add pattern analysis feature with web dashboard and CLI

New /patterns page with 9 analyses: chair win bias, bet rank
correlations, hand type distributions, pot size buckets, streaks,
hourly patterns, and recent-vs-overall comparison. Also adds a
standalone analyze.py CLI script for terminal output.

analyze.py

@@ -0,0 +1,166 @@
+#!/usr/bin/env python3
+"""
+Standalone CLI script for Teen Patti pattern analysis.
+
+Usage:
+    python analyze.py --host localhost --port 8123
+"""
+
+import argparse
+import sys
+
+
+def fmt_pct(n, total):
+    return f"{n/total*100:.1f}%" if total else "0.0%"
+
+
+def print_table(headers, rows, col_widths=None):
+    """Print a simple formatted table."""
+    if not col_widths:
+        col_widths = [max(len(str(h)), *(len(str(r[i])) for r in rows))
+                      for i, h in enumerate(headers)]
+    # Header
+    hdr = "  ".join(str(h).ljust(w) for h, w in zip(headers, col_widths))
+    print(hdr)
+    print("-" * len(hdr))
+    for row in rows:
+        print("  ".join(str(c).ljust(w) for c, w in zip(row, col_widths)))
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Teen Patti Pattern Analysis CLI")
+    parser.add_argument("--host", default="localhost", help="ClickHouse host")
+    parser.add_argument("--port", type=int, default=8123, help="ClickHouse HTTP port")
+    args = parser.parse_args()
+
+    # Set config before importing db
+    from app import config
+    config.CLICKHOUSE_HOST = args.host
+    config.CLICKHOUSE_PORT = args.port
+
+    from app import db
+
+    print(f"Connecting to ClickHouse at {args.host}:{args.port}...")
+    try:
+        data = db.get_pattern_analysis()
+    except Exception as e:
+        print(f"Error: {e}", file=sys.stderr)
+        sys.exit(1)
+
+    total = data["chair_bias"]["total_games"]
+    print(f"\n{'='*60}")
+    print(f"  TEEN PATTI PATTERN ANALYSIS  ({total:,} games)")
+    print(f"{'='*60}\n")
+
+    # 1. Chair Win Bias
+    print("1. CHAIR WIN BIAS (expected 33.3%)")
+    cb = data["chair_bias"]
+    rows = []
+    for ch in ("A", "B", "C"):
+        d = cb[ch]
+        diff = d["pct"] - 33.3
+        sign = "+" if diff >= 0 else ""
+        rows.append([ch, f"{d['wins']:,}", f"{d['pct']:.1f}%", f"{sign}{diff:.1f}%"])
+    print_table(["Chair", "Wins", "Win %", "vs Expected"], rows)
+
+    # 2. Bet Rank Analysis
+    print("\n2. BET RANK ANALYSIS")
+    br = data["bet_rank"]
+    br_total = br["high"] + br["mid"] + br["low"]
+    rows = []
+    for rank in ("high", "mid", "low"):
+        rows.append([rank.capitalize(), f"{br[rank]:,}", fmt_pct(br[rank], br_total)])
+    print_table(["Rank", "Wins", "Win %"], rows)
+
+    # 3. Per-Chair Bet Rank
+    print("\n3. PER-CHAIR: HIGHEST BET WIN RATE")
+    print("   When chair X has the highest bet, how often does X win?")
+    pcr = data["per_chair_rank"]
+    rows = []
+    for ch in ("A", "B", "C"):
+        d = pcr.get(ch, {})
+        rows.append([ch, f"{d.get('has_highest', 0):,}",
+                      f"{d.get('wins', 0):,}", f"{d.get('win_pct', 0):.1f}%"])
+    print_table(["Chair", "Times Highest", "Wins", "Win %"], rows)
+
+    # 4. Hand Type Distribution by Chair
+    print("\n4. HAND TYPE DISTRIBUTION BY CHAIR")
+    htbc = data["hand_types_by_chair"]
+    hand_order = ["Trail", "Straight Flush", "Straight", "Flush", "Pair", "High Card"]
+    rows = []
+    for ht in hand_order:
+        a = htbc["A"].get(ht, 0)
+        b = htbc["B"].get(ht, 0)
+        c = htbc["C"].get(ht, 0)
+        if a + b + c == 0:
+            continue
+        rows.append([ht, f"{a:,}", f"{b:,}", f"{c:,}"])
+    print_table(["Hand Type", "Chair A", "Chair B", "Chair C"], rows)
+
+    # 5. Hand Type Win Rates
+    print("\n5. HAND TYPE WIN RATES")
+    htw = data["hand_type_wins"]
+    htw_total = sum(htw.values())
+    rows = []
+    for ht in hand_order:
+        v = htw.get(ht, 0)
+        if v == 0:
+            continue
+        rows.append([ht, f"{v:,}", fmt_pct(v, htw_total)])
+    print_table(["Hand Type", "Wins", "Win %"], rows)
+
+    # 6. Pot Size Buckets
+    print("\n6. WIN RATES BY POT SIZE")
+    pb = data["pot_buckets"]
+    ranges = pb.get("_ranges", {})
+    rows = []
+    for bucket in ("small", "medium", "large", "whale"):
+        d = pb.get(bucket)
+        if not d:
+            continue
+        t = d["total"] or 1
+        rows.append([
+            bucket.capitalize(), ranges.get(bucket, ""),
+            f"{d['total']:,}",
+            f"{d['A']/t*100:.1f}%", f"{d['B']/t*100:.1f}%", f"{d['C']/t*100:.1f}%",
+        ])
+    print_table(["Bucket", "Range", "Games", "A %", "B %", "C %"], rows)
+
+    # 7. Streaks
+    print("\n7. STREAK ANALYSIS")
+    streaks = data["streaks"]
+    rows = []
+    for ch in ("A", "B", "C"):
+        s = streaks[ch]
+        rows.append([ch, str(s["max_streak"]), str(s["current_streak"])])
+    print_table(["Chair", "Max Streak", "Current Streak"], rows)
+
+    # 8. Hourly Patterns
+    print("\n8. HOURLY PATTERNS (win % by hour)")
+    hourly = data["hourly"]
+    hours = sorted(hourly.keys(), key=lambda h: int(h))
+    rows = []
+    for h in hours:
+        d = hourly[h]
+        t = d["total"] or 1
+        rows.append([
+            f"{int(h):02d}:00", str(d["total"]),
+            f"{d['A']/t*100:.1f}%", f"{d['B']/t*100:.1f}%", f"{d['C']/t*100:.1f}%",
+        ])
+    print_table(["Hour", "Games", "A %", "B %", "C %"], rows)
+
+    # 9. Recent vs Overall
+    print("\n9. RECENT (LAST 100) vs ALL-TIME")
+    rva = data["recent_vs_all"]
+    for label, section in [("All-Time", rva["all"]), ("Last 100", rva["recent"])]:
+        t = section["total"] or 1
+        d = section["dist"]
+        parts = " | ".join(f"{ch}: {d[ch]:>4} ({d[ch]/t*100:.1f}%)" for ch in ("A", "B", "C"))
+        print(f"  {label:>10}  [{t:>5} games]  {parts}")
+
+    print(f"\n{'='*60}")
+    print("  Done.")
+
+
+if __name__ == "__main__":
+    main()

