Polymarket only redeems *winning* shares, so `/closed-positions`
+   (redeemed or sold) is heavily **survivorship-biased toward winners** —
+   losing shares are worth $0 and sit unredeemed in `/positions` at
+   `curPrice 0` forever. A correct win rate has to **union both** endpoints
+   over the same window. Counting only `/closed-positions` (the naive approach)
+   reports ~90% for wallets whose real hit rate is ~50%.
 3. **Frequency** — counts trades from `/activity` over the last 4 weeks;
    *bets/week* is the number of **distinct markets** traded per week, so 50
    fills on one order don't count as 50 bets.
 4. **Filter** — keeps wallets with win rate ≥ 75%, ≥ 2 bets/week, and ≥ 10
-   resolved bets (so a 3-for-3 fluke doesn't rank as a 100% winner).
+   resolved bets.
+
+> **Reality check:** with the unbiased metric, essentially **no** top wallet
+> wins 75% of its bets — true rates cluster around **49% (a coin flip)**, max
+> ~60%. The profitable ones make money through position sizing and entry
+> prices, *not* hit rate. Treat a high win rate as a red flag for a bias bug,
+> not a green light. See the backtest below.
 
 ## Copy-trading (`copytrade.py`)
 
@@ -51,6 +61,27 @@ mirrors their trades onto your own account.
 - **No backfill** — only copies positions they open *after* you start
   watching; positions they already held are tracked (so exits still mirror)
   but never opened.
+- **Per-position cap** — `max_position_usd` caps total cost in any one market.
+  Without it, proportional adds let a single position balloon toward your whole
+  exposure limit as the whale piles in (a backtest caught exactly this).
+- **Discord alerts** — set `discord_webhook` in the config to get a ping on
+  every trade it would place (entries green, exits red).
+
+## Backtesting (`backtest.py`)
+
+Replays a watchlist's real trades over a recent window through the same copy
+logic, filling at each wallet's actual historical price and marking outcomes
+from how markets resolved.
+
+```bash
+python3 backtest.py --days 7
+```
+
+A 7-day backtest of four top wallets returned **−48% on deployed capital** —
+not because the engine is broken, but because the wallets' true entry hit rate
+is ~50% and flat-size copying pays the spread on every coin flip. Copying a
+profitable wallet's *entries* does not reproduce its edge, which lives in
+sizing and entry prices. Backtest before you fund anything.
 
 ### ⚠️ Real money — read this
 
@@ -86,7 +117,12 @@ and runtime state never get committed.
   A high-win-rate wallet that has never cracked any leaderboard window won't
   appear — scanning every wallet on the platform isn't feasible via the
   public API.
-- Win rate is measured over each wallet's most recent ~300 resolved
-  positions, not their entire history.
-- High win rate ≠ high EV: someone selling early for +$1 on every position
-  counts as winning. Check the realized PnL column alongside the win rate.
+- Win rate is measured over resolved bets in the last 90 days, not all history.
+- **Win rate ≠ EV.** Wallets with positive all-time leaderboard PnL routinely
+  show ~50% true win rates and even negative 90-day realized PnL. Following a
+  wallet profitably is about *how* it sizes and prices entries, not how often
+  it's right. The `realized_pnl` column is position-level over 90 days and is
+  **not** comparable to the all-time leaderboard figure.
+- Very high-volume / market-maker wallets (thousands of fills) can't be cleanly
+  backtested via the public API — too many fills, no historical position
+  snapshot.

