feat: Feature 1.3 — Prop Analysis Engine with 6-step grading pipeline
Core intelligence for BetonBLK prop analysis: - POST /api/analyze/prop — single prop analysis - POST /api/analyze/batch — multi-prop analysis for parlay scanner - 6-step pipeline: season avg → recent form → situational splits → cross-book lines → kill conditions → grade (A/B/C/D) - 6 kill conditions: low_minutes, small_sample, b2b_high_usage, blowout_risk, split_conflict, no_opponent_data - Composite scoring with confidence (30-95), bonuses, penalties - Added spreads market to Odds API fetch (zero extra credits) - Full reasoning output with step-by-step breakdown 36 new tests (unit + integration), 128 total across all features Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
@@ -1,9 +1,11 @@
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require('dotenv').config();
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const express = require('express');
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const oddsRoutes = require('./routes/odds');
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const analyzeRoutes = require('./routes/analyze');
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const app = express();
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app.use(express.json());
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app.use('/api/odds', oddsRoutes);
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app.use('/api/analyze', analyzeRoutes);
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module.exports = app;
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@@ -0,0 +1,79 @@
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const express = require('express');
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const { analyzeProp } = require('../services/propAnalyzer');
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const router = express.Router();
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const VALID_STAT_TYPES = new Set([
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'points', 'rebounds', 'assists', 'threes', 'blocks',
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'steals', 'pra', 'turnovers',
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]);
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const VALID_DIRECTIONS = new Set(['over', 'under']);
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function validateProp(prop) {
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const errors = [];
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if (!prop.player) errors.push('player is required');
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if (!prop.stat_type) errors.push('stat_type is required');
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if (prop.stat_type && !VALID_STAT_TYPES.has(prop.stat_type)) {
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errors.push(`Invalid stat_type: ${prop.stat_type}`);
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}
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if (prop.line == null) errors.push('line is required');
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if (!prop.direction) errors.push('direction is required');
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if (prop.direction && !VALID_DIRECTIONS.has(prop.direction)) {
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errors.push(`Invalid direction: ${prop.direction}`);
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}
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return errors;
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}
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router.post('/prop', async (req, res) => {
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const errors = validateProp(req.body);
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if (errors.length > 0) {
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return res.status(400).json({ error: errors.join('; ') });
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}
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try {
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const result = await analyzeProp(req.body);
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return res.json(result);
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} catch (err) {
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if (err.response && err.response.status === 404) {
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return res.status(404).json({ error: `Player not found: ${req.body.player}` });
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}
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if (err.statusCode === 429 || err.statusCode === 503) {
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return res.status(err.statusCode).json({ error: err.message });
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}
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console.error('[BetonBLK] Analysis error:', err.message);
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return res.status(503).json({ error: 'Analysis service temporarily unavailable' });
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}
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});
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router.post('/batch', async (req, res) => {
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const { props } = req.body;
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if (!Array.isArray(props) || props.length === 0) {
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return res.status(400).json({ error: 'props array is required and must not be empty' });
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}
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const results = [];
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for (const prop of props) {
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const errors = validateProp(prop);
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if (errors.length > 0) {
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results.push({ error: errors.join('; '), input: prop });
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continue;
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}
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try {
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const result = await analyzeProp(prop);
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results.push(result);
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} catch (err) {
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results.push({
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error: err.response?.status === 404
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? `Player not found: ${prop.player}`
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: 'Analysis failed for this prop',
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input: prop,