app/db.py

@@ -571,6 +571,202 @@ def get_analytics(period: str = "all") -> dict:
     }
 
 
+@_with_lock
+def get_pattern_analysis() -> dict:
+    """Run all pattern analysis queries and return a single dict."""
+    client = get_client()
+
+    # 1. Chair win bias
+    result = client.query(
+        "SELECT winner, count() AS cnt FROM games GROUP BY winner ORDER BY winner"
+    )
+    chair_wins = {}
+    total_games = 0
+    for row in result.result_rows:
+        chair = config.CHAIRS.get(row[0], "?")
+        chair_wins[chair] = row[1]
+        total_games += row[1]
+    chair_bias = {"total_games": total_games}
+    for ch in ("A", "B", "C"):
+        wins = chair_wins.get(ch, 0)
+        pct = round(wins / total_games * 100, 2) if total_games else 0
+        chair_bias[ch] = {"wins": wins, "pct": pct}
+
+    # 2. Bet rank analysis — how often the highest/mid/lowest bet chair wins
+    rank_result = client.query("""
+        SELECT
+            countIf(winner_bet >= greatest(bet_a, bet_b, bet_c)) AS high,
+            countIf(winner_bet > least(bet_a, bet_b, bet_c)
+                AND winner_bet < greatest(bet_a, bet_b, bet_c)) AS mid,
+            countIf(winner_bet <= least(bet_a, bet_b, bet_c)) AS low
+        FROM (
+            SELECT bet_a, bet_b, bet_c,
+                multiIf(winner = 3, bet_a, winner = 2, bet_b, bet_c) AS winner_bet
+            FROM games WHERE bet_a + bet_b + bet_c > 0
+        )
+    """)
+    bet_rank = {"high": 0, "mid": 0, "low": 0}
+    if rank_result.result_rows:
+        r = rank_result.result_rows[0]
+        bet_rank = {"high": r[0], "mid": r[1], "low": r[2]}
+
+    # 3. Per-chair bet rank — when chair X has max bet, how often does X win?
+    pcr = client.query("""
+        SELECT
+            countIf(bet_a >= greatest(bet_a, bet_b, bet_c) AND bet_a > 0) AS a_high,
+            countIf(bet_a >= greatest(bet_a, bet_b, bet_c) AND bet_a > 0 AND winner = 3) AS a_win,
+            countIf(bet_b >= greatest(bet_a, bet_b, bet_c) AND bet_b > 0) AS b_high,
+            countIf(bet_b >= greatest(bet_a, bet_b, bet_c) AND bet_b > 0 AND winner = 2) AS b_win,
+            countIf(bet_c >= greatest(bet_a, bet_b, bet_c) AND bet_c > 0) AS c_high,
+            countIf(bet_c >= greatest(bet_a, bet_b, bet_c) AND bet_c > 0 AND winner = 1) AS c_win
+        FROM games WHERE bet_a + bet_b + bet_c > 0
+    """)
+    per_chair_rank = {}
+    if pcr.result_rows:
+        r = pcr.result_rows[0]
+        for i, ch in enumerate(("A", "B", "C")):
+            has = r[i * 2]
+            wins = r[i * 2 + 1]
+            per_chair_rank[ch] = {
+                "has_highest": has, "wins": wins,
+                "win_pct": round(wins / has * 100, 2) if has else 0,
+            }
+
+    # 4. Hand type distribution by chair (all dealt hands, not just winners)
+    ht_result = client.query("""
+        SELECT 'A' AS chair, hand_type_a AS ht, count() AS cnt
+            FROM games WHERE hand_type_a > 0 GROUP BY ht
+        UNION ALL
+        SELECT 'B', hand_type_b, count()
+            FROM games WHERE hand_type_b > 0 GROUP BY hand_type_b
+        UNION ALL
+        SELECT 'C', hand_type_c, count()
+            FROM games WHERE hand_type_c > 0 GROUP BY hand_type_c
+        ORDER BY chair, ht
+    """)
+    hand_types_by_chair = {"A": {}, "B": {}, "C": {}}
+    for row in ht_result.result_rows:
+        ch = row[0]
+        type_name = config.HAND_TYPES.get(row[1], f"Type {row[1]}")
+        hand_types_by_chair[ch][type_name] = row[2]
+
+    # 5. Hand type win rates (winning hand type distribution)
+    htw = client.query("""
+        SELECT hand_type, count() AS cnt FROM (
+            SELECT multiIf(winner = 3, hand_type_a, winner = 2, hand_type_b, hand_type_c) AS hand_type
+            FROM games
+        ) WHERE hand_type > 0
+        GROUP BY hand_type ORDER BY hand_type
+    """)
+    hand_type_wins = {}