backtest.py

@@ -0,0 +1,257 @@
+#!/usr/bin/env python3
+"""Backtest the copy-trade strategy over a recent window.
+
+Replays each watched wallet's real trades through the same copy logic the live
+bot uses — % -of-bankroll sizing, no-backfill, proportional adds/exits, risk
+caps — but fills at the wallet's actual historical trade price. Outcomes are
+marked from how each market resolved (curPrice 1/0 from closed-positions) or,
+for still-open positions, the current market price.
+
+    python3 backtest.py                 # last 7 days, config.json watchlist
+    python3 backtest.py --days 7
+
+This is an approximation. Notably the price guard is a near no-op in backtest
+(we fill at their price, with no 12s real-time lag), so results are slightly
+optimistic. Wallets whose history doesn't reach before the window are flagged.
+"""
+
+import argparse
+import json
+import time
+from collections import defaultdict
+
+import smart_money as sm
+from copytrade import clob_price, DEFAULT_CONFIG, load_json
+
+LOOKBACK_DAYS = 21          # how far before the window we try to read, for seed
+MAX_TRADES = 4000           # pagination cap per wallet
+
+
+def fetch_trades(wallet, since_ts):
+    """Newest-first TRADE activity back to ~since_ts (capped)."""
+    out, off = [], 0
+    while off < MAX_TRADES:
+        page = sm.get_json("/activity",
+                           {"user": wallet, "type": "TRADE",
+                            "limit": 500, "offset": off})
+        if not page:
+            break
+        out += page
+        off += 500
+        if len(page) < 500 or page[-1].get("timestamp", 0) < since_ts:
+            break
+    return out
+
+
+def mark_map(wallets):
+    """asset(token) -> current/resolved price (curPrice).
+
+    Merges each wallet's open /positions (curPrice = live price, or 0/1 if it
+    resolved but isn't redeemed yet) and /closed-positions (resolved 1/0). This
+    is what lets us mark a position we still hold at its true value rather than
+    falling back to entry price.
+    """
+    res = {}
+    for w in wallets:
+        for endpoint in ("/positions", "/closed-positions"):
+            off = 0
+            while off < 1000:
+                params = {"user": w, "limit": 50, "offset": off}
+                if endpoint == "/closed-positions":
+                    params.update(sortBy="TIMESTAMP", sortDirection="DESC")
+                else:
+                    params["sizeThreshold"] = 0.0
+                page = sm.get_json(endpoint, params)
+                if not page:
+                    break
+                for p in page:
+                    if p.get("asset") is not None:
+                        # closed-positions wins ties (definitively resolved)
+                        if endpoint == "/closed-positions" or p["asset"] not in res:
+                            res[p["asset"]] = p.get("curPrice", 0)
+                off += 50
+                if len(page) < 50:
+                    break
+    return res
+
+
+def backtest(cfg, days):
+    wallets = cfg["watchlist"]
+    now = time.time()
+    window_start = now - days * 86400
+    lookback_start = window_start - LOOKBACK_DAYS * 86400
+    stake = cfg["bankroll_usd"] * cfg["bankroll_pct"]
+    risk = cfg["risk"]
+
+    print(f"Backtesting {len(wallets)} wallets over the last {days} days "
+          f"· ${stake:.0f}/entry · caps: ${risk['max_trade_usd']:.0f}/trade, "
+          f"${risk['daily_spend_cap_usd']:.0f}/day, "
+          f"${risk['max_total_exposure_usd']:.0f} exposure\n")
+
+    # gather every wallet's trades + per-wallet data reach
+    all_trades, reach = [], {}
+    for w in wallets:
+        ts = fetch_trades(w, lookback_start)
+        for t in ts:
+            t["_wallet"] = w
+        all_trades += ts
+        oldest = min((t["timestamp"] for t in ts), default=now)
+        reach[w] = (now - oldest) / 86400
+    all_trades.sort(key=lambda t: t["timestamp"])
+
+    res = mark_map(wallets)
+
+    # replay state
+    their_pos = defaultdict(float)         # (wallet, token) -> shares
+    seed_tokens = set()                    # (wallet, token) held before window
+    my = {}                                # token -> {shares, cost, title, outcome, wallet}
+    daily_spend = defaultdict(float)       # 'YYYY-MM-DD' -> usd
+    deployed = 0.0
+    realized = 0.0
+    n_open = n_add = n_exit = n_skip_guard = n_skip_cap = n_skip_backfill = 0
+    price_cache = {}
+
+    def cur_price(token, side):
+        key = (token, side)
+        if key not in price_cache:
+            price_cache[key] = clob_price(token, side)
+        return price_cache[key]
+
+    def exposure():
+        return sum(p["cost"] for p in my.values())
+
+    for t in all_trades:
+        w, token = t["_wallet"], t.get("asset")
+        side, size, price = t.get("side"), t.get("size", 0), t.get("price", 0)
+        key = (w, token)
+        prev = their_pos[key]
+
+        # pre-window trades only build their position (establish the seed)
+        if t["timestamp"] < window_start:
+            seed_tokens.add(key)
+            their_pos[key] = prev + size if side == "BUY" else max(0.0, prev - size)
+            continue
+
+        label = f"{t.get('outcome','?')} · {t.get('title','?')[:44]}"
+        if side == "BUY":
+            mine = my.get(token)
+            if mine is None and key in seed_tokens:
+                n_skip_backfill += 1
+            elif mine is None:
+                # fresh OPEN
