add semi-win scoring (0.5 pts for 2nd pick) and whale/public bet recommendations
This commit is contained in:
48
app/db.py
48
app/db.py
@@ -1123,7 +1123,8 @@ def _backtest_theories(winners):
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return {"error": "Not enough data for backtesting"}
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theories = ["base_rate", "markov_1", "markov_2", "recent_20", "streak", "combined"]
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correct = {t: 0 for t in theories}
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full_hits = {t: 0 for t in theories}
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semi_hits = {t: 0 for t in theories}
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total_tested = 0
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rolling = {t: [] for t in theories} # rolling accuracy over last 200
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@@ -1135,24 +1136,24 @@ def _backtest_theories(winners):
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total_h = len(history)
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# Base rate
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base = {c: history.count(c) / total_h for c in CHAIR_LABELS}
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base_pick = max(CHAIR_LABELS, key=lambda c: base[c])
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base_ranked = sorted(CHAIR_LABELS, key=lambda c: base[c], reverse=True)
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# Markov-1
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m1, _ = _markov_matrix_1(history)
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last = history[-1]
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m1_probs = m1.get(last, {c: 1 / 3 for c in CHAIR_LABELS})
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m1_pick = max(CHAIR_LABELS, key=lambda c: m1_probs.get(c, 0))
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m1_ranked = sorted(CHAIR_LABELS, key=lambda c: m1_probs.get(c, 0), reverse=True)
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# Markov-2
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m2, _ = _markov_matrix_2(history)
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key2 = f"{history[-2]}{history[-1]}"
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m2_probs = m2.get(key2, {c: 1 / 3 for c in CHAIR_LABELS})
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m2_pick = max(CHAIR_LABELS, key=lambda c: m2_probs.get(c, 0))
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m2_ranked = sorted(CHAIR_LABELS, key=lambda c: m2_probs.get(c, 0), reverse=True)
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# Recent-20
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recent = history[-20:] if len(history) >= 20 else history
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rec = {c: recent.count(c) / len(recent) for c in CHAIR_LABELS}
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rec_pick = max(CHAIR_LABELS, key=lambda c: rec[c])
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rec_ranked = sorted(CHAIR_LABELS, key=lambda c: rec[c], reverse=True)
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# Streak
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streak_chair = history[-1]
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@@ -1173,7 +1174,7 @@ def _backtest_theories(winners):
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streak_probs = {c: streak_probs[c] / s_total for c in CHAIR_LABELS}
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else:
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streak_probs = {c: 1 / 3 for c in CHAIR_LABELS}
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streak_pick = max(CHAIR_LABELS, key=lambda c: streak_probs[c])
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streak_ranked = sorted(CHAIR_LABELS, key=lambda c: streak_probs[c], reverse=True)
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# Combined Bayesian
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combined = {c: 0 for c in CHAIR_LABELS}
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@@ -1182,19 +1183,28 @@ def _backtest_theories(winners):
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for sig_name, weight in weights.items():
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for c in CHAIR_LABELS:
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combined[c] += weight * signals[sig_name].get(c, 1 / 3)
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combined_pick = max(CHAIR_LABELS, key=lambda c: combined[c])
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combined_ranked = sorted(CHAIR_LABELS, key=lambda c: combined[c], reverse=True)
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picks = {
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"base_rate": base_pick, "markov_1": m1_pick, "markov_2": m2_pick,
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"recent_20": rec_pick, "streak": streak_pick, "combined": combined_pick,
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ranked = {
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"base_rate": base_ranked, "markov_1": m1_ranked, "markov_2": m2_ranked,
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"recent_20": rec_ranked, "streak": streak_ranked, "combined": combined_ranked,
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}
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for t in theories:
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hit = 1 if picks[t] == actual else 0
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if picks[t] == actual:
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correct[t] += 1
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rolling[t].append(hit)
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pick = ranked[t][0]
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second = ranked[t][1]
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if pick == actual:
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full_hits[t] += 1
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rolling[t].append(1.0)
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elif second == actual:
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semi_hits[t] += 1
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rolling[t].append(0.5)
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else:
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rolling[t].append(0.0)
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accuracy = {t: round(correct[t] / total_tested * 100, 2) if total_tested else 0 for t in theories}
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accuracy = {
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t: round((full_hits[t] + semi_hits[t] * 0.5) / total_tested * 100, 2) if total_tested else 0
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for t in theories
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}
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# Rolling accuracy over last 200 games
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window = 200
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@@ -1212,6 +1222,8 @@ def _backtest_theories(winners):
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return {
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"total_tested": total_tested,
