add predictions page with game theory analysis and card stats

Bayesian next-chair predictor (Markov chains, base rate, streak regression), statistical tests (chi-squared, runs test, autocorrelation), theory backtesting with rolling accuracy, and card-level analysis (value/suit distribution, face card frequency, top winning cards).
2026-02-25 23:16:37 +05:00
parent d8ec792a88
commit b07b073cc0
6 changed files with 1003 additions and 0 deletions
--- a/static/analytics.html
+++ b/static/analytics.html
@@ -215,6 +215,7 @@
  <div style="display:flex;gap:14px">
    <a href="/" class="nav-link">Live Dashboard &rarr;</a>
    <a href="/patterns" class="nav-link">Patterns &rarr;</a>
+    <a href="/predictions" class="nav-link">Predictions &rarr;</a>
  </div>
 </div>

--- a/static/index.html
+++ b/static/index.html
@@ -603,6 +603,7 @@
  <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>
+    <a href="/predictions" style="color:var(--accent);text-decoration:none;font-size:12px;font-weight:600;margin-right:10px">Predictions &rarr;</a>
    <div id="status-dot" class="status-dot"></div>
    <span id="status-text">Connecting...</span>
  </div>
--- a/static/patterns.html
+++ b/static/patterns.html
@@ -123,6 +123,7 @@
  <div class="nav-links">
    <a href="/" class="nav-link">Live Dashboard &rarr;</a>
    <a href="/analytics" class="nav-link">Analytics &rarr;</a>
+    <a href="/predictions" class="nav-link">Predictions &rarr;</a>
  </div>
 </div>

--- a/static/predictions.html
+++ b/static/predictions.html
@@ -0,0 +1,528 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>Predictions &amp; Game Theory</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, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; background: var(--bg); color: var(--text); }
+
+.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: 1400px; margin: 0 auto; }
+.loading { text-align: center; padding: 60px; color: var(--text2); font-size: 14px; }
+
+.section { margin-bottom: 24px; }
+.section-title {
+  font-size: 13px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.5px;
+  color: var(--text2); margin-bottom: 12px; padding-bottom: 6px; border-bottom: 1px solid var(--border);
+}
+
+/* Hero prediction cards */
+.pred-cards { display: grid; grid-template-columns: repeat(3, 1fr); gap: 16px; margin-bottom: 16px; }
+.pred-card {
+  background: var(--surface); border: 1px solid var(--border); border-radius: 10px;
+  padding: 24px; text-align: center; position: relative; transition: all 0.3s;
+}
+.pred-card.recommended {
+  border-color: var(--accent);
+  box-shadow: 0 0 20px rgba(108, 92, 231, 0.3), 0 0 40px rgba(108, 92, 231, 0.1);
+}
+.pred-card .chair-label { font-size: 14px; font-weight: 700; margin-bottom: 8px; }
+.pred-card .prob { font-size: 42px; font-weight: 800; letter-spacing: -2px; }
+.pred-card .badge {
+  display: inline-block; margin-top: 8px; padding: 3px 10px; border-radius: 12px;
+  font-size: 11px; font-weight: 600; background: var(--accent); color: #fff;
+}
+
+.signal-table { width: 100%; border-collapse: collapse; font-size: 12px; }
+.signal-table th, .signal-table td {
+  padding: 8px 12px; text-align: center; border-bottom: 1px solid var(--border);
+}
+.signal-table th { color: var(--text2); font-weight: 600; text-transform: uppercase; font-size: 11px; }
+
+/* Two-column layout */
+.two-col { display: grid; grid-template-columns: 1fr 1fr; gap: 16px; }
+.panel {
+  background: var(--surface); border: 1px solid var(--border); border-radius: 8px; padding: 16px;
+}
