diff --git a/FINDINGS.md b/FINDINGS.md
index 0dc1f282..a7b6ab3c 100644
--- a/FINDINGS.md
+++ b/FINDINGS.md
@@ -142,6 +142,29 @@ misleading signal on the platform; favorite-riders are uncopyable.* The
 underdog/`value` archetype (beats longshot prices) is the only one left worth
 testing.
 
+## Train/test wallet selection, and the capital wall (June 2026)
+
+Built `live/strategy.py` (train on bets resolved before May 30, validate June 1+)
+and `live/followability.py` (entry-time + lead-time + cadence filter). Selecting
+on **copy-ROI + z + monthly consistency + diversification** (not win rate) gave
+150 wallets; **59/100 stayed profitable forward** (p=0.044), and filtering to
+*followable* markets lifted it to **49/77 (p=0.011), +23.4% pooled** out-of-
+sample. So a real, persistent, copyable edge **does** exist — unlike favorites.
+
+Then the reality check (`live/pnl_basket.py`, `live/pnl_focused.py`): a $1,000
+copier with **missed-trade accounting** (capital tied in open positions).
+- **Broad 10-wallet basket:** the wallets fire **1,210 markets** in June; $1,000
+  can follow only ~2–13% of them. At realistic stakes it **loses** (−$384 to
+  −$800); the gains sit in the trades you couldn't afford ($14k–$153k "missed").
+  **Capital, not edge, is the binding constraint.**
+- **Focused + conviction:** copy only 1–2 top wallets and only their larger-stake
+  (≥$200) bets → trade count drops to ~30–40, $1,000 affords them all, and it
+  **clears: +91% to +247% across stakes, stable, no blowup.**
+
+*Lesson: a small-bankroll copier cannot follow a skilled wallet's whole feed —
+the edge is only capturable by concentrating on few wallets' high-conviction
+bets. The live tracker (jaxperro.com/trading) now runs exactly that config.*
+
 ## Repo layout
 
 - `insider.py` — the detector: z-score/p-value, timing/freshness/sizing signals,
diff --git a/live/README.md b/live/README.md
index 1ae9350e..07d08f34 100644
--- a/live/README.md
+++ b/live/README.md
@@ -62,6 +62,18 @@ turn into losers out-of-sample. **Don't copy favorite-riders.** The `value`
 archetype (beats underdog prices) is where real alpha may live — test it with
 `backtest_june.py value`.
 
+## Strategy backtests
+
+- `strategy.py` — train (pre-May-30) / test (June1+) wallet selection on copy-ROI
+  + z + monthly consistency + diversification. → `selection.json`.
+- `followability.py` — pull entry timestamps (cached), drop wallets whose edge is
+  in un-followable fast/live markets, re-rank on followable forward bets. →
+  `watch_final.json` (the execution-realistic list).
+- `pnl_basket.py` / `pnl_focused.py` — $1,000 capital-constrained copy sims with
+  **missed-trade accounting**. Key result: the broad basket loses on $1k (can't
+  follow 1,200 trades), but **1–2 wallets + a conviction (bet-size) filter clears**
+  out-of-sample. See `../FINDINGS.md`.
+
 ## Daily (`daily.sh`)
 
 1. discover (enumerate last 14d) → 2. freshen cache (force-refresh watchlist +
diff --git a/live/cache.py b/live/cache.py
index b9d07c45..1008d6c1 100644
--- a/live/cache.py
+++ b/live/cache.py
@@ -33,6 +33,31 @@ _con.execute("""CREATE TABLE IF NOT EXISTS bets(
     wallet TEXT, cond TEXT, won BOOLEAN, p DOUBLE, res_t BIGINT, size DOUBLE)""")
 _con.execute("CREATE INDEX IF NOT EXISTS bets_w ON bets(wallet)")
 _con.execute("CREATE TABLE IF NOT EXISTS pulled(wallet TEXT PRIMARY KEY, pulled_at BIGINT)")
+_con.execute("CREATE TABLE IF NOT EXISTS entries(wallet TEXT, cond TEXT, first_buy BIGINT)")
+_con.execute("CREATE INDEX IF NOT EXISTS entries_w ON entries(wallet)")
+_con.execute("CREATE TABLE IF NOT EXISTS pulled_entries(wallet TEXT PRIMARY KEY, pulled_at BIGINT)")
+
+
+def get_entries(wallet):
+    """{conditionId: earliest BUY timestamp} for a wallet — cached. Lets us
+    compute entry->resolution lead time and trade cadence (followability)."""
+    now = time.time()
+    with _lock:
+        r = _con.execute("SELECT pulled_at FROM pulled_entries WHERE wallet=?", [wallet]).fetchone()
+        if r and now - r[0] < MAX_AGE_DAYS * 86400:
+            rows = _con.execute("SELECT cond,first_buy FROM entries WHERE wallet=?", [wallet]).fetchall()
+            return {c: t for c, t in rows}
+    try:
+        first_buy, _ = insider.entry_times(wallet)
+    except Exception:
+        first_buy = {}
+    with _lock:
+        _con.execute("DELETE FROM entries WHERE wallet=?", [wallet])
+        if first_buy:
+            _con.executemany("INSERT INTO entries(wallet,cond,first_buy) VALUES (?,?,?)",
+                             [(wallet, c, t) for c, t in first_buy.items()])
+        _con.execute("INSERT OR REPLACE INTO pulled_entries VALUES (?,?)", [wallet, int(now)])
+    return first_buy
 
 
 def get_bets(wallet):
diff --git a/live/followability.py b/live/followability.py
new file mode 100644
index 00000000..da8ea535
--- /dev/null
+++ b/live/followability.py
@@ -0,0 +1,126 @@
+#!/usr/bin/env python3
+"""Execution-realistic re-ranking of the selected wallets.