+                if not (risk["min_price"] <= price <= risk["max_price"]):
+                    n_skip_guard += 1
+                else:
+                    day = time.strftime("%Y-%m-%d", time.gmtime(t["timestamp"]))
+                    cap = min(stake, risk["max_trade_usd"],
+                              risk.get("max_position_usd", float("inf")),
+                              risk["daily_spend_cap_usd"] - daily_spend[day],
+                              risk["max_total_exposure_usd"] - exposure())
+                    if cap < risk["min_order_usd"] or len(my) >= risk["max_open_positions"]:
+                        n_skip_cap += 1
+                    else:
+                        sh = cap / price
+                        my[token] = {"shares": sh, "cost": cap,
+                                     "title": t.get("title", "?"),
+                                     "outcome": t.get("outcome", "?"), "wallet": w}
+                        deployed += cap
+                        daily_spend[day] += cap
+                        n_open += 1
+            else:
+                # proportional ADD
+                frac = size / prev if prev > 0 else 0
+                add_sh = mine["shares"] * frac
+                add_usd = add_sh * price
+                day = time.strftime("%Y-%m-%d", time.gmtime(t["timestamp"]))
+                cap = min(add_usd, risk["max_trade_usd"],
+                          risk.get("max_position_usd", float("inf")) - mine["cost"],
+                          risk["daily_spend_cap_usd"] - daily_spend[day],
+                          risk["max_total_exposure_usd"] - exposure())
+                if cap >= risk["min_order_usd"]:
+                    sh = cap / price
+                    mine["shares"] += sh
+                    mine["cost"] += cap
+                    deployed += cap
+                    daily_spend[day] += cap
+                    n_add += 1
+            their_pos[key] = prev + size
+        elif side == "SELL":
+            mine = my.get(token)
+            if mine and mine["shares"] > 0:
+                frac = 1.0 if prev <= 0 else min(1.0, size / prev)
+                sell_sh = min(mine["shares"], mine["shares"] * frac)
+                if sell_sh > 0:
+                    sold_frac = sell_sh / mine["shares"]
+                    cost_out = mine["cost"] * sold_frac
+                    proceeds = sell_sh * price
+                    realized += proceeds - cost_out
+                    mine["shares"] -= sell_sh
+                    mine["cost"] -= cost_out
+                    n_exit += 1
+                    if mine["shares"] <= 0.01:
+                        del my[token]
+            their_pos[key] = max(0.0, prev - size)
+
+    # mark remaining open positions to resolution or current price
+    unrealized = 0.0
+    open_rows = []
+    for token, p in my.items():
+        mark = res.get(token)
+        if mark is None:
+            mark = cur_price(token, "sell")
+        if mark is None:
+            mark = p["cost"] / p["shares"]   # last resort: flat
+        # curPrice at the extremes means the market has resolved
+        if mark <= 0.02:
+            status = "LOST"
+        elif mark >= 0.98:
+            status = "WON"
+        else:
+            status = "open"
+        val = p["shares"] * mark
+        pnl = val - p["cost"]
+        unrealized += pnl
+        open_rows.append((p, mark, pnl, status))
+
+    total_pnl = realized + unrealized
+    print(f"{'─'*74}")
+    print("  Per-wallet data reach (how far history extended before today):")
+    for w in wallets:
+        flag = "" if reach[w] >= days + 3 else "  ⚠ short history — low confidence"
+        print(f"    {w[:12]}…  {reach[w]:5.1f} days{flag}")
+    print(f"{'─'*74}")
+    print(f"  Copies it would have made:")
+    print(f"    {n_open} fresh entries · {n_add} adds · {n_exit} exits/trims")
+    print(f"    skipped: {n_skip_backfill} held-before-start, "
+          f"{n_skip_guard} price/range, {n_skip_cap} risk-cap")
+    print(f"{'─'*74}")
+    print(f"  Total deployed (bought):     ${deployed:>12,.2f}")
+    print(f"  Realized P&L (closed legs):  ${realized:>+12,.2f}")
+    print(f"  Unrealized P&L (still held): ${unrealized:>+12,.2f}")
+    print(f"  ── Net P&L:                  ${total_pnl:>+12,.2f}"
+          f"   ({(total_pnl/deployed*100) if deployed else 0:+.1f}% on deployed)")
+    print(f"{'─'*74}")
+    if open_rows:
+        won = sum(1 for _, _, _, s in open_rows if s == "WON")
+        lost = sum(1 for _, _, _, s in open_rows if s == "LOST")
+        opn = sum(1 for _, _, _, s in open_rows if s == "open")
+        print(f"  Positions still on the book at window end: {len(open_rows)} "
+              f"({won} won, {lost} lost, {opn} open & marked-to-market)")
+        for p, mark, pnl, status in sorted(open_rows, key=lambda x: x[2]):
+            print(f"    {status:>5}  {pnl:>+9,.2f}  {p['outcome']} · {p['title'][:40]}")
+    print()
+
+
+def main():
+    ap = argparse.ArgumentParser(description=__doc__,
+                                 formatter_class=argparse.RawDescriptionHelpFormatter)
+    ap.add_argument("--config", default="config.json")
+    ap.add_argument("--days", type=int, default=7)
+    args = ap.parse_args()
+    cfg = {**DEFAULT_CONFIG, **load_json(args.config, {})}
+    cfg["risk"] = {**DEFAULT_CONFIG["risk"], **cfg.get("risk", {})}
+    backtest(cfg, args.days)
+
+
+if __name__ == "__main__":
+    main()