+.panel-title { font-size: 12px; font-weight: 700; color: var(--text2); margin-bottom: 12px; text-transform: uppercase; }
+
+/* Heatmap tables */
+.heatmap { width: 100%; border-collapse: collapse; font-size: 12px; }
+.heatmap th, .heatmap td { padding: 6px 8px; text-align: center; border: 1px solid var(--border); }
+.heatmap th { background: var(--surface2); color: var(--text2); font-weight: 600; font-size: 11px; }
+
+/* Stat cards */
+.stat-cards { display: grid; grid-template-columns: repeat(3, 1fr); gap: 16px; }
+.stat-card {
+  background: var(--surface); border: 1px solid var(--border); border-radius: 8px;
+  padding: 20px; text-align: center;
+}
+.stat-card .label { font-size: 12px; color: var(--text2); font-weight: 600; margin-bottom: 4px; }
+.stat-card .value { font-size: 28px; font-weight: 800; }
+
+/* Test result panels */
+.test-result { margin-bottom: 8px; }
+.test-result .test-label { font-size: 11px; color: var(--text3); font-weight: 600; text-transform: uppercase; }
+.test-result .test-value { font-size: 16px; font-weight: 700; }
+.test-result .test-interpret { font-size: 12px; color: var(--text2); margin-top: 2px; }
+.significant { color: var(--red); }
+.not-significant { color: var(--green); }
+
+/* Chart containers */
+.chart-container { position: relative; height: 300px; }
+.chart-container-sm { position: relative; height: 250px; }
+
+/* Backtest */
+.backtest-grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(140px, 1fr)); gap: 12px; margin-bottom: 16px; }
+.bt-card {
+  background: var(--surface); border: 1px solid var(--border); border-radius: 8px;
+  padding: 14px; text-align: center;
+}
+.bt-card .bt-name { font-size: 11px; color: var(--text2); font-weight: 600; text-transform: uppercase; margin-bottom: 4px; }
+.bt-card .bt-acc { font-size: 24px; font-weight: 800; }
+.bt-card .bt-acc.above { color: var(--green); }
+.bt-card .bt-acc.below { color: var(--red); }
+
+@media (max-width: 768px) {
+  .pred-cards, .two-col, .stat-cards { grid-template-columns: 1fr; }
+  .backtest-grid { grid-template-columns: repeat(2, 1fr); }
+  .pred-card .prob { font-size: 32px; }
+}
+</style>
+</head>
+<body>
+<div class="header">
+  <h1>Predictions &amp; Game Theory</h1>
+  <div class="nav-links">
+    <a href="/" class="nav-link">Live Dashboard &rarr;</a>
+    <a href="/analytics" class="nav-link">Analytics &rarr;</a>
+    <a href="/patterns" class="nav-link">Patterns &rarr;</a>
+  </div>
+</div>
+<div class="content">
+  <div id="loading" class="loading">Loading prediction data...</div>
+  <div id="main" style="display:none">
+
+    <!-- Bayesian Prediction Hero -->
+    <div class="section">
+      <div class="section-title">Bayesian Next-Chair Prediction</div>
+      <div id="pred-cards" class="pred-cards"></div>
+      <div class="panel" style="margin-top:8px">
+        <div class="panel-title">Signal Breakdown</div>
+        <table class="signal-table" id="signal-table">
+          <thead><tr><th>Signal</th><th>Weight</th><th>A</th><th>B</th><th>C</th></tr></thead>
+          <tbody></tbody>
+        </table>
+      </div>
+    </div>
+
+    <!-- Markov Matrices -->
+    <div class="section">
+      <div class="section-title">Markov Transition Matrices</div>
+      <div class="two-col">
+        <div class="panel">
+          <div class="panel-title">1st Order &mdash; P(next | last)</div>
+          <table class="heatmap" id="markov1-table"></table>
+        </div>
+        <div class="panel">
+          <div class="panel-title">2nd Order &mdash; P(next | last two)</div>