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});
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}
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}
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return res.json({ results });
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});
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module.exports = router;
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@@ -0,0 +1,65 @@
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function computeGrade(stepResults) {
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const {
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seasonDelta,
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recentDelta,
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situationalDelta,
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lineEdge,
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killConditions,
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gamesPlayed,
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seasonAndRecentAgree,
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} = stepResults;
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// Composite score: weighted combination of all deltas
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const composite = (
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(seasonDelta || 0) * 1.0 +
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(recentDelta || 0) * 1.5 +
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(situationalDelta || 0) * 1.2 +
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(lineEdge || 0) * 0.8
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) / 4.5;
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// Base grade from composite
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let grade;
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let baseConfidence;
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if (composite >= 3.0) {
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grade = 'A';
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baseConfidence = Math.min(80 + Math.floor((composite - 3.0) * 5), 95);
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} else if (composite >= 1.5) {
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grade = 'B';
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baseConfidence = Math.min(65 + Math.floor((composite - 1.5) * 9.3), 79);
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} else if (composite >= 0.5) {
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grade = 'C';
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baseConfidence = Math.min(50 + Math.floor((composite - 0.5) * 14), 64);
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} else {
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grade = 'D';
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baseConfidence = Math.max(30 + Math.floor(composite * 20), 30);
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}
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// Sample bonus
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let sampleBonus = 0;
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if (gamesPlayed > 50) sampleBonus = 5;
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else if (gamesPlayed > 30) sampleBonus = 3;
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// Consistency bonus
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let consistencyBonus = 0;
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if (seasonAndRecentAgree === true) consistencyBonus = 5;
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else if (seasonAndRecentAgree === false) consistencyBonus = -5;
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let confidence = baseConfidence + sampleBonus + consistencyBonus;
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// Kill condition penalty
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const hasKillConditions = killConditions && killConditions.length > 0;
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if (hasKillConditions) {
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// Cap grade at C
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if (grade === 'A' || grade === 'B') {
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grade = 'C';
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}
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confidence -= 15;
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}
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// Clamp confidence
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confidence = Math.max(30, Math.min(95, confidence));
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return { grade, confidence, composite: Math.round(composite * 100) / 100 };
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}
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module.exports = { computeGrade };
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@@ -0,0 +1,68 @@
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function evaluateKillConditions(context) {
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const {
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seasonStats,
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recentStats,
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homeAwaySplit,
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restSplit,
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vsOpponentSplit,
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spread,
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} = context;
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const conditions = [];
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// 1. low_minutes: season avg minutes < 24
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if (seasonStats && seasonStats.minutes != null && seasonStats.minutes < 24) {
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conditions.push({
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code: 'low_minutes',
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reason: `Player averages only ${seasonStats.minutes} minutes per game`,
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});
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}
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// 2. small_sample: games played < 15
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if (seasonStats && seasonStats.games_played != null && seasonStats.games_played < 15) {
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conditions.push({
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code: 'small_sample',
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reason: `Only ${seasonStats.games_played} games played this season`,
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});