+    for row in htw.result_rows:
+        type_name = config.HAND_TYPES.get(row[0], f"Type {row[0]}")
+        hand_type_wins[type_name] = row[1]
+
+    # 6. Pot size buckets — win rates by pot quartile
+    qr = client.query("""
+        SELECT
+            quantile(0.25)(total_pot) AS q1,
+            quantile(0.5)(total_pot) AS q2,
+            quantile(0.75)(total_pot) AS q3
+        FROM games
+    """)
+    pot_buckets = {}
+    if qr.result_rows:
+        q1, q2, q3 = int(qr.result_rows[0][0]), int(qr.result_rows[0][1]), int(qr.result_rows[0][2])
+        br = client.query(f"""
+            SELECT
+                multiIf(
+                    total_pot <= {q1}, 'small',
+                    total_pot <= {q2}, 'medium',
+                    total_pot <= {q3}, 'large',
+                    'whale'
+                ) AS bucket,
+                winner, count() AS cnt
+            FROM games GROUP BY bucket, winner
+        """)
+        for row in br.result_rows:
+            bucket, chair_id, cnt = row[0], row[1], row[2]
+            chair = config.CHAIRS.get(chair_id, "?")
+            if bucket not in pot_buckets:
+                pot_buckets[bucket] = {"A": 0, "B": 0, "C": 0, "total": 0}
+            pot_buckets[bucket][chair] = cnt
+            pot_buckets[bucket]["total"] += cnt
+        pot_buckets["_ranges"] = {
+            "small": f"0–{q1}", "medium": f"{q1+1}–{q2}",
+            "large": f"{q2+1}–{q3}", "whale": f">{q3}",
+        }
+
+    # 7. Streak analysis — compute in Python from ordered winners
+    streak_result = client.query(
+        "SELECT winner FROM games ORDER BY game_no ASC"
+    )
+    winners_list = [config.CHAIRS.get(r[0], "?") for r in streak_result.result_rows]
+    streaks = {}
+    for ch in ("A", "B", "C"):
+        max_s = cur = 0
+        for w in winners_list:
+            if w == ch:
+                cur += 1
+                max_s = max(max_s, cur)
+            else:
+                cur = 0
+        # current streak from the end
+        current = 0
+        for w in reversed(winners_list):
+            if w == ch:
+                current += 1
+            else:
+                break
+        streaks[ch] = {"max_streak": max_s, "current_streak": current}
+
+    # 8. Hourly patterns — win rates by hour of day
+    hr_result = client.query("""
+        SELECT toHour(created_at) AS hr, winner, count() AS cnt
+        FROM games GROUP BY hr, winner ORDER BY hr, winner
+    """)
+    hourly = {}
+    for row in hr_result.result_rows:
+        h = str(row[0])
+        chair = config.CHAIRS.get(row[1], "?")
+        if h not in hourly:
+            hourly[h] = {"A": 0, "B": 0, "C": 0, "total": 0}
+        hourly[h][chair] = row[2]
+        hourly[h]["total"] += row[2]
+
+    # 9. Recent (last 100) vs overall
+    recent = client.query("""
+        SELECT winner, count() AS cnt FROM (
+            SELECT winner FROM games ORDER BY game_no DESC LIMIT 100
+        ) GROUP BY winner
+    """)
+    recent_dist = {"A": 0, "B": 0, "C": 0}
+    recent_total = 0
+    for row in recent.result_rows:
+        chair = config.CHAIRS.get(row[0], "?")
+        if chair in recent_dist:
+            recent_dist[chair] = row[1]
+            recent_total += row[1]
+
+    return {
+        "chair_bias": chair_bias,
+        "bet_rank": bet_rank,
+        "per_chair_rank": per_chair_rank,
+        "hand_types_by_chair": hand_types_by_chair,
+        "hand_type_wins": hand_type_wins,
+        "pot_buckets": pot_buckets,
+        "streaks": streaks,
+        "hourly": hourly,
+        "recent_vs_all": {
+            "recent": {"dist": recent_dist, "total": recent_total},
+            "all": {
+                "dist": {ch: chair_bias[ch]["wins"] for ch in ("A", "B", "C")},
+                "total": total_games,
+            },
+        },
+    }
+
+
 @_with_lock
 def get_hot_cold_players(n: int = 5) -> dict:
     """