+          <table class="heatmap" id="markov2-table"></table>
+        </div>
+      </div>
+    </div>
+
+    <!-- Autocorrelation -->
+    <div class="section">
+      <div class="section-title">Autocorrelation (Lags 1&ndash;5)</div>
+      <div class="panel">
+        <div class="chart-container-sm"><canvas id="autocorr-chart"></canvas></div>
+      </div>
+    </div>
+
+    <!-- Statistical Tests -->
+    <div class="section">
+      <div class="section-title">Statistical Tests</div>
+      <div class="two-col">
+        <div class="panel">
+          <div class="panel-title">Chi-Squared Goodness of Fit</div>
+          <div id="chi-results"></div>
+        </div>
+        <div class="panel">
+          <div class="panel-title">Wald-Wolfowitz Runs Test</div>
+          <div id="runs-results"></div>
+        </div>
+      </div>
+    </div>
+
+    <!-- Theory Backtesting -->
+    <div class="section">
+      <div class="section-title">Theory Backtesting</div>
+      <div id="backtest-cards" class="backtest-grid"></div>
+      <div class="panel">
+        <div class="panel-title">Rolling Accuracy (Last 200 Games)</div>
+        <div class="chart-container"><canvas id="backtest-chart"></canvas></div>
+      </div>
+    </div>
+
+    <!-- Card Value Distribution -->
+    <div class="section">
+      <div class="section-title">Card Value Distribution by Chair (Last 500 Games)</div>
+      <div class="panel">
+        <div class="chart-container"><canvas id="card-value-chart"></canvas></div>
+      </div>
+    </div>
+
+    <!-- Face Card Frequency -->
+    <div class="section">
+      <div class="section-title">Face Card Frequency (J, Q, K, A)</div>
+      <div id="face-cards" class="stat-cards"></div>
+    </div>
+
+    <!-- Suit Distribution -->
+    <div class="section">
+      <div class="section-title">Suit Distribution by Chair</div>
+      <div class="panel">
+        <div class="chart-container-sm"><canvas id="suit-chart"></canvas></div>
+      </div>
+    </div>
+
+    <!-- Top Winning Cards -->
+    <div class="section">
+      <div class="section-title">Top 20 Cards in Winning Hands</div>
+      <div class="panel">
+        <div class="chart-container"><canvas id="winning-cards-chart"></canvas></div>
+      </div>
+    </div>
+
+  </div>
+</div>
+
+<script>
+const $ = id => document.getElementById(id);
+const CHAIRS = ['A', 'B', 'C'];
+const CHAIR_COLORS = {A:'#3b82f6', B:'#ec4899', C:'#f59e0b'};
+const CHART_DEFAULTS = {
+  responsive: true, maintainAspectRatio: false,
+  plugins: { legend: { labels: { color: '#8b8fa3', font: { size: 11 } } } },
+  scales: {
+    x: { ticks: { color: '#5a5f75', font: { size: 10 } }, grid: { color: '#2d3148' } },
+    y: { ticks: { color: '#5a5f75', font: { size: 10 } }, grid: { color: '#2d3148' } }
+  }
+};
+
+function heatColor(val) {
+  // val is probability 0-1, center at 0.333
+  const diff = val - 1/3;
+  if (diff > 0) {
+    const intensity = Math.min(diff * 6, 1);
+    return `rgba(16, 185, 129, ${0.15 + intensity * 0.5})`;  // green
+  } else {
+    const intensity = Math.min(Math.abs(diff) * 6, 1);
+    return `rgba(239, 68, 68, ${0.15 + intensity * 0.5})`;  // red
+  }
+}
+
+function pct(v) { return (v * 100).toFixed(1) + '%'; }
+
+function renderPrediction(data) {
+  const container = $('pred-cards');
+  const best = CHAIRS.reduce((a, b) => data.prediction[a] > data.prediction[b] ? a : b);
+  container.innerHTML = CHAIRS.map(c => {
+    const p = data.prediction[c];
+    const isBest = c === best;
+    return `<div class="pred-card ${isBest ? 'recommended' : ''}">