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"accuracy": accuracy,
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"full_hits": {t: full_hits[t] for t in theories},
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"semi_hits": {t: semi_hits[t] for t in theories},
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"rolling_accuracy": rolling_accuracy,
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"random_baseline": 33.33,
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}
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@@ -1230,12 +1242,16 @@ def _last_n_predictions(winners, n=20):
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m1, _ = _markov_matrix_1(history)
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m2, _ = _markov_matrix_2(history)
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pred, _ = _bayesian_prediction(history, m1, m2)
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predicted = max(CHAIR_LABELS, key=lambda c: pred[c])
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ranked = sorted(CHAIR_LABELS, key=lambda c: pred[c], reverse=True)
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predicted = ranked[0]
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second_predicted = ranked[1]
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results.append({
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"index": i,
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"predicted": predicted,
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"second_predicted": second_predicted,
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"actual": actual,
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"correct": predicted == actual,
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"semi_correct": predicted != actual and second_predicted == actual,
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"probs": {c: round(pred[c], 4) for c in CHAIR_LABELS},
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})
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return results
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@@ -88,7 +88,7 @@ body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-
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background: var(--surface); border: 1px solid var(--border); border-radius: 10px;
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padding: 18px; margin-bottom: 16px;
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}
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.advisor-grid { display: grid; grid-template-columns: 1fr 1fr 1fr; gap: 16px; }
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.advisor-grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(140px, 1fr)); gap: 16px; }
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.advisor-item { text-align: center; }
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.advisor-item .adv-label { font-size: 11px; color: var(--text3); font-weight: 600; text-transform: uppercase; margin-bottom: 4px; }
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.advisor-item .adv-value { font-size: 20px; font-weight: 800; }
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@@ -163,6 +163,7 @@ body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-
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.pred-history th, .pred-history td { padding: 7px 10px; text-align: center; border-bottom: 1px solid var(--border); }
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.pred-history th { color: var(--text2); font-weight: 600; text-transform: uppercase; font-size: 11px; background: var(--surface2); position: sticky; top: 0; }
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.pred-history .correct { color: var(--green); }
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.pred-history .semi { color: #f59e0b; }
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.pred-history .wrong { color: var(--red); }
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.pred-history .winner-cell { font-weight: 800; }
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.prob-bar { display: inline-block; height: 6px; border-radius: 3px; vertical-align: middle; }
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@@ -173,6 +174,7 @@ body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-
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}
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.result-flash.show { display: block; }
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.result-flash.win { background: rgba(16,185,129,0.15); border: 1px solid var(--green); color: var(--green); }
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.result-flash.semi { background: rgba(245,158,11,0.15); border: 1px solid #f59e0b; color: #f59e0b; }
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.result-flash.loss { background: rgba(239,68,68,0.15); border: 1px solid var(--red); color: var(--red); }
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@keyframes flashIn { from { opacity: 0; transform: translateY(-10px); } to { opacity: 1; transform: translateY(0); } }
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@@ -260,7 +262,7 @@ body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-
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<div class="section-title">Last 20 Predictions vs Actual</div>
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<div class="panel" style="max-height:500px;overflow-y:auto">
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<table class="pred-history" id="pred-history">
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<thead><tr><th>Game</th><th>Predicted</th><th>P(A)</th><th>P(B)</th><th>P(C)</th><th>Actual</th><th>Result</th></tr></thead>
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<thead><tr><th>Game</th><th>Predicted</th><th>2nd Pick</th><th>P(A)</th><th>P(B)</th><th>P(C)</th><th>Actual</th><th>Result</th></tr></thead>
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<tbody></tbody>
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</table>
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</div>
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@@ -376,6 +378,7 @@ let predictionData = null;
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let liveBets = {A: 0, B: 0, C: 0};
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let liveGameNo = null;
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let currentPrediction = null;
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let currentSecondPrediction = null;
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let roundBettors = {};
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// Track whale-pick wins and public-pick wins from round results we witness
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let crowdTracker = {whaleCorrect: 0, publicCorrect: 0, roundsSeen: 0};
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@@ -399,6 +402,7 @@ function renderPrediction(data) {
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const ranked = CHAIRS.slice().sort((a, b) => data.prediction[b] - data.prediction[a]);
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const best = ranked[0], second = ranked[1];
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currentPrediction = best;