app/server.py

@@ -41,6 +41,8 @@ class WebServer:
         self.app.router.add_get("/api/hot-cold", self._handle_hot_cold)
         self.app.router.add_get("/analytics", self._handle_analytics_page)
         self.app.router.add_get("/api/analytics", self._handle_analytics)
+        self.app.router.add_get("/patterns", self._handle_patterns_page)
+        self.app.router.add_get("/api/patterns", self._handle_patterns)
         self.app.router.add_get("/ws", self._handle_ws)
         self.app.router.add_static("/static/", STATIC_DIR, name="static")
 
@@ -90,6 +92,18 @@ class WebServer:
         path = os.path.join(STATIC_DIR, "analytics.html")
         return web.FileResponse(path)
 
+    async def _handle_patterns_page(self, request: web.Request) -> web.Response:
+        path = os.path.join(STATIC_DIR, "patterns.html")
+        return web.FileResponse(path)
+
+    async def _handle_patterns(self, request: web.Request) -> web.Response:
+        try:
+            data = await _run_sync(db.get_pattern_analysis)
+            return web.json_response(data)
+        except Exception as e:
+            log.error("Pattern analysis query failed: %s", e)
+            return web.json_response({"error": str(e)}, status=500)
+
     async def _handle_analytics(self, request: web.Request) -> web.Response:
         period = request.query.get("period", "all")
         if period not in ("1h", "6h", "24h", "7d", "all"):

static/analytics.html

@@ -212,7 +212,10 @@
 
 <div class="header">
   <h1>Teen Patti Analytics</h1>
+  <div style="display:flex;gap:14px">
     <a href="/" class="nav-link">Live Dashboard &rarr;</a>
+    <a href="/patterns" class="nav-link">Patterns &rarr;</a>
+  </div>
 </div>
 
 <div class="period-bar">

static/index.html

@@ -602,6 +602,7 @@
   </div>
   <div class="status">
     <a href="/analytics" style="color:var(--accent);text-decoration:none;font-size:12px;font-weight:600;margin-right:10px">Analytics &rarr;</a>
+    <a href="/patterns" style="color:var(--accent);text-decoration:none;font-size:12px;font-weight:600;margin-right:10px">Patterns &rarr;</a>
     <div id="status-dot" class="status-dot"></div>
     <span id="status-text">Connecting...</span>
   </div>