+
+Pulls entry timestamps (cached) for the strategy.py shortlist, then judges each
+wallet on whether we could actually FOLLOW it with $1,000:
+
+  * lead time = resolution - entry. Bets that resolve within MIN_LEAD_H of the
+    wallet's entry (live/in-game/instant markets) are NOT copyable — you can't
+    see and mirror the trade in time. We drop them.
+  * cadence = distinct markets entered per active day. Extreme cadence = a bot
+    we can't hand-follow.
+
+Then it recomputes forward (June1+, resolved) copy-ROI on ONLY the followable
+bets — the realistic number — and re-ranks. Output: watch_final.json.
+
+    python3 followability.py
+"""
+
+import json
+import os
+import statistics as st
+import time
+from concurrent.futures import ThreadPoolExecutor, as_completed
+
+import cache
+
+HERE = os.path.dirname(__file__)
+TEST_START = time.mktime(time.strptime(os.environ.get("TEST_START", "2026-06-01"), "%Y-%m-%d"))
+MIN_LEAD_H = 1.0          # a bet must resolve >= 1h after entry to be followable
+MED_LEAD_MIN = 2.0        # wallet's median lead must clear this to qualify
+MAX_CADENCE = 50.0        # entries/day above this = bot-like, hard to follow
+MIN_FOLL_FRAC = 0.5       # >= half the wallet's bets must be followable
+MIN_FWD_FOLL = 5          # need this many followable forward bets to rank
+
+
+def ret(p, won):
+    return (1 - p) / p if won else -1.0
+
+
+def assess(wallet):
+    ent = cache.get_entries(wallet)            # {cond: first_buy_ts}
+    bets = cache.get_bets(wallet)              # cached
+    leads = []
+    for b in bets:
+        e = ent.get(b["cond"])
+        if e and b.get("res_t"):
+            lh = (b["res_t"] - e) / 3600.0
+            if lh >= 0:
+                leads.append((b, lh))
+    if not leads:
+        return None
+    med_lead = st.median([lh for _, lh in leads])
+    foll_frac = sum(1 for _, lh in leads if lh >= MIN_LEAD_H) / len(leads)
+    ts = sorted(ent.values())
+    span = max(1.0, (ts[-1] - ts[0]) / 86400) if len(ts) > 1 else 1.0
+    cadence = len(ent) / span
+    # forward, followable only
+    fwd_foll = [b for b, lh in leads if b["res_t"] >= TEST_START and lh >= MIN_LEAD_H]
+    fwd_all = [b for b, lh in leads if b["res_t"] >= TEST_START]
+    foll_roi = (sum(ret(b["p"], b["won"]) for b in fwd_foll) / len(fwd_foll)
+                if fwd_foll else None)
+    raw_roi = (sum(ret(b["p"], b["won"]) for b in fwd_all) / len(fwd_all)
+               if fwd_all else None)
+    wins = sum(1 for b in fwd_foll if b["won"])
+    return dict(wallet=wallet, med_lead=med_lead, foll_frac=foll_frac, cadence=cadence,
+                fwd_foll_n=len(fwd_foll), foll_roi=foll_roi, raw_roi=raw_roi,
+                fwd_win=100 * wins / len(fwd_foll) if fwd_foll else 0)
+
+
+def main():
+    sel = json.load(open(os.path.join(HERE, "selection.json")))
+    wallets = [c["wallet"] for c in sel]
+    meta = {c["wallet"]: c for c in sel}
+    print(f"assessing followability of {len(wallets)} selected wallets "
+          f"(entry-time pull, cached)…\n", flush=True)
+
+    rows, done = [], 0
+    with ThreadPoolExecutor(max_workers=10) as ex:
+        for r in ex.map(assess, wallets):
+            done += 1
+            if r:
+                rows.append(r)
+            if done % 30 == 0:
+                print(f"  {done}/{len(wallets)}", flush=True)
+
+    # followability gates
+    foll = [r for r in rows if
+            r["med_lead"] >= MED_LEAD_MIN and
+            r["foll_frac"] >= MIN_FOLL_FRAC and
+            r["cadence"] <= MAX_CADENCE]
+    ranked = [r for r in foll if r["fwd_foll_n"] >= MIN_FWD_FOLL]
+    ranked.sort(key=lambda r: r["foll_roi"], reverse=True)
+
+    dropped = len(rows) - len(foll)
+    print(f"\n{len(rows)} assessed · {dropped} dropped as un-followable "
+          f"(fast/live markets or bot cadence) · {len(foll)} copyable\n")
+    if ranked:
+        pooled_num = sum(r["foll_roi"] * r["fwd_foll_n"] for r in ranked)
+        pooled_den = sum(r["fwd_foll_n"] for r in ranked)
+        pos = sum(1 for r in ranked if r["foll_roi"] > 0)
+        print(f"FOLLOWABLE forward verdict ({len(ranked)} wallets w/ >= {MIN_FWD_FOLL} "
+              f"followable June+ bets):")
+        print(f"  {pos}/{len(ranked)} profitable · pooled followable copy-ROI "
+              f"{pooled_num/pooled_den:+.1%} · median {st.median([r['foll_roi'] for r in ranked]):+.1%}\n")
+
+    h = (f"{'foll_roi':>9}{'raw_roi':>8}{'medLeadH':>9}{'foll%':>6}{'cad/d':>7}"
+         f"{'fwd_n':>6}{'tr_z':>6}  wallet")
+    print(h); print("-" * len(h))
+    for r in ranked[:40]:
+        m = meta[r["wallet"]]
+        raw = f"{r['raw_roi']:+.0%}" if r["raw_roi"] is not None else "—"
+        print(f"{r['foll_roi']:>+8.0%}{raw:>8}{r['med_lead']:>8.1f}h{r['foll_frac']*100:>5.0f}%"
+              f"{r['cadence']:>7.1f}{r['fwd_foll_n']:>6}{m['train_z']:>6.1f}  {r['wallet']}")
+
+    out = [{"wallet": r["wallet"], "name": r["wallet"][:10],
+            "foll_fwd_copy_roi": round(r["foll_roi"], 4),
+            "med_lead_h": round(r["med_lead"], 1), "cadence_per_day": round(r["cadence"], 1),