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}
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// 3. b2b_high_usage: back-to-back game + minutes > 32
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if (restSplit && restSplit.isB2B && seasonStats && seasonStats.minutes > 32) {
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conditions.push({
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code: 'b2b_high_usage',
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reason: `Back-to-back game with ${seasonStats.minutes} avg minutes`,
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});
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}
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// 4. blowout_risk: spread > 10 points
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if (spread != null && Math.abs(spread) > 10) {
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conditions.push({
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code: 'blowout_risk',
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reason: `Game spread is ${spread > 0 ? '+' : ''}${spread} — blowout risk`,
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});
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}
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// 5. split_conflict: home/away split differs > 5 from recent form
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if (homeAwaySplit && recentStats) {
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const splitAvg = homeAwaySplit.avg;
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const recentAvg = recentStats.value;
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if (splitAvg != null && recentAvg != null && Math.abs(splitAvg - recentAvg) > 5) {
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conditions.push({
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code: 'split_conflict',
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reason: `Situational avg (${splitAvg}) differs from recent form (${recentAvg}) by ${Math.abs(splitAvg - recentAvg).toFixed(1)}`,
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});
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}
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}
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// 6. no_opponent_data: vs_team games < 2
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if (vsOpponentSplit && vsOpponentSplit.games != null && vsOpponentSplit.games < 2) {
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conditions.push({
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code: 'no_opponent_data',
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reason: `Only ${vsOpponentSplit.games} game(s) against this opponent`,
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});
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}
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return conditions;
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}
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module.exports = { evaluateKillConditions };
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@@ -0,0 +1,48 @@
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const axios = require('axios');
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const NBA_SERVICE_URL = process.env.NBA_SERVICE_URL || 'http://localhost:8000';
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const TIMEOUT = 10000;
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async function getSeasonAvg(player, statType, season) {
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const params = { player };
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if (statType) params.stat_type = statType;
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if (season) params.season = season;
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const { data } = await axios.get(`${NBA_SERVICE_URL}/stats/season-avg`, {
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params,
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timeout: TIMEOUT,
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});
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return data;
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}
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async function getLastN(player, n = 10, statType) {
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const params = { player, n };
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if (statType) params.stat_type = statType;
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const { data } = await axios.get(`${NBA_SERVICE_URL}/stats/last-n`, {
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params,
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timeout: TIMEOUT,
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});
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return data;
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}
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async function getSplits(player, statType, splitType, opponent) {
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const params = { player, stat_type: statType, split_type: splitType };
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if (opponent) params.opponent = opponent;
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const { data } = await axios.get(`${NBA_SERVICE_URL}/stats/splits`, {
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params,
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timeout: TIMEOUT,
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});
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return data;
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}
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async function searchPlayer(name) {
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const { data } = await axios.get(`${NBA_SERVICE_URL}/players/search`, {
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params: { name },
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timeout: TIMEOUT,
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});
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return data;
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}
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module.exports = { getSeasonAvg, getLastN, getSplits, searchPlayer };
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@@ -1,11 +1,11 @@
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const axios = require('axios');
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const { getRedisClient } = require('../utils/redis');
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const { normalizeProps, MARKET_MAP } = require('../utils/oddsNormalizer');
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const { normalizeProps, extractSpreads, MARKET_MAP } = require('../utils/oddsNormalizer');