static/patterns.html

@@ -0,0 +1,443 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>Teen Patti Pattern Analysis</title>
+<script src="https://cdn.jsdelivr.net/npm/chart.js@4"></script>
+<style>
+  :root {
+    --bg: #0f1117;
+    --surface: #1a1d27;
+    --surface2: #232736;
+    --surface3: #2a2e42;
+    --border: #2d3148;
+    --text: #e4e6f0;
+    --text2: #8b8fa3;
+    --text3: #5a5f75;
+    --accent: #6c5ce7;
+    --chair-a: #3b82f6;
+    --chair-b: #ec4899;
+    --chair-c: #f59e0b;
+    --green: #10b981;
+    --red: #ef4444;
+  }
+  * { margin: 0; padding: 0; box-sizing: border-box; }
+  body {
+    font-family: -apple-system, 'Segoe UI', Roboto, sans-serif;
+    background: var(--bg);
+    color: var(--text);
+    min-height: 100vh;
+  }
+  .header {
+    display: flex; align-items: center; justify-content: space-between;
+    padding: 10px 20px; background: var(--surface);
+    border-bottom: 1px solid var(--border);
+  }
+  .header h1 { font-size: 15px; font-weight: 700; letter-spacing: -0.3px; }
+  .nav-links { display: flex; gap: 14px; }
+  .nav-link {
+    font-size: 12px; color: var(--accent); text-decoration: none;
+    font-weight: 600; transition: color 0.2s;
+  }
+  .nav-link:hover { color: #a78bfa; }
+  .content { padding: 16px 20px; max-width: 1200px; margin: 0 auto; }
+  .loading {
+    text-align: center; padding: 60px; color: var(--text2); font-size: 14px;
+  }
+  .section {
+    background: var(--surface); border: 1px solid var(--border);
+    border-radius: 8px; padding: 14px; margin-bottom: 16px;
+  }
+  .section-title {
+    font-size: 10px; text-transform: uppercase; letter-spacing: 1.2px;
+    color: var(--text2); margin-bottom: 10px; font-weight: 700;
+  }
+  .section-desc {
+    font-size: 11px; color: var(--text3); margin-bottom: 12px;
+  }
+  .two-col { display: grid; grid-template-columns: 1fr 1fr; gap: 16px; margin-bottom: 16px; }
+  .three-col { display: grid; grid-template-columns: 1fr 1fr 1fr; gap: 16px; margin-bottom: 16px; }
+
+  /* Tables */
+  .ptable { width: 100%; border-collapse: collapse; font-size: 12px; }
+  .ptable th {
+    text-align: left; padding: 6px 8px;
+    border-bottom: 2px solid var(--border);
+    color: var(--text3); font-size: 10px;
+    text-transform: uppercase; letter-spacing: 0.5px; font-weight: 700;
+  }
+  .ptable td { padding: 5px 8px; border-bottom: 1px solid #2d314830; }
+  .ptable tr:hover { background: var(--surface2); }
+  .ptable .num { text-align: right; font-variant-numeric: tabular-nums; font-weight: 600; }
+  .ptable .pct { text-align: right; font-variant-numeric: tabular-nums; color: var(--text2); }
+  .positive { color: var(--green); }
+  .negative { color: var(--red); }
+  .chair-a { color: var(--chair-a); font-weight: 700; }
+  .chair-b { color: var(--chair-b); font-weight: 700; }
+  .chair-c { color: var(--chair-c); font-weight: 700; }
+
+  /* H-bars */
+  .hbar-row { display: flex; align-items: center; gap: 8px; padding: 5px 0; font-size: 13px; }
+  .hbar-label { font-weight: 700; min-width: 80px; font-size: 12px; }
+  .hbar-bg { flex: 1; height: 22px; border-radius: 4px; background: var(--surface3); overflow: hidden; }
+  .hbar-fill { height: 100%; border-radius: 4px; transition: width 0.4s ease; min-width: 2px; }
+  .hbar-value { font-weight: 700; min-width: 50px; text-align: right; font-variant-numeric: tabular-nums; font-size: 12px; }
+  .hbar-pct { font-size: 11px; color: var(--text3); min-width: 45px; text-align: right; }
+
+  /* Chart */
+  .chart-container { position: relative; height: 250px; }
+
+  /* Streak cards */
+  .streak-cards { display: grid; grid-template-columns: repeat(3, 1fr); gap: 10px; }
+  .streak-card {
+    background: var(--surface2); border-radius: 8px; padding: 12px; text-align: center;
+    border: 1px solid var(--border);
+  }
+  .streak-card-label { font-size: 10px; text-transform: uppercase; letter-spacing: 0.8px; color: var(--text3); font-weight: 700; }
+  .streak-card-value { font-size: 28px; font-weight: 800; margin-top: 4px; }
+  .streak-card-sub { font-size: 11px; color: var(--text2); margin-top: 2px; }
+
+  /* Comparison */