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currentSecondPrediction = second;
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$('pred-game-label').textContent = data.total_games ? `(based on ${data.total_games} games)` : '';
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const pot = liveBets.A + liveBets.B + liveBets.C;
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@@ -442,10 +446,33 @@ function renderPrediction(data) {
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renderBetAdvisor(data, pot);
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}
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function computeBetRecommendations() {
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const bettors = Object.values(roundBettors);
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if (bettors.length < 2) return null;
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const sorted = bettors.slice().sort((a, b) => b.total - a.total);
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const whales = sorted.slice(0, 5);
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const pub = sorted.slice(5);
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const whaleAvg = {A: 0, B: 0, C: 0};
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const pubAvg = {A: 0, B: 0, C: 0};
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if (whales.length > 0) {
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for (const w of whales) for (const c of CHAIRS) whaleAvg[c] += w.chairs[c] || 0;
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for (const c of CHAIRS) whaleAvg[c] = Math.round(whaleAvg[c] / whales.length);
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}
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if (pub.length > 0) {
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for (const p of pub) for (const c of CHAIRS) pubAvg[c] += p.chairs[c] || 0;
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for (const c of CHAIRS) pubAvg[c] = Math.round(pubAvg[c] / pub.length);
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}
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return { whaleAvg, pubAvg, whaleCount: whales.length, pubCount: pub.length };
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}
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function renderBetAdvisor(data, pot) {
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const el = $('advisor-content');
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const ranked = CHAIRS.slice().sort((a, b) => data.prediction[b] - data.prediction[a]);
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const best = ranked[0];
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const second = ranked[1];
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const pBest = data.prediction[best];
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const ev = pBest * PAYOUT - 1;
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@@ -462,6 +489,30 @@ function renderBetAdvisor(data, pot) {
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const highWinPct = brTotal > 0 ? ((br.high || 0) / brTotal * 100).toFixed(0) : '?';
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const evClass = ev >= 0 ? 'ev-positive' : 'ev-negative';
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// Whale & public bet recommendations
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const recs = computeBetRecommendations();
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let whaleHtml = '', pubHtml = '';
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if (recs) {
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const wPrimary = recs.whaleAvg[best] || 0;
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const wSecondary = Math.round(wPrimary / 2);
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whaleHtml = `
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<div class="advisor-item">
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<div class="adv-label">Whale Avg Bet</div>
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<div class="adv-value" style="color:${CHAIR_COLORS[best]}">${fmt(wPrimary)}</div>
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<div class="adv-note">on ${best} (primary) · ${fmt(wSecondary)} on ${second} (2nd)</div>
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</div>`;
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const pPrimary = recs.pubAvg[best] || 0;
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const pSecondary = Math.round(pPrimary / 2);
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pubHtml = `
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<div class="advisor-item">
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<div class="adv-label">Public Avg Bet</div>
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<div class="adv-value" style="color:${CHAIR_COLORS[best]}">${fmt(pPrimary)}</div>
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<div class="adv-note">on ${best} (primary) · ${fmt(pSecondary)} on ${second} (2nd)</div>
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</div>`;
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}
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el.innerHTML = `
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<div class="advisor-item">
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<div class="adv-label">Best Chair</div>
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@@ -478,6 +529,8 @@ function renderBetAdvisor(data, pot) {
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<div class="adv-value">${lowWinPct}% low</div>
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<div class="adv-note">Lowest-bet chair wins ${lowWinPct}% · Highest wins ${highWinPct}%</div>
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</div>
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${whaleHtml}
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${pubHtml}
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`;
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}
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@@ -582,27 +635,32 @@ function renderCrowdStats(data) {
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function renderLast20(predictions) {
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const tbody = $('pred-history').querySelector('tbody');
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if (!predictions || predictions.length === 0) {
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tbody.innerHTML = '<tr><td colspan="7" style="color:var(--text3)">Not enough data</td></tr>';
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tbody.innerHTML = '<tr><td colspan="8" style="color:var(--text3)">Not enough data</td></tr>';
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return;
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}
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const correctCount = predictions.filter(p => p.correct).length;
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const fullHits = predictions.filter(p => p.correct).length;
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const semiHits = predictions.filter(p => p.semi_correct).length;
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const score = fullHits + semiHits * 0.5;
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tbody.innerHTML = predictions.slice().reverse().map(p => {