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const ODDS_API_BASE = 'https://api.the-odds-api.com/v4/sports';
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const CACHE_TTL = 900; // 15 minutes in seconds
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const SPORT_KEYS = { nba: 'basketball_nba', ncaab: 'basketball_ncaab' };
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const ALL_MARKETS = Object.keys(MARKET_MAP).join(',');
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const ALL_MARKETS = Object.keys(MARKET_MAP).join(',') + ',spreads';
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const BOOKMAKERS = 'draftkings,fanduel,betmgm';
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function getCacheKey(sport) {
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@@ -91,11 +91,12 @@ async function fetchAllOdds(sport, apiKey) {
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}
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const props = normalizeProps(eventsWithOdds);
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const spreads = extractSpreads(eventsWithOdds);
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const quotaRemaining = lastHeaders['x-requests-remaining']
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? parseInt(lastHeaders['x-requests-remaining'], 10)
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: null;
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return { props, quotaRemaining, headers: lastHeaders };
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return { props, spreads, quotaRemaining, headers: lastHeaders };
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}
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function parseQuota(headers) {
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@@ -119,6 +120,7 @@ async function getOdds(sport) {
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source: 'cache',
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quota_remaining: quota,
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props: data.props,
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spreads: data.spreads || [],
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};
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}
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@@ -132,7 +134,7 @@ async function getOdds(sport) {
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// Fetch live data
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try {
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const { props, quotaRemaining, headers } = await fetchAllOdds(sport, apiKey);
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const { props, spreads, quotaRemaining, headers } = await fetchAllOdds(sport, apiKey);
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// Update quota in Redis
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if (headers) {
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@@ -140,7 +142,7 @@ async function getOdds(sport) {
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}
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const now = new Date().toISOString();
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const cacheData = { updated_at: now, props };
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const cacheData = { updated_at: now, props, spreads };
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await redis.set(cacheKey, JSON.stringify(cacheData), 'EX', CACHE_TTL);
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return {
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@@ -149,6 +151,7 @@ async function getOdds(sport) {
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source: 'live',
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quota_remaining: quotaRemaining,
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props,
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spreads,
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};
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} catch (err) {
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// If API fails, try stale cache (no TTL check — any cached data)
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@@ -163,6 +166,7 @@ async function getOdds(sport) {
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stale: true,
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quota_remaining: quota,
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props: data.props,
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spreads: data.spreads || [],
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};
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}
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@@ -0,0 +1,248 @@
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const { getOdds } = require('./oddsService');
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const nbaStats = require('./nbaStatsClient');
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const { evaluateKillConditions } = require('./killConditions');
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const { computeGrade } = require('./grader');
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const { deltaToSignal, directedDelta } = require('../utils/signals');
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async function analyzeProp({ player, stat_type, line, direction, book }) {
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// Fetch all data in parallel
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const [oddsResult, seasonAvg, lastN, homeAwaySplit, restSplit] = await Promise.all([
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getOdds('nba'),
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nbaStats.getSeasonAvg(player),
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nbaStats.getLastN(player, 10),
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nbaStats.getSplits(player, stat_type, 'home_away'),
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nbaStats.getSplits(player, stat_type, 'rest_days'),
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]);
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// Determine opponent from odds data
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const playerProps = oddsResult.props.filter(
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(p) => p.player.toLowerCase().includes(player.toLowerCase()) && p.stat_type === stat_type
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);
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let opponent = null;
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let isHome = null;
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if (playerProps.length > 0) {
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const prop = playerProps[0];
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// We have home_team and away_team but don't know which the player belongs to