config.example.json

@@ -1,12 +1,14 @@
 {
   "mode": "paper",
   "poll_seconds": 12,
+  "discord_webhook": "",
   "watchlist": [],
   "bankroll_usd": 1000.0,
   "bankroll_pct": 0.02,
   "price_guard_pct": 0.05,
   "risk": {
     "max_trade_usd": 50.0,
+    "max_position_usd": 40.0,
     "daily_spend_cap_usd": 250.0,
     "max_total_exposure_usd": 500.0,
     "max_open_positions": 20,

copytrade.py

@@ -47,12 +47,14 @@ CONFIRM_PHRASE = "TRADE LIVE"
 DEFAULT_CONFIG = {
     "mode": "paper",                 # "paper" or "live"
     "poll_seconds": 12,              # how often to check each wallet
+    "discord_webhook": "",           # paste a Discord webhook URL to get pings
     "watchlist": [],                 # ["0xwallet1", "0xwallet2", ...]
     "bankroll_usd": 1000.0,          # your stake pool
     "bankroll_pct": 0.02,            # 2% of bankroll per new entry
     "price_guard_pct": 0.05,         # skip if price moved >5% from their fill
     "risk": {
         "max_trade_usd": 50.0,       # hard ceiling on any single copy
+        "max_position_usd": 40.0,    # hard ceiling on total cost in one market
         "daily_spend_cap_usd": 250.0,
         "max_total_exposure_usd": 500.0,
         "max_open_positions": 20,
@@ -71,6 +73,22 @@ DEFAULT_CONFIG = {
 STATE_PATH_DEFAULT = "copytrade_state.json"
 