+  .compare-grid { display: grid; grid-template-columns: 1fr 1fr; gap: 14px; }
+  .compare-panel {
+    background: var(--surface2); border-radius: 8px; padding: 12px;
+    border: 1px solid var(--border);
+  }
+  .compare-title {
+    font-size: 10px; text-transform: uppercase; letter-spacing: 0.8px;
+    color: var(--text2); font-weight: 700; margin-bottom: 8px;
+  }
+
+  @media (max-width: 768px) {
+    .two-col, .three-col { grid-template-columns: 1fr; }
+    .streak-cards { grid-template-columns: 1fr; }
+    .compare-grid { grid-template-columns: 1fr; }
+  }
+</style>
+</head>
+<body>
+
+<div class="header">
+  <h1>Pattern Analysis</h1>
+  <div class="nav-links">
+    <a href="/" class="nav-link">Live Dashboard &rarr;</a>
+    <a href="/analytics" class="nav-link">Analytics &rarr;</a>
+  </div>
+</div>
+
+<div class="content">
+  <div class="loading" id="loading">Loading pattern analysis...</div>
+  <div id="main" style="display:none">
+
+    <!-- 1. Chair Win Bias -->
+    <div class="two-col">
+      <div class="section">
+        <div class="section-title">Chair Win Bias</div>
+        <div class="section-desc">Win % per chair vs expected 33.3%. Sample: <span id="bias-n">0</span> games.</div>
+        <div id="chair-bias-bars"></div>
+      </div>
+      <div class="section">
+        <div class="section-title">Chair Win Distribution</div>
+        <div class="chart-container" style="height:200px">
+          <canvas id="chair-pie"></canvas>
+        </div>
+      </div>
+    </div>
+
+    <!-- 2 & 3. Bet Rank Analysis -->
+    <div class="two-col">
+      <div class="section">
+        <div class="section-title">Winner Bet Rank</div>
+        <div class="section-desc">How often does the winning chair have the highest, mid, or lowest bet?</div>
+        <div id="bet-rank-bars"></div>
+      </div>
+      <div class="section">
+        <div class="section-title">Per-Chair: Highest Bet Win Rate</div>
+        <div class="section-desc">When chair X has the highest bet, how often does X win?</div>
+        <table class="ptable">
+          <thead><tr><th>Chair</th><th style="text-align:right">Times Highest</th><th style="text-align:right">Wins</th><th style="text-align:right">Win %</th></tr></thead>
+          <tbody id="pcr-body"></tbody>
+        </table>
+      </div>
+    </div>
+
+    <!-- 4 & 5. Hand Type Distribution -->
+    <div class="two-col">
+      <div class="section">
+        <div class="section-title">Hand Type Distribution by Chair</div>
+        <div class="section-desc">Are better hands dealt to certain chairs more often?</div>
+        <div class="chart-container">
+          <canvas id="hand-type-chart"></canvas>
+        </div>
+      </div>
+      <div class="section">
+        <div class="section-title">Hand Type Win Rates</div>
+        <div class="section-desc">Which hand types win most often?</div>
+        <div id="hand-type-wins-bars"></div>
+      </div>
+    </div>
+
+    <!-- 6. Pot Size Buckets -->
+    <div class="section">
+      <div class="section-title">Win Rates by Pot Size</div>
+      <div class="section-desc">Does the pot size affect which chair wins?</div>
+      <table class="ptable">
+        <thead>
+          <tr><th>Bucket</th><th>Range</th><th style="text-align:right">Games</th>
+          <th style="text-align:right">A %</th><th style="text-align:right">B %</th><th style="text-align:right">C %</th></tr>
+        </thead>
+        <tbody id="pot-body"></tbody>
+      </table>
+    </div>
+
+    <!-- 7. Streak Analysis -->
+    <div class="section">
+      <div class="section-title">Streak Analysis</div>
+      <div class="streak-cards" id="streak-cards"></div>
+    </div>
+
+    <!-- 8. Hourly Patterns -->
+    <div class="section">
+      <div class="section-title">Hourly Win Patterns</div>
+      <div class="section-desc">Win rates by hour of day (server time).</div>
+      <div class="chart-container">
+        <canvas id="hourly-chart"></canvas>
+      </div>
+    </div>
+
+    <!-- 9. Recent vs Overall -->
+    <div class="section">
+      <div class="section-title">Recent (Last 100) vs All-Time</div>