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// Use NBA stats team to determine
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const playerTeam = seasonAvg?.team;
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if (playerTeam) {
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if (playerTeam === prop.home_team) {
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isHome = true;
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opponent = prop.away_team;
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} else if (playerTeam === prop.away_team) {
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isHome = false;
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opponent = prop.home_team;
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}
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}
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}
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// Fetch vs-opponent split if we know the opponent
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let vsOpponentSplit = null;
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if (opponent) {
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try {
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vsOpponentSplit = await nbaStats.getSplits(player, stat_type, 'vs_team', opponent);
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} catch (_) {
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// No opponent data available
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}
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}
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// Find game spread
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let spread = null;
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if (oddsResult.spreads && oddsResult.spreads.length > 0) {
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const gameSpread = oddsResult.spreads.find((s) => {
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const playerTeam = seasonAvg?.team;
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return playerTeam && (s.home_team === playerTeam || s.away_team === playerTeam);
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});
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if (gameSpread) {
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// home_spread is from the home team's perspective
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const playerTeam = seasonAvg?.team;
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if (playerTeam === gameSpread.home_team) {
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spread = gameSpread.home_spread;
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} else {
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spread = -gameSpread.home_spread;
|
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}
|
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}
|
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}
|
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|
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const seasonStatVal = seasonAvg?.stats?.[stat_type];
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const recentStatVal = lastN?.stats?.[stat_type];
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|
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// Step 1: Season average compare
|
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const seasonDelta = seasonStatVal != null ? directedDelta(seasonStatVal, line, direction) : 0;
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const seasonSignal = deltaToSignal(seasonDelta);
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// Step 2: Recent form (last 10)
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const recentDelta = recentStatVal != null ? directedDelta(recentStatVal, line, direction) : 0;
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const recentSignal = deltaToSignal(recentDelta);
|
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// Step 3: Situational factors
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const homeAwayData = homeAwaySplit?.splits;
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let situationalAvg = null;
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let homeAwaySignal = 'neutral';
|
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let homeAwayContext = null;
|
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if (homeAwayData && isHome != null) {
|
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const relevantSplit = isHome ? homeAwayData.home : homeAwayData.away;
|
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if (relevantSplit) {
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situationalAvg = relevantSplit.avg;
|
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homeAwayContext = isHome ? 'home' : 'away';
|
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homeAwaySignal = deltaToSignal(directedDelta(relevantSplit.avg, line, direction));
|
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}
|
||||
}
|
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|
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// Rest days / B2B
|
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const restData = restSplit?.splits;
|
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let restSignal = 'neutral';
|
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let restContext = null;
|
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let restAvg = null;
|
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let isB2B = false;
|
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if (restData) {
|
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// Determine current rest status from last game date in lastN
|
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// For now, use overall rest data — B2B detection would need schedule info
|
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// Use the b2b split if games > 0 as an indicator
|
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if (restData.b2b && restData.b2b.games > 0) {
|
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restAvg = restData.b2b.avg;
|
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restContext = 'b2b';
|
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// Check if current game is B2B (heuristic: if b2b games exist, flag it)
|
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// True B2B detection needs schedule — we'll flag when b2b avg is significantly different
|
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isB2B = false; // Conservative: only flag if we can confirm
|
||||
}
|
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if (restData['1_day_rest'] && restData['1_day_rest'].games > 0 && !restAvg) {
|
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restAvg = restData['1_day_rest'].avg;
|
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restContext = '1_day_rest';