 
+def post_discord(webhook, content):
+    """POST a message to a Discord webhook. Best-effort; never raises."""
+    if not webhook:
+        return False
+    try:
+        body = json.dumps({"content": content}).encode()
+        req = urllib.request.Request(
+            webhook, data=body, method="POST",
+            headers={"Content-Type": "application/json",
+                     "User-Agent": "Mozilla/5.0"})
+        urllib.request.urlopen(req, timeout=10, context=SSL_CTX).read()
+        return True
+    except (urllib.error.URLError, TimeoutError):
+        return False
+
+
 # ── state ─────────────────────────────────────────────────────────────────
 
 def load_json(path, default):
@@ -201,11 +219,22 @@ class CopyTrader:
         self.state_path = state_path
         self.risk = cfg["risk"]
         self.seen = set(state["seen_tx"])
+        self.webhook = cfg.get("discord_webhook", "")
+        self._discord_warned = False
 
     # -- helpers --
     def log(self, msg):
         print(f"{time.strftime('%H:%M:%S')}  {msg}", flush=True)
 
+    def alert(self, msg, discord_text=None):
+        """Log to console AND push to Discord (used for actual placements)."""
+        self.log(msg)
+        if self.webhook:
+            ok = post_discord(self.webhook, discord_text or msg)
+            if not ok and not self._discord_warned:
+                self.log("  ⚠ Discord webhook post failed (check the URL)")
+                self._discord_warned = True
+
     def reset_daily_if_needed(self):
         today = time.strftime("%Y-%m-%d")
         if self.state["spend"]["date"] != today:
@@ -219,7 +248,7 @@ class CopyTrader:
         save_json(self.state_path, self.state)
 
     # -- risk gate: returns (allowed_usd, reason_if_blocked) --
-    def gate_buy(self, want_usd, price):
+    def gate_buy(self, want_usd, price, pos_cost=0.0):
         r = self.risk
         if not (r["min_price"] <= price <= r["max_price"]):
             return 0.0, f"price {price:.3f} outside [{r['min_price']},{r['max_price']}]"
@@ -229,6 +258,7 @@ class CopyTrader:
         caps = [
             want_usd,
             r["max_trade_usd"],
+            r.get("max_position_usd", float("inf")) - pos_cost,
             r["daily_spend_cap_usd"] - self.state["spend"]["usd"],
             r["max_total_exposure_usd"] - self.open_exposure(),
         ]
@@ -307,7 +337,8 @@ class CopyTrader:
             want_usd = self.cfg["bankroll_usd"] * self.cfg["bankroll_pct"]
             kind = "OPEN"
 
-        allowed, reason = self.gate_buy(want_usd, price)
+        pos_cost = mine["cost"] if is_add else 0.0
+        allowed, reason = self.gate_buy(want_usd, price, pos_cost)
         if reason:
             self.log(f"{kind} {label} — skip ({reason})")
             return
@@ -326,8 +357,12 @@ class CopyTrader:
                 "shares": res["filled_shares"], "cost": spent,
                 "title": title, "outcome": outcome}
         tag = "[PAPER]" if not self.ex.live else "[LIVE]"
-        self.log(f"{kind} {label} — {tag} buy {res['filled_shares']:.1f} "
-                 f"@ {res['price']:.3f}  (${spent:.2f})")
+        self.alert(
+            f"{kind} {label} — {tag} buy {res['filled_shares']:.1f} "
+            f"@ {res['price']:.3f}  (${spent:.2f})",
+            discord_text=(f"🟢 **{kind.strip()}** {tag}\n{label}\n"
+                          f"buy {res['filled_shares']:.0f} @ {res['price']:.3f} "
+                          f"= **${spent:.2f}**"))
 