+      <div class="section-desc">Spot shifts in chair dominance.</div>
+      <div class="compare-grid">
+        <div class="compare-panel">
+          <div class="compare-title">All-Time</div>
+          <div id="compare-all"></div>
+        </div>
+        <div class="compare-panel">
+          <div class="compare-title">Last 100 Games</div>
+          <div id="compare-recent"></div>
+        </div>
+      </div>
+    </div>
+
+  </div>
+</div>
+
+<script>
+const $ = id => document.getElementById(id);
+const fmt = n => {
+  if (n == null) return '0';
+  const abs = Math.abs(n);
+  if (abs >= 1e6) return (n/1e6).toFixed(1) + 'M';
+  if (abs >= 1e3) return (n/1e3).toFixed(1) + 'K';
+  return String(n);
+};
+const fmtFull = n => n == null ? '0' : Number(n).toLocaleString();
+const CHAIR_COLORS = {A:'#3b82f6', B:'#ec4899', C:'#f59e0b'};
+const HAND_ORDER = ['Trail', 'Straight Flush', 'Straight', 'Flush', 'Pair', 'High Card'];
+
+function renderHBar(container, items, colorFn) {
+  const total = items.reduce((s, i) => s + i.value, 0) || 1;
+  const max = Math.max(...items.map(i => i.value)) || 1;
+  container.innerHTML = items.map(item => {
+    const pct = (item.value / max * 100).toFixed(0);
+    const totalPct = (item.value / total * 100).toFixed(1);
+    const color = colorFn(item.label);
+    return `<div class="hbar-row">
+      <span class="hbar-label" style="color:${color}">${item.label}</span>
+      <div class="hbar-bg"><div class="hbar-fill" style="width:${pct}%;background:${color}"></div></div>
+      <span class="hbar-value">${fmtFull(item.value)}</span>
+      <span class="hbar-pct">${totalPct}%</span>
+    </div>`;
+  }).join('');
+}
+
+function renderComparePanel(el, dist, total) {
+  const items = ['A','B','C'].map(ch => ({label: ch, value: dist[ch] || 0}));
+  renderHBar(el, items, l => CHAIR_COLORS[l]);
+  const note = document.createElement('div');
+  note.style.cssText = 'font-size:10px;color:var(--text3);margin-top:6px';
+  note.textContent = `${total} games`;
+  el.appendChild(note);
+}
+
+function render(data) {
+  // 1. Chair win bias
+  $('bias-n').textContent = fmtFull(data.chair_bias.total_games);
+  const biasItems = ['A','B','C'].map(ch => ({
+    label: `Chair ${ch}`, value: data.chair_bias[ch].wins,
+  }));
+  renderHBar($('chair-bias-bars'), biasItems, l => CHAIR_COLORS[l.replace('Chair ', '')]);
+
+  // Chair pie
+  new Chart($('chair-pie'), {
+    type: 'doughnut',
+    data: {
+      labels: ['A','B','C'],
+      datasets: [{
+        data: ['A','B','C'].map(ch => data.chair_bias[ch].wins),
+        backgroundColor: ['#3b82f6','#ec4899','#f59e0b'],
+        borderWidth: 0,
+      }]
+    },
+    options: {
+      responsive: true, maintainAspectRatio: false,
+      plugins: {
+        legend: { labels: { color: '#8b8fa3', font: { size: 11 } } },
+        tooltip: {
+          callbacks: {
+            label: ctx => {
+              const v = ctx.raw;
+              const t = data.chair_bias.total_games || 1;
+              return ` ${ctx.label}: ${v} (${(v/t*100).toFixed(1)}%)`;
+            }
+          }
+        }
+      }
+    }
+  });
+
+  // 2. Bet rank
+  const br = data.bet_rank;
+  renderHBar($('bet-rank-bars'), [
+    {label: 'High Bet', value: br.high},
+    {label: 'Mid Bet', value: br.mid},
+    {label: 'Low Bet', value: br.low},
+  ], l => l.startsWith('High') ? '#f87171' : l.startsWith('Mid') ? '#fbbf24' : '#34d399');
+
+  // 3. Per-chair rank table
+  const pcrBody = $('pcr-body');
+  pcrBody.innerHTML = ['A','B','C'].map(ch => {
+    const d = data.per_chair_rank[ch] || {};
+    return `<tr>
+      <td class="chair-${ch.toLowerCase()}">${ch}</td>
+      <td class="num">${fmtFull(d.has_highest || 0)}</td>
+      <td class="num">${fmtFull(d.wins || 0)}</td>
+      <td class="num">${(d.win_pct || 0).toFixed(1)}%</td>
+    </tr>`;
+  }).join('');
+
+  // 4. Hand type distribution by chair (grouped bar chart)
+  const htByChair = data.hand_types_by_chair;
+  const htLabels = HAND_ORDER.filter(t =>
+    (htByChair.A[t] || 0) + (htByChair.B[t] || 0) + (htByChair.C[t] || 0) > 0
+  );
+  new Chart($('hand-type-chart'), {
+    type: 'bar',
+    data: {
+      labels: htLabels,