+            "followable_frac": round(r["foll_frac"], 2), "fwd_followable_n": r["fwd_foll_n"],
+            "train_z": meta[r["wallet"]]["train_z"],
+            "train_copy_roi": meta[r["wallet"]]["train_copy_roi"]} for r in ranked]
+    json.dump(out, open(os.path.join(HERE, "watch_final.json"), "w"), indent=2)
+    print(f"\n-> watch_final.json ({len(out)} execution-realistic wallets)")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/live/pnl_basket.py b/live/pnl_basket.py
new file mode 100644
index 00000000..988ff0ad
--- /dev/null
+++ b/live/pnl_basket.py
@@ -0,0 +1,101 @@
+#!/usr/bin/env python3
+"""Capital-constrained copy backtest of the 10-wallet basket, June 1 -> now.
+
+$1,000 bankroll. Replay the wallets' June-1+ entries in time order (using cached
+entry timestamps). At each entry: first settle any held bets that have resolved
+(free the cash + realize P&L), then enter IF we can afford the stake — otherwise
+it's a MISSED trade (counted, with its hypothetical outcome). Capital stays tied
+in still-open positions, which is what forces the misses. Realized P&L only.
+
+One position per market (earliest of the 10 wallets to enter it). Shown across a
+few flat stake sizes since that's the knob that trades off coverage vs misses.
+"""
+
+import time
+import cache
+
+JUN1 = time.mktime(time.strptime("2026-06-01", "%Y-%m-%d"))
+NOW = time.time()
+BANK = 1000.0
+WALLETS = [
+    "0xe8ca3f758c93f44f3ec210542ab78afb7c0bcccb", "0x0a7aaf83341b52df34e8ffef52aa295538d6df1b",
+    "0xfd4263b3ad08226034fe1b1ea678a46d80b58895", "0x13464aabec792c36b062316f474713e681330448",
+    "0x36bfcd8ab96dce2ddea30145ab749b59c6362864", "0x2d4bf8f846bf68f43b9157bf30810d334ac6ca7a",
+    "0x1cff72c8dddc30a64486fda6eab71ab5f9243984", "0xfc81760d44a21acc9fd4b749a5bf9a9b2eeae072",
+    "0x86c878cde72660ec52f5e6f0f0438b76de8fc867", "0x6fdddf25b92251ed1515703cda43bf8ff5f5d385",
+]
+
+
+def gather():
+    """One copy signal per market: (entry_ts, p, won, res_t|None). res_t None =
+    still open (ties up capital, no realized P&L)."""
+    pos = {}
+    for w in WALLETS:
+        ent = cache.get_entries(w)                    # {cond: first_buy_ts}
+        resolved = {b["cond"]: b for b in cache.get_bets(w)}
+        for cond, ets in ent.items():
+            if ets < JUN1:
+                continue
+            b = resolved.get(cond)
+            p = max(0.001, min(0.999, b["p"])) if b else None
+            rec = dict(ets=ets, p=p, won=b["won"] if b else None,
+                       res_t=(b["res_t"] if b else None))
+            if cond not in pos or ets < pos[cond]["ets"]:
+                pos[cond] = rec
+    return sorted(pos.values(), key=lambda r: r["ets"])
+
+
+def sim(events, stake):
+    cash, realized = BANK, 0.0
+    held = []                       # (res_t, p, won, stake)
+    entered = missed = openn = 0
+    missed_pnl = 0.0
+
+    def settle2(upto):
+        nonlocal cash, realized
+        keep = []
+        for res_t, p, won, s in held:
+            if res_t is not None and res_t <= upto:
+                payout = (s / p) if won else 0.0
+                cash += payout
+                realized += payout - s
+            else:
+                keep.append((res_t, p, won, s))
+        held[:] = keep
+
+    for e in events:
+        settle2(e["ets"])
+        if cash >= stake:
+            cash -= stake
+            held.append((e["res_t"], e["p"], e["won"], stake))
+            entered += 1
+            if e["res_t"] is None:
+                openn += 1
+        else:
+            missed += 1
+            if e["res_t"] is not None:               # hypothetical realized miss
+                missed_pnl += (stake / e["p"] - stake) if e["won"] else -stake
+    settle2(NOW)
+    open_left = sum(1 for h in held if h[0] is None or h[0] > NOW)
+    equity = BANK + realized                          # open held at cost
+    return dict(stake=stake, entered=entered, missed=missed, open_left=open_left,
+                realized=realized, equity=equity, missed_pnl=missed_pnl)
+
+
+def main():
+    ev = gather()
+    res = sum(1 for e in ev if e["res_t"] is not None)
+    print(f"10-wallet basket · {len(ev)} unique June1+ markets entered "
+          f"({res} resolved, {len(ev)-res} still open) · $1000 bankroll, miss when broke\n")
+    h = f"{'stake':>6}{'entered':>8}{'missed':>7}{'open':>5}{'realized P&L':>14}{'equity':>10}{'missed P&L':>12}"
+    print(h); print("-" * len(h))
+    for s in (20, 50, 100, 200):
+        r = sim(ev, s)
+        print(f"${r['stake']:>4}{r['entered']:>8}{r['missed']:>7}{r['open_left']:>5}"
+              f"{r['realized']:>+13,.0f}{r['equity']:>10,.0f}{r['missed_pnl']:>+12,.0f}")
+    print("\nrealized P&L = settled bets only · equity = $1000 + realized (open held at cost)")
+    print("missed P&L = hypothetical resolved P&L of trades skipped for lack of cash")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/live/pnl_focused.py b/live/pnl_focused.py
new file mode 100644
index 00000000..c3a26015
--- /dev/null
+++ b/live/pnl_focused.py
@@ -0,0 +1,66 @@
+#!/usr/bin/env python3
+"""Does a FOCUSED copy strategy clear where the broad 10-wallet basket didn't?