+      <div class="chair-label" style="color:${CHAIR_COLORS[c]}">Chair ${c}</div>
+      <div class="prob" style="color:${CHAIR_COLORS[c]}">${pct(p)}</div>
+      ${isBest ? '<div class="badge">Recommended</div>' : ''}
+    </div>`;
+  }).join('');
+
+  // Signal table
+  const tbody = $('signal-table').querySelector('tbody');
+  const sigNames = {'base_rate':'Base Rate','markov_1':'Markov-1','markov_2':'Markov-2','recent_20':'Recent 20','streak':'Streak'};
+  tbody.innerHTML = Object.entries(data.signals).map(([key, sig]) =>
+    `<tr><td style="text-align:left">${sigNames[key]||key}</td><td>${(sig.weight*100).toFixed(0)}%</td>` +
+    CHAIRS.map(c => `<td style="color:${CHAIR_COLORS[c]}">${pct(sig.probs[c])}</td>`).join('') + '</tr>'
+  ).join('') +
+    `<tr style="font-weight:700;border-top:2px solid var(--border)"><td style="text-align:left">Combined</td><td>100%</td>` +
+    CHAIRS.map(c => `<td style="color:${CHAIR_COLORS[c]}">${pct(data.prediction[c])}</td>`).join('') + '</tr>';
+}
+
+function renderMarkov1(m) {
+  const t = $('markov1-table');
+  let html = '<tr><th>From \\ To</th>' + CHAIRS.map(c => `<th style="color:${CHAIR_COLORS[c]}">→${c}</th>`).join('') + '</tr>';
+  for (const src of CHAIRS) {
+    html += `<tr><th style="color:${CHAIR_COLORS[src]}">${src}</th>`;
+    for (const dst of CHAIRS) {
+      const v = m.matrix[src]?.[dst] || 0;
+      html += `<td style="background:${heatColor(v)}">${pct(v)}</td>`;
+    }
+    html += '</tr>';
+  }
+  t.innerHTML = html;
+}
+
+function renderMarkov2(m) {
+  const t = $('markov2-table');
+  const keys = [];
+  for (const a of CHAIRS) for (const b of CHAIRS) keys.push(a+b);
+  let html = '<tr><th>From \\ To</th>' + CHAIRS.map(c => `<th style="color:${CHAIR_COLORS[c]}">→${c}</th>`).join('') + '</tr>';
+  for (const key of keys) {
+    html += `<tr><th>${key}</th>`;
+    for (const dst of CHAIRS) {
+      const v = m.matrix[key]?.[dst] || 0;
+      html += `<td style="background:${heatColor(v)}">${pct(v)}</td>`;
+    }
+    html += '</tr>';
+  }
+  t.innerHTML = html;
+}
+
+function renderAutocorrelation(ac) {
+  const ctx = $('autocorr-chart').getContext('2d');
+  const threshold = ac.length > 0 && ac[0].significant !== undefined ? 1.96 / Math.sqrt(100) : 0.196;
+  new Chart(ctx, {
+    type: 'bar',
+    data: {
+      labels: ac.map(a => `Lag ${a.lag}`),
+      datasets: [{
+        label: 'Autocorrelation',
+        data: ac.map(a => a.r),
+        backgroundColor: ac.map(a => a.significant ? '#ef4444' : '#6c5ce7'),
+        borderRadius: 4,
+      }]
+    },
+    options: {
+      ...CHART_DEFAULTS,
+      plugins: {
+        ...CHART_DEFAULTS.plugins,
+        annotation: undefined,
+        legend: { display: false },
+      },
+      scales: {
+        ...CHART_DEFAULTS.scales,
+        y: { ...CHART_DEFAULTS.scales.y, suggestedMin: -0.3, suggestedMax: 0.3 }
+      }
+    },
+    plugins: [{
+      id: 'thresholdLines',
+      afterDraw(chart) {
+        const {ctx, chartArea, scales} = chart;
+        const yScale = scales.y;
+        ctx.save();
+        ctx.setLineDash([5, 5]);
+        ctx.strokeStyle = '#ef444480';
+        ctx.lineWidth = 1;
+        for (const val of [threshold, -threshold]) {
+          const y = yScale.getPixelForValue(val);
+          ctx.beginPath();
+          ctx.moveTo(chartArea.left, y);
+          ctx.lineTo(chartArea.right, y);
+          ctx.stroke();
+        }
+        ctx.restore();
+      }
+    }]
+  });
+}
+
+function renderChiSquared(chi) {