     def _handle_their_sell(self, token, their_size, their_prev, label):
         mine = self.state["my_pos"].get(token)
@@ -351,8 +386,12 @@ class CopyTrader:
         mine["shares"] -= res["filled_shares"]
         tag = "[PAPER]" if not self.ex.live else "[LIVE]"
         verb = "EXIT" if frac >= 0.999 else "TRIM"
-        self.log(f"{verb} {label} — {tag} sell {res['filled_shares']:.1f} "
-                 f"@ {res['price']:.3f}  (${proceeds:.2f})")
+        self.alert(
+            f"{verb} {label} — {tag} sell {res['filled_shares']:.1f} "
+            f"@ {res['price']:.3f}  (${proceeds:.2f})",
+            discord_text=(f"🔴 **{verb}** {tag}\n{label}\n"
+                          f"sell {res['filled_shares']:.0f} @ {res['price']:.3f} "
+                          f"= **${proceeds:.2f}**"))
         if mine["shares"] <= 0.01:
             del self.state["my_pos"][token]
 
@@ -389,6 +428,14 @@ class CopyTrader:
                  f"bankroll ${self.cfg['bankroll_usd']:.0f} @ "
                  f"{self.cfg['bankroll_pct']:.1%}/entry · "
                  f"guard {self.cfg['price_guard_pct']:.0%}")
+        if self.webhook:
+            post_discord(self.webhook,
+                         f"✅ **Copy-trade tracker connected** ({mode})\n"
+                         f"watching {len(self.cfg['watchlist'])} wallets · "
+                         f"${self.cfg['bankroll_usd']:.0f} bankroll @ "
+                         f"{self.cfg['bankroll_pct']:.1%}/entry · "
+                         f"guard {self.cfg['price_guard_pct']:.0%}\n"
+                         f"You'll get a ping on every trade it would place.")
         if not self.cfg["watchlist"]:
             self.log("watchlist is empty — add wallets to the config. "
                      "(Run smart_money.py to find them.)")

smart_money.py

@@ -26,10 +26,10 @@ PORT = 8899
 # Scan defaults — adjustable in the UI
 DEFAULTS = {
     "pool": 150,           # candidate wallets pulled from the leaderboard
-    "min_win_rate": 75.0,  # percent of resolved bets with realizedPnl > 0
+    "min_win_rate": 75.0,  # percent of resolved bets that won (true, unbiased)
     "min_bets_week": 2.0,  # distinct markets traded per week, recent 4 weeks
     "min_resolved": 10,    # resolved bets required (filters 3-for-3 flukes)
-    "max_positions": 300,  # most recent resolved positions sampled per wallet
+    "max_positions": 80,   # page cap per endpoint (50 each) — window is the real limit
 }
 FREQ_WEEKS = 4  # window for the bets-per-week measurement
 
@@ -102,23 +102,72 @@ def leaderboard_candidates(pool):
     return ranked[:pool]
 
 
-def closed_positions(wallet, max_positions):
-    """Most recent resolved positions, newest first.
+WIN_WINDOW_DAYS = 90   # measure win rate over resolved bets in this window
 