+
+Same $1000 capital-constrained engine + missed-trade accounting (pnl_basket.sim),
+but on narrower signal sets: fewer wallets, and/or only the wallet's higher-
+conviction (larger-stake) bets — so $1000 isn't spread across 1,210 markets.
+"""
+
+import time
+import cache
+import pnl_basket as pb
+
+JUN1 = time.mktime(time.strptime("2026-06-01", "%Y-%m-%d"))
+E8 = "0xe8ca3f758c93f44f3ec210542ab78afb7c0bcccb"
+A0 = "0x0a7aaf83341b52df34e8ffef52aa295538d6df1b"
+
+
+def gather(wallets, size_min=None):
+    """One signal per market. size_min filters to the wallet's larger-stake
+    (higher-conviction) bets; in that mode we only use resolved bets (open ones
+    have no known stake to filter on)."""
+    pos = {}
+    for w in wallets:
+        ent = cache.get_entries(w)
+        resolved = {b["cond"]: b for b in cache.get_bets(w)}
+        for cond, ets in ent.items():
+            if ets < JUN1:
+                continue
+            b = resolved.get(cond)
+            if b:
+                if size_min and (b["size"] or 0) < size_min:
+                    continue
+                rec = dict(ets=ets, p=max(0.001, min(0.999, b["p"])),
+                           won=b["won"], res_t=b["res_t"])
+            else:
+                if size_min:
+                    continue
+                rec = dict(ets=ets, p=None, won=None, res_t=None)
+            if cond not in pos or ets < pos[cond]["ets"]:
+                pos[cond] = rec
+    return sorted(pos.values(), key=lambda r: r["ets"])
+
+
+def run(label, wallets, size_min=None):
+    ev = gather(wallets, size_min)
+    res = sum(1 for e in ev if e["res_t"] is not None)
+    print(f"\n### {label} — {len(ev)} markets ({res} resolved)")
+    h = f"{'stake':>6}{'entered':>8}{'missed':>7}{'open':>5}{'realized':>11}{'equity':>9}"
+    print(h)
+    for s in (50, 100, 200):
+        r = pb.sim(ev, s)
+        print(f"${s:>4}{r['entered']:>8}{r['missed']:>7}{r['open_left']:>5}"
+              f"{r['realized']:>+10,.0f}{r['equity']:>9,.0f}")
+
+
+def main():
+    run("0xe8 only — all June+ entries", [E8])
+    run("0xe8 only — conviction (their bets >= $200)", [E8], size_min=200)
+    run("0xe8 only — conviction (their bets >= $1000)", [E8], size_min=1000)
+    run("0xe8 + 0x0a — all June+ entries", [E8, A0])
+    run("0xe8 + 0x0a — conviction (>= $200)", [E8, A0], size_min=200)
+    print("\nrealized = settled-bet P&L · equity = $1000 + realized (open at cost)")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/live/selection.json b/live/selection.json
new file mode 100644
index 00000000..1b6be6a4
--- /dev/null
+++ b/live/selection.json
@@ -0,0 +1,1502 @@
+[
+  {
+    "wallet": "0xa3d105059d622ac40f379461107e457944636f1a",
+    "train_copy_roi": 2.9232,
+    "train_z": 3.59,
+    "train_n": 65,
+    "fwd_copy_roi": null,
+    "fwd_n": 0,
+    "med_size": 20.0,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0xe8ca3f758c93f44f3ec210542ab78afb7c0bcccb",
+    "train_copy_roi": 2.8782,
+    "train_z": 18.86,
+    "train_n": 1289,
+    "fwd_copy_roi": 2.1914,
+    "fwd_n": 116,
+    "med_size": 12.2,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0xfd4263b3ad08226034fe1b1ea678a46d80b58895",
+    "train_copy_roi": 2.1616,
+    "train_z": 15.53,
+    "train_n": 667,
+    "fwd_copy_roi": 0.9877,
+    "fwd_n": 39,
+    "med_size": 77.1,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x1a6df901e63422055a1658b0ef2b2a871507cf4a",
+    "train_copy_roi": 2.1573,
+    "train_z": 11.16,
+    "train_n": 1183,
+    "fwd_copy_roi": -0.579,
+    "fwd_n": 172,
+    "med_size": 31.2,
+    "consistency": 0.67
+  },
+  {
+    "wallet": "0x55ac83b5a4837d868fd058c9793d53ab73c19955",
+    "train_copy_roi": 1.9708,
+    "train_z": 9.75,
+    "train_n": 177,
+    "fwd_copy_roi": null,
+    "fwd_n": 1,
+    "med_size": 13.6,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0xd84d970b0d4ec9bfc28d011306eba298b339cc32",