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const maxProb = Math.max(p.probs.A, p.probs.B, p.probs.C);
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const resultClass = p.correct ? 'correct' : (p.semi_correct ? 'semi' : 'wrong');
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const resultLabel = p.correct ? 'HIT' : (p.semi_correct ? 'SEMI' : 'MISS');
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return `<tr>
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<td style="font-weight:700">#${p.game_no}</td>
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<td class="winner-cell" style="color:${CHAIR_COLORS[p.predicted]}">${p.predicted}</td>
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<td style="color:${CHAIR_COLORS[p.second_predicted]}">${p.second_predicted}</td>
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${CHAIRS.map(c => {
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const w = p.probs[c] / maxProb * 40;
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return `<td><span class="prob-bar" style="width:${w}px;background:${CHAIR_COLORS[c]}"></span> ${pct(p.probs[c])}</td>`;
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}).join('')}
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<td class="winner-cell" style="color:${CHAIR_COLORS[p.actual]}">${p.actual}</td>
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<td class="${p.correct ? 'correct' : 'wrong'}" style="font-weight:700">${p.correct ? 'HIT' : 'MISS'}</td>
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<td class="${resultClass}" style="font-weight:700">${resultLabel}</td>
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</tr>`;
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}).join('') +
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`<tr style="border-top:2px solid var(--border);font-weight:700">
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<td colspan="5" style="text-align:right;color:var(--text2)">Accuracy (last ${predictions.length})</td>
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<td colspan="2" style="color:${correctCount/predictions.length > 1/3 ? 'var(--green)' : 'var(--red)'}">
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${(correctCount/predictions.length*100).toFixed(1)}% (${correctCount}/${predictions.length})
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<td colspan="6" style="text-align:right;color:var(--text2)">Accuracy (last ${predictions.length})</td>
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<td colspan="2" style="color:${score/predictions.length > 1/3 ? 'var(--green)' : 'var(--red)'}">
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${(score/predictions.length*100).toFixed(1)}% (${score}/${predictions.length})
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</td>
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</tr>`;
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}
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@@ -686,11 +744,14 @@ function renderRunsTest(runs) {
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function renderBacktest(bt) {
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if (bt.error) { $('backtest-cards').innerHTML = `<div style="color:var(--text2)">${bt.error}</div>`; return; }
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const names = {base_rate:'Base Rate',markov_1:'Markov-1',markov_2:'Markov-2',recent_20:'Recent 20',streak:'Streak',combined:'Combined'};
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$('backtest-cards').innerHTML = Object.entries(bt.accuracy).map(([key, acc]) =>
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`<div class="bt-card"><div class="bt-name">${names[key]||key}</div>
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$('backtest-cards').innerHTML = Object.entries(bt.accuracy).map(([key, acc]) => {
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const fh = bt.full_hits?.[key] ?? '?';
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const sh = bt.semi_hits?.[key] ?? '?';
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return `<div class="bt-card"><div class="bt-name">${names[key]||key}</div>
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<div class="bt-acc ${acc > bt.random_baseline ? 'above' : 'below'}">${acc}%</div>
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<div style="font-size:10px;color:var(--text3);margin-top:4px">vs ${bt.random_baseline}% random</div></div>`
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).join('');
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<div style="font-size:10px;color:var(--text3);margin-top:4px">${fh} hits + ${sh} semi</div>
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<div style="font-size:10px;color:var(--text3)">vs ${bt.random_baseline}% random</div></div>`;
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}).join('');
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if (bt.rolling_accuracy) {
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const ctx = $('backtest-chart').getContext('2d');
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const colors = {base_rate:'#8b8fa3',markov_1:'#3b82f6',markov_2:'#ec4899',recent_20:'#f59e0b',streak:'#10b981',combined:'#6c5ce7'};
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@@ -845,6 +906,7 @@ function trackBet(bet) {
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rb.chairs[bet.chair_name] = (rb.chairs[bet.chair_name] || 0) + bet.bet_amount;
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rb.total += bet.bet_amount;
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renderWhaleTrend();
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if (predictionData) renderBetAdvisor(predictionData, liveBets.A + liveBets.B + liveBets.C);
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}
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function updatePredCardBets() {
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@@ -885,8 +947,11 @@ function onRoundResult(data) {
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if (currentPrediction) {
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const hit = currentPrediction === winner;
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flash.className = `result-flash show ${hit ? 'win' : 'loss'}`;
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flash.innerHTML = `Round #${data.game_no}: Predicted <b>${currentPrediction}</b> \u2014 <b>${winner}</b> won. ${hit ? 'HIT!' : 'MISS'}` +
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const semiHit = !hit && currentSecondPrediction === winner;
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const cls = hit ? 'win' : (semiHit ? 'semi' : 'loss');
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const label = hit ? 'HIT!' : (semiHit ? 'SEMI-WIN (2nd pick)' : 'MISS');
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flash.className = `result-flash show ${cls}`;
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flash.innerHTML = `Round #${data.game_no}: Predicted <b>${currentPrediction}</b> \u2014 <b>${winner}</b> won. ${label}` +
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(extra.length ? ` \u00b7 ${extra.join(' \u00b7 ')}` : '');
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}
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Block a user