+      datasets: ['A','B','C'].map(ch => ({
+        label: ch,
+        data: htLabels.map(t => htByChair[ch][t] || 0),
+        backgroundColor: CHAIR_COLORS[ch] + '80',
+        borderColor: CHAIR_COLORS[ch],
+        borderWidth: 1,
+      })),
+    },
+    options: {
+      responsive: true, maintainAspectRatio: false,
+      plugins: { legend: { labels: { color: '#8b8fa3', font: { size: 10 }, boxWidth: 12 } } },
+      scales: {
+        x: { ticks: { color: '#5a5f75', font: { size: 10 } }, grid: { color: '#2d314820' } },
+        y: { ticks: { color: '#5a5f75', font: { size: 10 } }, grid: { color: '#2d314830' } },
+      }
+    }
+  });
+
+  // 5. Hand type wins
+  const htw = data.hand_type_wins;
+  const htwItems = HAND_ORDER.filter(t => htw[t]).map(t => ({label: t, value: htw[t]}));
+  renderHBar($('hand-type-wins-bars'), htwItems, () => '#6c5ce7');
+
+  // 6. Pot size buckets
+  const pb = data.pot_buckets;
+  const ranges = pb._ranges || {};
+  const bucketOrder = ['small','medium','large','whale'];
+  $('pot-body').innerHTML = bucketOrder.map(b => {
+    const d = pb[b];
+    if (!d) return '';
+    const t = d.total || 1;
+    return `<tr>
+      <td style="font-weight:700;text-transform:capitalize">${b}</td>
+      <td style="color:var(--text3)">${ranges[b] || ''}</td>
+      <td class="num">${fmtFull(d.total)}</td>
+      <td class="num" style="color:var(--chair-a)">${(d.A/t*100).toFixed(1)}%</td>
+      <td class="num" style="color:var(--chair-b)">${(d.B/t*100).toFixed(1)}%</td>
+      <td class="num" style="color:var(--chair-c)">${(d.C/t*100).toFixed(1)}%</td>
+    </tr>`;
+  }).join('');
+
+  // 7. Streaks
+  const streaks = data.streaks;
+  $('streak-cards').innerHTML = ['A','B','C'].map(ch => {
+    const s = streaks[ch];
+    return `<div class="streak-card">
+      <div class="streak-card-label" style="color:${CHAIR_COLORS[ch]}">Chair ${ch}</div>
+      <div class="streak-card-value" style="color:${CHAIR_COLORS[ch]}">${s.max_streak}</div>
+      <div class="streak-card-sub">Max Streak</div>
+      <div style="font-size:18px;font-weight:700;margin-top:8px;color:${s.current_streak >= 3 ? 'var(--green)' : 'var(--text2)'}">${s.current_streak}</div>
+      <div class="streak-card-sub">Current Streak</div>
+    </div>`;
+  }).join('');
+
+  // 8. Hourly patterns
+  const hourly = data.hourly;
+  const hours = Object.keys(hourly).map(Number).sort((a,b) => a - b);
+  new Chart($('hourly-chart'), {
+    type: 'bar',
+    data: {
+      labels: hours.map(h => String(h).padStart(2, '0') + ':00'),
+      datasets: ['A','B','C'].map(ch => ({
+        label: ch,
+        data: hours.map(h => {
+          const d = hourly[String(h)];
+          return d ? (d[ch] / d.total * 100) : 0;
+        }),
+        backgroundColor: CHAIR_COLORS[ch] + '80',
+        borderColor: CHAIR_COLORS[ch],
+        borderWidth: 1,
+      })),
+    },
+    options: {
+      responsive: true, maintainAspectRatio: false,
+      plugins: {
+        legend: { labels: { color: '#8b8fa3', font: { size: 10 }, boxWidth: 12 } },
+        tooltip: { callbacks: { label: ctx => ` ${ctx.dataset.label}: ${ctx.raw.toFixed(1)}%` } },
+      },
+      scales: {
+        x: { stacked: true, ticks: { color: '#5a5f75', font: { size: 9 } }, grid: { color: '#2d314820' } },
+        y: {
+          stacked: true, max: 100,
+          ticks: { color: '#5a5f75', callback: v => v + '%', font: { size: 10 } },
+          grid: { color: '#2d314830' },
+        },
+      }
+    }
+  });
+
+  // 9. Recent vs Overall
+  const rva = data.recent_vs_all;
+  renderComparePanel($('compare-all'), rva.all.dist, rva.all.total);
+  renderComparePanel($('compare-recent'), rva.recent.dist, rva.recent.total);
+}
+
+// Fetch and render
+fetch('/api/patterns')
+  .then(r => r.json())
+  .then(data => {
+    if (data.error) {
+      $('loading').textContent = 'Error: ' + data.error;
+      return;
+    }
+    $('loading').style.display = 'none';
+    $('main').style.display = 'block';
+    render(data);
+  })
+  .catch(e => {
+    $('loading').textContent = 'Failed to load: ' + e.message;
+  });
+</script>
+</body>
+</html>