+    "train_copy_roi": 1.7671,
+    "train_z": 8.73,
+    "train_n": 1687,
+    "fwd_copy_roi": 1.1306,
+    "fwd_n": 131,
+    "med_size": 15.3,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x8548f0fae7636fc17ca6bb2cbae39cbd4fbce4c1",
+    "train_copy_roi": 1.2923,
+    "train_z": 4.34,
+    "train_n": 1776,
+    "fwd_copy_roi": -0.0054,
+    "fwd_n": 211,
+    "med_size": 53.4,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x83c821d1be2143f5699a07310101a52140c826f0",
+    "train_copy_roi": 1.2769,
+    "train_z": 13.85,
+    "train_n": 884,
+    "fwd_copy_roi": null,
+    "fwd_n": 1,
+    "med_size": 24.0,
+    "consistency": 0.75
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+    "wallet": "0xc5d521074e88279556836998fb2a5d2e2c1c6caa",
+    "train_copy_roi": 0.051,
+    "train_z": 5.39,
+    "train_n": 1740,
+    "fwd_copy_roi": -0.0602,
+    "fwd_n": 167,
+    "med_size": 155.7,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0xfe37315964b9a43b48b4ece3882a08f226619d5c",
+    "train_copy_roi": 0.0502,
+    "train_z": 3.01,
+    "train_n": 635,
+    "fwd_copy_roi": null,
+    "fwd_n": 0,
+    "med_size": 16.0,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x99292fe5c401a3a2b8df0e65e6e7df0b5ab6919e",
+    "train_copy_roi": 0.0484,
+    "train_z": 5.89,
+    "train_n": 1201,
+    "fwd_copy_roi": null,
+    "fwd_n": 0,
+    "med_size": 350.0,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0xbf3e350e8dcff777e78ec3dfa1282d0c6fc89a95",
+    "train_copy_roi": 0.0471,
+    "train_z": 4.09,
+    "train_n": 1978,
+    "fwd_copy_roi": null,
+    "fwd_n": 1,
+    "med_size": 8.8,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x97892305f3b5569c32d16f4ed70f840dd7e61ae7",
+    "train_copy_roi": 0.0463,
+    "train_z": 8.9,
+    "train_n": 1805,
+    "fwd_copy_roi": null,
+    "fwd_n": 1,
+    "med_size": 14.0,
+    "consistency": 0.6
+  },
+  {
+    "wallet": "0x9dbd5ca25b5c69a3ef8fb94de0edd083ff0ced07",
+    "train_copy_roi": 0.0453,
+    "train_z": 4.24,
+    "train_n": 1004,
+    "fwd_copy_roi": -0.5724,
+    "fwd_n": 6,
+    "med_size": 17.1,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x64096d6c0020cb82f282876760d207e91f860414",
+    "train_copy_roi": 0.0437,
+    "train_z": 3.11,
+    "train_n": 606,
+    "fwd_copy_roi": null,
+    "fwd_n": 0,
+    "med_size": 50.0,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0xc78cdeb598f0bb8bae62a80e8134e842b3c44455",
+    "train_copy_roi": 0.0435,
+    "train_z": 5.48,
+    "train_n": 1182,
+    "fwd_copy_roi": null,
+    "fwd_n": 0,
+    "med_size": 350.0,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x312d268ab4d1823684d6838f24a3c96da7d66814",
+    "train_copy_roi": 0.0428,
+    "train_z": 3.48,
+    "train_n": 1957,
+    "fwd_copy_roi": 0.0981,
+    "fwd_n": 43,
+    "med_size": 75.5,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x2ba9075a4393227d4f1bee910725a6706de0b078",
+    "train_copy_roi": 0.0412,
+    "train_z": 4.59,
+    "train_n": 1137,
+    "fwd_copy_roi": null,
+    "fwd_n": 0,
+    "med_size": 350.0,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0xff4288c9d0cf320e494174554a752fe9f9ca1548",
+    "train_copy_roi": 0.04,
+    "train_z": 3.17,
+    "train_n": 1768,
+    "fwd_copy_roi": 0.025,
+    "fwd_n": 291,
+    "med_size": 29.2,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x7ba3f3293a09015aeec9fd91a7af70f071db8d20",
+    "train_copy_roi": 0.0397,
+    "train_z": 3.35,
+    "train_n": 1078,
+    "fwd_copy_roi": 0.0802,
+    "fwd_n": 845,
+    "med_size": 9.9,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x5f5945ea1a0be6c3ca7c841769ef892be48ae61d",
+    "train_copy_roi": 0.0393,
+    "train_z": 4.14,
+    "train_n": 1948,
+    "fwd_copy_roi": 0.1136,
+    "fwd_n": 41,
+    "med_size": 27.4,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x5ed80437ecc55ad71260e71e0c2a8bd9e73b303d",
+    "train_copy_roi": 0.0391,