+  $('chi-results').innerHTML = `
+    <div class="test-result"><div class="test-label">Chi-Squared Statistic</div>
+      <div class="test-value">${chi.chi2}</div></div>
+    <div class="test-result"><div class="test-label">p-value</div>
+      <div class="test-value ${chi.significant ? 'significant' : 'not-significant'}">${chi.p_value}</div></div>
+    <div class="test-result"><div class="test-label">Expected Count (each chair)</div>
+      <div class="test-value">${chi.expected}</div></div>
+    <div class="test-result"><div class="test-label">Observed</div>
+      <div class="test-value">A: ${chi.counts.A} &nbsp; B: ${chi.counts.B} &nbsp; C: ${chi.counts.C}</div></div>
+    <div class="test-result"><div class="test-label">Interpretation</div>
+      <div class="test-interpret ${chi.significant ? 'significant' : 'not-significant'}">
+        ${chi.significant ? 'Distribution is significantly non-uniform (p < 0.05)' : 'Distribution is consistent with uniform (p >= 0.05)'}
+      </div></div>`;
+}
+
+function renderRunsTest(runs) {
+  $('runs-results').innerHTML = `
+    <div class="test-result"><div class="test-label">Observed Runs</div>
+      <div class="test-value">${runs.runs}</div></div>
+    <div class="test-result"><div class="test-label">Expected Runs</div>
+      <div class="test-value">${runs.expected_runs || '—'}</div></div>
+    <div class="test-result"><div class="test-label">Z-Score</div>
+      <div class="test-value">${runs.z_score}</div></div>
+    <div class="test-result"><div class="test-label">p-value</div>
+      <div class="test-value ${runs.significant ? 'significant' : 'not-significant'}">${runs.p_value}</div></div>
+    <div class="test-result"><div class="test-label">Interpretation</div>
+      <div class="test-interpret ${runs.significant ? 'significant' : 'not-significant'}">${runs.interpretation}</div></div>`;
+}
+
+function renderBacktest(bt) {
+  if (bt.error) {
+    $('backtest-cards').innerHTML = `<div style="color:var(--text2)">${bt.error}</div>`;
+    return;
+  }
+  const names = {base_rate:'Base Rate',markov_1:'Markov-1',markov_2:'Markov-2',recent_20:'Recent 20',streak:'Streak',combined:'Combined'};
+  $('backtest-cards').innerHTML = Object.entries(bt.accuracy).map(([key, acc]) =>
+    `<div class="bt-card"><div class="bt-name">${names[key]||key}</div>
+      <div class="bt-acc ${acc > bt.random_baseline ? 'above' : 'below'}">${acc}%</div>
+      <div style="font-size:10px;color:var(--text3);margin-top:4px">vs ${bt.random_baseline}% random</div>
+    </div>`
+  ).join('');
+
+  if (bt.rolling_accuracy) {
+    const ctx = $('backtest-chart').getContext('2d');
+    const colors = {base_rate:'#8b8fa3',markov_1:'#3b82f6',markov_2:'#ec4899',recent_20:'#f59e0b',streak:'#10b981',combined:'#6c5ce7'};
+    const datasets = Object.entries(bt.rolling_accuracy).map(([key, data]) => ({
+      label: names[key]||key, data,
+      borderColor: colors[key]||'#fff', backgroundColor: 'transparent',
+      borderWidth: key === 'combined' ? 3 : 1.5,
+      pointRadius: 0, tension: 0.3,
+    }));
+    new Chart(ctx, {
+      type: 'line',
+      data: { labels: bt.rolling_accuracy.combined.map((_, i) => i + 1), datasets },
+      options: {
+        ...CHART_DEFAULTS,
+        scales: {
+          ...CHART_DEFAULTS.scales,
+          y: { ...CHART_DEFAULTS.scales.y, title: { display: true, text: 'Accuracy %', color: '#5a5f75' } },
+          x: { ...CHART_DEFAULTS.scales.x, title: { display: true, text: 'Game', color: '#5a5f75' },
+               ticks: { ...CHART_DEFAULTS.scales.x.ticks, maxTicksLimit: 10 } }