-    The API defaults to sorting by realizedPnl descending — without an
-    explicit TIMESTAMP sort you get a wallet's biggest *wins* first, which
-    inflates every win rate toward 100%. Sort by time so we sample the
-    actual recent record.
+
+def _parse_end(end):
+    """Parse an endDate ('2026-06-11T00:00:00Z' or '2026-06-09') to epoch."""
+    if not end:
+        return 0
+    end = end.replace("Z", "")
+    for fmt in ("%Y-%m-%dT%H:%M:%S", "%Y-%m-%d"):
+        try:
+            return time.mktime(time.strptime(end, fmt))
+        except ValueError:
+            continue
+    return 0
+
+
+def resolved_positions(wallet, max_pages):
+    """Every resolved bet — won or lost — in the last WIN_WINDOW_DAYS.
+
+    Polymarket only redeems *winning* shares; losing shares are worth $0 and
+    sit unredeemed in the wallet forever. So /closed-positions (redeemed or
+    sold) is heavily survivorship-biased toward winners — the losers pile up
+    in /positions at curPrice 0. A true win rate has to union both, over the
+    same time window so the ratio isn't skewed by truncation.
     """
+    cutoff = time.time() - WIN_WINDOW_DAYS * 86400
+    now = time.time()
     out = []
+
+    # redeemed / sold winners (and losers sold before resolution), time-sorted
     offset = 0
-    while offset < max_positions:
+    while offset < max_pages * 50:
         page = get_json("/closed-positions",
                         {"user": wallet, "limit": 50, "offset": offset,
                          "sortBy": "TIMESTAMP", "sortDirection": "DESC"})
         if not page:
             break
-        out.extend(page)
+        for p in page:
+            if p.get("timestamp", 0) >= cutoff:
+                out.append({"won": p.get("curPrice", 0) >= 0.5,
+                            "pnl": p.get("realizedPnl", 0),
+                            "title": p.get("title", "?"),
+                            "outcome": p.get("outcome", "?"),
+                            "avgPrice": p.get("avgPrice", 0),
+                            "ts": p.get("timestamp", 0)})
+        offset += 50
+        if len(page) < 50 or page[-1].get("timestamp", 0) < cutoff:
+            break
+
+    # currently-held positions whose market already resolved (the hidden losers)
+    offset = 0
+    while offset < max_pages * 50:
+        page = get_json("/positions",
+                        {"user": wallet, "limit": 50, "offset": offset,
+                         "sizeThreshold": 0.0})
+        if not page:
+            break
+        for p in page:
+            end = _parse_end(p.get("endDate"))
+            if cutoff <= end < now:   # resolved, in window, unredeemed
+                out.append({"won": p.get("curPrice", 0) >= 0.5,
+                            "pnl": p.get("cashPnl", 0),
+                            "title": p.get("title", "?"),
+                            "outcome": p.get("outcome", "?"),
+                            "avgPrice": p.get("avgPrice", 0),
+                            "ts": end})
         offset += 50
         if len(page) < 50:
             break
@@ -149,17 +198,13 @@ def recent_trade_frequency(wallet, weeks=FREQ_WEEKS):
 
 def analyze_wallet(candidate, max_positions):
     wallet = candidate["wallet"]
-    resolved = closed_positions(wallet, max_positions)
+    resolved = resolved_positions(wallet, max_positions)
     if not resolved:
         return None
-    # A bet won if the outcome it held resolved YES. For resolved positions
-    # curPrice is binary (1 = won, 0 = lost), so it's a cleaner signal than
-    # the sign of realizedPnl — a hedged position can win yet net $0 PnL.
-    def won(p):
-        return p.get("curPrice", 0) >= 0.5
-    wins = sum(1 for p in resolved if won(p))
-    realized_pnl = sum(p.get("realizedPnl", 0) for p in resolved)
+    wins = sum(1 for p in resolved if p["won"])
+    realized_pnl = sum(p["pnl"] for p in resolved)
     trades, markets = recent_trade_frequency(wallet)
+    recent = sorted(resolved, key=lambda p: p["ts"], reverse=True)[:15]
     return {
         **candidate,
         "resolved": len(resolved),
@@ -171,14 +216,14 @@ def analyze_wallet(candidate, max_positions):
         "bets_per_week": round(markets / FREQ_WEEKS, 1),
         "recent": [
             {
-                "title": p.get("title", "?"),
-                "outcome": p.get("outcome", "?"),
-                "avgPrice": p.get("avgPrice", 0),
-                "realizedPnl": round(p.get("realizedPnl", 0), 2),
-                "won": won(p),
-                "timestamp": p.get("timestamp", 0),
+                "title": p["title"],
+                "outcome": p["outcome"],
+                "avgPrice": p["avgPrice"],
+                "realizedPnl": round(p["pnl"], 2),
+                "won": p["won"],
+                "timestamp": p["ts"],
             }
-            for p in resolved[:15]
+            for p in recent
         ],
     }