+    "train_z": 4.92,
+    "train_n": 1619,
+    "fwd_copy_roi": 0.1861,
+    "fwd_n": 331,
+    "med_size": 188.5,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x9c5ee2dbc061988546414f0ef376c430c56287da",
+    "train_copy_roi": 0.0373,
+    "train_z": 3.69,
+    "train_n": 890,
+    "fwd_copy_roi": null,
+    "fwd_n": 0,
+    "med_size": 22.4,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x303f943c371d7df8a95e3071e53ade5e287caa41",
+    "train_copy_roi": 0.0367,
+    "train_z": 3.34,
+    "train_n": 1574,
+    "fwd_copy_roi": 0.0296,
+    "fwd_n": 74,
+    "med_size": 10.0,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x3d62c046ec89150cfffbbba421d378778326e173",
+    "train_copy_roi": 0.0348,
+    "train_z": 4.68,
+    "train_n": 674,
+    "fwd_copy_roi": null,
+    "fwd_n": 0,
+    "med_size": 21.0,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x34f4c3118569f32ef02441326305bca0ff5816bd",
+    "train_copy_roi": 0.0336,
+    "train_z": 3.96,
+    "train_n": 1910,
+    "fwd_copy_roi": -0.3303,
+    "fwd_n": 205,
+    "med_size": 30.0,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x8783bb044976ff3d11654ffa27cbcc0e921c8d5f",
+    "train_copy_roi": 0.0284,
+    "train_z": 3.44,
+    "train_n": 1729,
+    "fwd_copy_roi": -0.0575,
+    "fwd_n": 205,
+    "med_size": 5.0,
+    "consistency": 0.67
+  },
+  {
+    "wallet": "0xa6214292fba769fc1c0a11c3191cefe197bf6e29",
+    "train_copy_roi": 0.0241,
+    "train_z": 5.0,
+    "train_n": 1958,
+    "fwd_copy_roi": -0.0131,
+    "fwd_n": 17,
+    "med_size": 23.1,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x8c1026f774fe33016fb36d5f18f5e791d3e0d7b3",
+    "train_copy_roi": 0.0215,
+    "train_z": 3.16,
+    "train_n": 1126,
+    "fwd_copy_roi": 0.0198,
+    "fwd_n": 253,
+    "med_size": 104.0,
+    "consistency": 0.71
+  },
+  {
+    "wallet": "0xe4b4e0710005c51a625afb51a6469d3ea94c18d6",
+    "train_copy_roi": 0.0184,
+    "train_z": 4.13,
+    "train_n": 1026,
+    "fwd_copy_roi": -0.1394,
+    "fwd_n": 6,
+    "med_size": 165.5,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0xa45d6698070c771e662c80d57925fd28bc249026",
+    "train_copy_roi": 0.0177,
+    "train_z": 3.98,
+    "train_n": 906,
+    "fwd_copy_roi": null,
+    "fwd_n": 0,
+    "med_size": 26.1,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x167790e5dff0404a40e511682d792b98ce930521",
+    "train_copy_roi": 0.0148,
+    "train_z": 4.34,
+    "train_n": 1568,
+    "fwd_copy_roi": null,
+    "fwd_n": 0,
+    "med_size": 6.6,
+    "consistency": 1.0
+  },
+  {
+    "wallet": "0x875e974594985283c999765461bf2e15b4dee6b5",
+    "train_copy_roi": 0.0102,
+    "train_z": 4.25,
+    "train_n": 1806,
+    "fwd_copy_roi": -0.0288,
+    "fwd_n": 157,
+    "med_size": 297.6,
+    "consistency": 0.67
+  },
+  {
+    "wallet": "0x7ca56b03105371839e4a3d98f4c1059d10d784bc",
+    "train_copy_roi": 0.0063,
+    "train_z": 4.57,
+    "train_n": 1610,
+    "fwd_copy_roi": 0.0181,
+    "fwd_n": 300,
+    "med_size": 33.0,
+    "consistency": 0.67
+  }
+]
\ No newline at end of file
diff --git a/live/strategy.py b/live/strategy.py
new file mode 100644
index 00000000..93345991
--- /dev/null
+++ b/live/strategy.py
@@ -0,0 +1,162 @@
+#!/usr/bin/env python3
+"""Train/test wallet-selection study, entirely from the local cache.
+
+TRAIN  = bets resolved before --train-end (default 2026-05-30): pick wallets.
+TEST   = bets resolved on/after --test-start (default 2026-06-01), resolved only:
+         validate which picks were actually profitable to follow forward.
+
+Lens: we have $1,000 and copy flat-size, so the key metric is COPY-ROI — the
+mean per-bet return if we mirror each entry with the same stake:
+    win  -> (1-p)/p   per $1   (entry at price p pays out at 1)
+    loss -> -1
+A wallet with positive copy-ROI would have made us money (before lag/fees).
+We also compute z (beats entry prices) and the wallet's own $ ROI.