+        }
+      },
+      plugins: [{
+        id: 'baselineLine',
+        afterDraw(chart) {
+          const {ctx, chartArea, scales} = chart;
+          const y = scales.y.getPixelForValue(bt.random_baseline);
+          ctx.save();
+          ctx.setLineDash([5, 5]);
+          ctx.strokeStyle = '#ef444480';
+          ctx.lineWidth = 1;
+          ctx.beginPath();
+          ctx.moveTo(chartArea.left, y);
+          ctx.lineTo(chartArea.right, y);
+          ctx.stroke();
+          ctx.restore();
+        }
+      }]
+    });
+  }
+}
+
+function renderCardValues(cv) {
+  const ctx = $('card-value-chart').getContext('2d');
+  new Chart(ctx, {
+    type: 'bar',
+    data: {
+      labels: cv.labels,
+      datasets: CHAIRS.map(c => ({
+        label: `Chair ${c}`, data: cv.labels.map(v => cv.chairs[c]?.[v] || 0),
+        backgroundColor: CHAIR_COLORS[c] + '99', borderColor: CHAIR_COLORS[c],
+        borderWidth: 1, borderRadius: 3,
+      }))
+    },
+    options: CHART_DEFAULTS
+  });
+}
+
+function renderFaceCards(fc) {
+  $('face-cards').innerHTML = CHAIRS.map(c => {
+    const d = fc[c];
+    return `<div class="stat-card">
+      <div class="label" style="color:${CHAIR_COLORS[c]}">Chair ${c}</div>
+      <div class="value" style="color:${CHAIR_COLORS[c]}">${d.pct}%</div>
+      <div style="font-size:11px;color:var(--text3);margin-top:4px">${d.face_cards} / ${d.total_cards} cards</div>
+    </div>`;
+  }).join('');
+}
+
+function renderSuits(s) {
+  const ctx = $('suit-chart').getContext('2d');
+  const suitColors = {'\u2660':'#e4e6f0','\u2665':'#ef4444','\u2663':'#10b981','\u2666':'#3b82f6'};
+  new Chart(ctx, {
+    type: 'bar',
+    data: {
+      labels: CHAIRS.map(c => `Chair ${c}`),
+      datasets: s.labels.map(suit => ({
+        label: suit, data: CHAIRS.map(c => s.chairs[c]?.[suit] || 0),
+        backgroundColor: (suitColors[suit] || '#8b8fa3') + '99',
+        borderColor: suitColors[suit] || '#8b8fa3',
+        borderWidth: 1, borderRadius: 3,
+      }))
+    },
+    options: CHART_DEFAULTS
+  });
+}
+
+function renderWinningCards(wc) {
+  const ctx = $('winning-cards-chart').getContext('2d');
+  // Color hearts/diamonds red, spades/clubs white
+  const colors = wc.map(c => {
+    const suit = c.card.slice(-1);
+    return (suit === '\u2665' || suit === '\u2666') ? '#ef4444' : '#e4e6f0';
+  });
+  new Chart(ctx, {
+    type: 'bar',
+    data: {
+      labels: wc.map(c => c.card),
+      datasets: [{
+        label: 'Appearances in Winning Hands',
+        data: wc.map(c => c.count),
+        backgroundColor: colors.map(c => c + '80'),
+        borderColor: colors,
+        borderWidth: 1, borderRadius: 3,
+      }]
+    },
+    options: {
+      ...CHART_DEFAULTS,
+      indexAxis: 'y',
+      plugins: { legend: { display: false } },
+    }
+  });
+}
+
+function render(data) {
+  renderPrediction(data);
+  renderMarkov1(data.markov1);
+  renderMarkov2(data.markov2);
+  renderAutocorrelation(data.autocorrelation);
+  renderChiSquared(data.chi_squared);
+  renderRunsTest(data.runs_test);
+  renderBacktest(data.backtest);
+  renderCardValues(data.card_values);
+  renderFaceCards(data.face_cards);
+  renderSuits(data.suits);
+  renderWinningCards(data.winning_cards);
+  $('loading').style.display = 'none';
+  $('main').style.display = 'block';
+}
+
+fetch('/api/predictions')
+  .then(r => r.json())
+  .then(render)
+  .catch(err => { $('loading').textContent = 'Failed to load: ' + err.message; });
+</script>
+</body>
+</html>