+
+Selection gates (all on TRAIN):
+  * n >= MIN_N resolved bets
+  * z significant (Benjamini-Hochberg FDR)
+  * copy-ROI > 0  (copying them actually paid)
+  * consistent: positive copy-ROI in >= CONSISTENCY of monthly buckets
+  * copyable proxies: median bet size in [$5,$5000] (not dust, not whale),
+    not at the ~2000-bet HFT cap, not one-market-dependent
+
+    python3 strategy.py
+"""
+
+import math
+import os
+import sys
+import time
+from collections import defaultdict
+
+import duckdb
+
+HERE = os.path.dirname(__file__)
+DB = os.path.join(HERE, "cache.duckdb")
+TRAIN_END = time.mktime(time.strptime(os.environ.get("TRAIN_END", "2026-05-30"), "%Y-%m-%d"))
+TEST_START = time.mktime(time.strptime(os.environ.get("TEST_START", "2026-06-01"), "%Y-%m-%d"))
+MIN_N = 30                # train bets needed to judge a wallet
+MIN_N_TEST = 5            # forward bets needed to report a forward number
+CAP = 1990               # >= this looks API-capped (HFT/truncated) -> deprioritize
+SIZE_LO, SIZE_HI = 5.0, 5000.0     # copyable median bet size ($)
+CONSISTENCY = 0.6        # fraction of monthly buckets that must be profitable
+FDR_Q = 0.05
+
+
+def ret(p, won):
+    return (1 - p) / p if won else -1.0       # copy return per $1 staked
+
+
+def metrics(bets):
+    n = len(bets)
+    wins = sum(1 for b in bets if b["won"])
+    exp = sum(b["p"] for b in bets)
+    var = sum(b["p"] * (1 - b["p"]) for b in bets) or 1e-9
+    z = (wins - exp) / math.sqrt(var)
+    copy_roi = sum(ret(b["p"], b["won"]) for b in bets) / n
+    staked = sum(b["size"] for b in bets) or 1e-9
+    dollars = sum((b["size"] * (1 - b["p"]) / b["p"] if b["won"] else -b["size"]) for b in bets)
+    return dict(n=n, wins=wins, win_rate=100 * wins / n, z=z, copy_roi=copy_roi,
+                own_roi=dollars / staked, exp=exp)
+
+
+def consistency(bets):
+    """fraction of calendar-month buckets (by res_t) with positive copy-ROI."""
+    buck = defaultdict(list)
+    for b in bets:
+        buck[time.strftime("%Y-%m", time.localtime(b["res_t"] or 0))].append(b)
+    months = [m for m in buck.values() if len(m) >= 5]
+    if not months:
+        return 0.0, 0
+    good = sum(1 for m in months if sum(ret(b["p"], b["won"]) for b in m) > 0)
+    return good / len(months), len(months)
+
+
+def concentration(bets):
+    """share of total copy-return coming from the single best market."""
+    by = defaultdict(float)
+    for b in bets:
+        by[b["cond"]] += ret(b["p"], b["won"])
+    tot = sum(v for v in by.values() if v > 0) or 1e-9
+    return max(by.values()) / tot if by else 1.0
+
+
+def norm_sf(z):
+    return 0.5 * math.erfc(z / math.sqrt(2))
+
+
+def main():
+    con = duckdb.connect(DB, read_only=True)
+    wallets = [r[0] for r in con.execute("SELECT DISTINCT wallet FROM bets").fetchall()]
+    print(f"loaded {len(wallets):,} wallets; train<{time.strftime('%F', time.localtime(TRAIN_END))}"
+          f" test>={time.strftime('%F', time.localtime(TEST_START))}\n", flush=True)
+
+    cand = []
+    for w in wallets:
+        rows = con.execute(
+            "SELECT won,p,res_t,size,cond FROM bets WHERE wallet=?", [w]).fetchall()
+        bets = [dict(won=x[0], p=max(0.001, min(0.999, x[1] or 0)),
+                     res_t=x[2], size=x[3] or 0, cond=x[4]) for x in rows]
+        train = [b for b in bets if (b["res_t"] or 0) < TRAIN_END]
+        if len(train) < MIN_N:
+            continue
+        m = metrics(train)
+        med = sorted(b["size"] for b in train)[len(train) // 2]
+        cons, nmonths = consistency(train)
+        conc = concentration(train)
+        test = [b for b in bets if (b["res_t"] or 0) >= TEST_START]
+        tm = metrics(test) if len(test) >= MIN_N_TEST else None
+        cand.append(dict(w=w, m=m, med=med, cons=cons, nmonths=nmonths, conc=conc,
+                         capped=len(train) >= CAP, tm=tm, ntest=len(test)))
+
+    # FDR over the candidate edge p-values
+    pvals = sorted(norm_sf(c["m"]["z"]) for c in cand)
+    k = 0
+    for i, p in enumerate(pvals, 1):
+        if p <= FDR_Q * i / len(pvals):
+            k = i
+    thr = pvals[k - 1] if k else 0.0
+
+    # selection gates (all on TRAIN)
+    sel = [c for c in cand if
+           norm_sf(c["m"]["z"]) <= thr and thr > 0 and
+           c["m"]["copy_roi"] > 0 and
+           c["cons"] >= CONSISTENCY and
+           SIZE_LO <= c["med"] <= SIZE_HI and
+           not c["capped"] and
+           c["conc"] < 0.5]
+    sel.sort(key=lambda c: c["m"]["copy_roi"], reverse=True)
+
+    print(f"{len(cand):,} wallets with >= {MIN_N} train bets · BH thr p<= {thr:.1e}")
+    print(f"SELECTED (skilled + consistent + copyable on TRAIN): {len(sel)}\n")
+
+    # how did the SELECTED set do FORWARD?
+    fwd = [c for c in sel if c["tm"]]
+    if fwd:
+        avg_fwd = sum(c["tm"]["copy_roi"] for c in fwd) / len(fwd)
+        win_fwd = sum(1 for c in fwd if c["tm"]["copy_roi"] > 0)
+        print(f"FORWARD (June1+, resolved): {len(fwd)} selected wallets had test bets · "
+              f"{win_fwd}/{len(fwd)} stayed profitable · mean fwd copy-ROI {avg_fwd:+.1%}\n")
+
+    h = (f"{'train_roi':>10}{'fwd_roi':>9}{'tr_z':>6}{'tr_wr':>6}{'cons':>6}"
+         f"{'medSz':>7}{'tr_n':>6}{'fwd_n':>6}  wallet")
+    print(h); print("-" * len(h))
+    for c in sel[:40]:
+        t = c["tm"]
+        fr = f"{t['copy_roi']:+.0%}" if t else "  —"
+        fn = c["ntest"] if t else 0
+        print(f"{c['m']['copy_roi']:>+9.0%}{fr:>9}{c['m']['z']:>6.1f}{c['m']['win_rate']:>5.0f}%"
+              f"{c['cons']:>6.0%}{c['med']:>7.0f}{c['m']['n']:>6}{fn:>6}  {c['w']}")
+    # persist the selection for the followability pull + watchlist
+    import json
+    json.dump([{"wallet": c["w"], "train_copy_roi": round(c["m"]["copy_roi"], 4),
+                "train_z": round(c["m"]["z"], 2), "train_n": c["m"]["n"],
+                "fwd_copy_roi": round(c["tm"]["copy_roi"], 4) if c["tm"] else None,
+                "fwd_n": c["ntest"], "med_size": round(c["med"], 1),
+                "consistency": round(c["cons"], 2)} for c in sel],
+              open(os.path.join(HERE, "selection.json"), "w"), indent=2)
+    print(f"\n-> selection.json ({len(sel)} wallets)")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/live/watch_final.json b/live/watch_final.json
new file mode 100644
index 00000000..70fbff3f
--- /dev/null
+++ b/live/watch_final.json
@@ -0,0 +1,849 @@
+[
+  {
+    "wallet": "0xe8ca3f758c93f44f3ec210542ab78afb7c0bcccb",
+    "name": "0xe8ca3f75",
+    "foll_fwd_copy_roi": 2.7036,
+    "med_lead_h": 95.6,
+    "cadence_per_day": 8.7,
+    "followable_frac": 0.99,
+    "fwd_followable_n": 93,
+    "train_z": 18.86,
+    "train_copy_roi": 2.8782
+  },
+  {
+    "wallet": "0x0a7aaf83341b52df34e8ffef52aa295538d6df1b",
+    "name": "0x0a7aaf83",
+    "foll_fwd_copy_roi": 2.134,
+    "med_lead_h": 248.8,
+    "cadence_per_day": 9.8,
+    "followable_frac": 0.99,
+    "fwd_followable_n": 138,
+    "train_z": 7.21,
+    "train_copy_roi": 0.5841
+  },
+  {
+    "wallet": "0xfd4263b3ad08226034fe1b1ea678a46d80b58895",
+    "name": "0xfd4263b3",
+    "foll_fwd_copy_roi": 0.9877,
+    "med_lead_h": 256.3,
+    "cadence_per_day": 5.8,
+    "followable_frac": 0.98,
+    "fwd_followable_n": 39,
+    "train_z": 15.53,
+    "train_copy_roi": 2.1616
+  },
+  {
+    "wallet": "0x13464aabec792c36b062316f474713e681330448",
+    "name": "0x13464aab",
+    "foll_fwd_copy_roi": 0.9692,
+    "med_lead_h": 158.6,
+    "cadence_per_day": 5.8,
+    "followable_frac": 0.96,
+    "fwd_followable_n": 89,
+    "train_z": 7.33,
+    "train_copy_roi": 0.512
+  },
+  {
+    "wallet": "0xad703ba9fa7af1447bfcfe22522d052df64f4ccf",
+    "name": "0xad703ba9",
+    "foll_fwd_copy_roi": 0.9587,
+    "med_lead_h": 39.6,
+    "cadence_per_day": 11.0,
+    "followable_frac": 0.99,
+    "fwd_followable_n": 163,
+    "train_z": 3.98,
+    "train_copy_roi": 0.3063
+  },
+  {
+    "wallet": "0x36bfcd8ab96dce2ddea30145ab749b59c6362864",
+    "name": "0x36bfcd8a",
+    "foll_fwd_copy_roi": 0.8856,
+    "med_lead_h": 157.7,
+    "cadence_per_day": 16.9,
+    "followable_frac": 1.0,
+    "fwd_followable_n": 96,
+    "train_z": 7.03,
+    "train_copy_roi": 0.2044
+  },
+  {
+    "wallet": "0x2d4bf8f846bf68f43b9157bf30810d334ac6ca7a",
+    "name": "0x2d4bf8f8",
+    "foll_fwd_copy_roi": 0.6857,
+    "med_lead_h": 364.3,
+    "cadence_per_day": 6.8,
+    "followable_frac": 0.99,
+    "fwd_followable_n": 110,
+    "train_z": 19.72,
+    "train_copy_roi": 0.8859
+  },
+  {
+    "wallet": "0xade74a23c444d0eebee00034459fbc269fab58af",
+    "name": "0xade74a23",
+    "foll_fwd_copy_roi": 0.6597,
+    "med_lead_h": 161.4,
+    "cadence_per_day": 1.5,
+    "followable_frac": 1.0,
+    "fwd_followable_n": 18,
+    "train_z": 6.43,
+    "train_copy_roi": 0.3886
+  },
+  {
+    "wallet": "0xab2067f2bfe4a5bce93cda6f418cde1515d2d9e2",
+    "name": "0xab2067f2",
+    "foll_fwd_copy_roi": 0.5481,
+    "med_lead_h": 161.4,
+    "cadence_per_day": 3.8,
+    "followable_frac": 1.0,
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\ No newline at end of file