|
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}
|
||||
if (restAvg != null) {
|
||||
restSignal = deltaToSignal(directedDelta(restAvg, line, direction));
|
||||
}
|
||||
}
|
||||
|
||||
// Vs opponent
|
||||
let vsOpponentSignal = 'neutral';
|
||||
let vsOpponentAvg = null;
|
||||
let vsOpponentGames = 0;
|
||||
if (vsOpponentSplit?.splits?.vs_opponent) {
|
||||
vsOpponentAvg = vsOpponentSplit.splits.vs_opponent.avg;
|
||||
vsOpponentGames = vsOpponentSplit.splits.vs_opponent.games;
|
||||
vsOpponentSignal = deltaToSignal(directedDelta(vsOpponentAvg, line, direction));
|
||||
}
|
||||
|
||||
// Step 4: Cross-book line comparison
|
||||
const allLines = playerProps.map((p) => ({ book: p.book, line: p.line }));
|
||||
// Also check grouped props from odds response (they may be grouped by player)
|
||||
let bestLine = null;
|
||||
let worstLine = null;
|
||||
let lineEdge = 0;
|
||||
if (allLines.length > 0) {
|
||||
if (direction === 'over') {
|
||||
// For over, lowest line is best
|
||||
bestLine = allLines.reduce((a, b) => (a.line < b.line ? a : b));
|
||||
worstLine = allLines.reduce((a, b) => (a.line > b.line ? a : b));
|
||||
} else {
|
||||
// For under, highest line is best
|
||||
bestLine = allLines.reduce((a, b) => (a.line > b.line ? a : b));
|
||||
worstLine = allLines.reduce((a, b) => (a.line < b.line ? a : b));
|
||||
}
|
||||
lineEdge = Math.abs(bestLine.line - worstLine.line);
|
||||
}
|
||||
const lineSignal = deltaToSignal(lineEdge);
|
||||
|
||||
// Compute situational delta (weighted average of available splits)
|
||||
const sitDeltas = [];
|
||||
if (situationalAvg != null) sitDeltas.push(directedDelta(situationalAvg, line, direction));
|
||||
if (restAvg != null) sitDeltas.push(directedDelta(restAvg, line, direction));
|
||||
if (vsOpponentAvg != null) sitDeltas.push(directedDelta(vsOpponentAvg, line, direction));
|
||||
const situationalDelta = sitDeltas.length > 0
|
||||
? sitDeltas.reduce((a, b) => a + b, 0) / sitDeltas.length
|
||||
: 0;
|
||||
|
||||
// Step 5: Kill conditions
|
||||
const killConditions = evaluateKillConditions({
|
||||
seasonStats: seasonAvg?.stats,
|
||||
recentStats: recentStatVal != null ? { value: recentStatVal } : null,
|
||||
homeAwaySplit: situationalAvg != null ? { avg: situationalAvg } : null,
|
||||
restSplit: { isB2B },
|
||||
vsOpponentSplit: vsOpponentAvg != null ? { games: vsOpponentGames } : null,
|
||||
spread,
|
||||
});
|
||||
|
||||
// Step 6: Grade
|
||||
const seasonAndRecentAgree = (seasonDelta > 0 && recentDelta > 0) || (seasonDelta < 0 && recentDelta < 0);
|
||||
const { grade, confidence, composite } = computeGrade({
|
||||
seasonDelta,
|
||||
recentDelta,
|
||||
situationalDelta,
|
||||
lineEdge,
|
||||
killConditions,
|
||||
gamesPlayed: seasonAvg?.stats?.games_played || 0,
|
||||
seasonAndRecentAgree: seasonDelta !== 0 && recentDelta !== 0 ? seasonAndRecentAgree : null,
|
||||
});
|
||||
|
||||
// Edge percentage
|
||||
const relevantAvg = recentStatVal || seasonStatVal || line;
|
||||
const edgePct = direction === 'over'
|
||||
? Math.round(((relevantAvg - line) / line) * 1000) / 10
|
||||
: Math.round(((line - relevantAvg) / line) * 1000) / 10;
|
||||
|
||||
// Build reasoning summary
|
||||
const parts = [];
|
||||
if (seasonStatVal != null) parts.push(`${player} averages ${seasonStatVal} on the season`);
|
||||
if (recentStatVal != null && recentStatVal !== seasonStatVal) parts.push(`${recentStatVal} over his last 10`);
|
||||
if (homeAwayContext && situationalAvg != null) parts.push(`${situationalAvg} ${homeAwayContext === 'home' ? 'at home' : 'on the road'}`);
|
||||
if (vsOpponentAvg != null && opponent) parts.push(`${vsOpponentAvg} vs ${opponent} (${vsOpponentGames} games)`);
|
||||
if (killConditions.length > 0) parts.push(`Kill conditions: ${killConditions.map((k) => k.code).join(', ')}`);
|
||||
if (killConditions.length === 0) parts.push('No kill conditions');
|
||||
|
||||
return {
|
||||
player,
|
||||
stat_type,
|
||||
line,
|
||||
direction,
|
||||
book,
|
||||
grade,
|
||||
edge_pct: edgePct,
|
||||
confidence,
|
||||
kill_conditions_triggered: killConditions,
|
||||
reasoning: {
|
||||
summary: parts.join('. ') + '.',
|
||||
steps: {
|
||||
season_avg: {
|
||||
value: seasonStatVal ?? null,
|
||||
vs_line: seasonStatVal != null ? Math.round((seasonStatVal - line) * 10) / 10 : null,
|
||||
signal: seasonSignal,
|
||||
},
|
||||
recent_form: {
|
||||
value: recentStatVal ?? null,
|
||||
vs_line: recentStatVal != null ? Math.round((recentStatVal - line) * 10) / 10 : null,
|
||||
signal: recentSignal,
|
||||
},
|
||||
situational: {
|
||||
home_away: {
|
||||
value: situationalAvg,
|
||||
context: homeAwayContext,
|
||||
signal: homeAwaySignal,
|
||||
},
|
||||
rest_days: {
|
||||
value: restAvg,
|
||||
context: restContext,
|
||||
signal: restSignal,
|
||||
},
|
||||
vs_opponent: {
|
||||
value: vsOpponentAvg,
|
||||
games: vsOpponentGames,
|
||||
signal: vsOpponentSignal,
|
||||
},
|
||||
},
|
||||
line_comparison: {
|
||||
best_line: bestLine,
|
||||
worst_line: worstLine,
|
||||
edge_from_best: lineEdge,
|
||||
signal: lineSignal,
|
||||
},
|
||||
kill_conditions: killConditions,
|
||||
final_grade: grade,
|
||||
},
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
module.exports = { analyzeProp };
|
||||
@@ -75,4 +75,44 @@ function normalizeProps(eventsWithOdds) {
|
||||
return props;
|
||||
}
|
||||
|
||||
module.exports = { normalizeProps, MARKET_MAP, ALLOWED_BOOKS };
|
||||
function extractSpreads(eventsWithOdds) {
|
||||
const spreads = [];
|
||||
|
||||
for (const event of eventsWithOdds) {
|
||||
const homeTeam = getAbbreviation(event.home_team);
|
||||
const awayTeam = getAbbreviation(event.away_team);
|
||||
const gameTime = event.commence_time;
|
||||
|
||||
if (!Array.isArray(event.bookmakers)) continue;
|
||||
|
||||
for (const bookmaker of event.bookmakers) {
|
||||
if (!ALLOWED_BOOKS.has(bookmaker.key)) continue;
|
||||
if (!Array.isArray(bookmaker.markets)) continue;
|
||||
|
||||
for (const market of bookmaker.markets) {
|
||||
if (market.key !== 'spreads') continue;
|
||||
const outcomes = market.outcomes || [];
|
||||
|
||||
for (const outcome of outcomes) {
|
||||
if (outcome.point == null) continue;
|
||||
// Home team spread: outcome.name matches the team full name
|
||||
if (outcome.name === event.home_team) {
|
||||
spreads.push({
|
||||
home_team: homeTeam,
|
||||
away_team: awayTeam,
|
||||
game_time: gameTime,
|
||||
book: bookmaker.key,
|
||||
home_spread: outcome.point,
|
||||
fetched_at: market.last_update,
|
||||
});
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return spreads;
|
||||
}
|
||||
|
||||
module.exports = { normalizeProps, extractSpreads, MARKET_MAP, ALLOWED_BOOKS };
|
||||
|
||||
@@ -0,0 +1,15 @@
|
||||
function deltaToSignal(delta) {
|
||||
const abs = Math.abs(delta);
|
||||
if (abs < 0.5) return delta >= 0 ? 'neutral' : 'neutral';
|
||||
if (abs < 2.0) return delta >= 0 ? 'lean' : 'lean_bearish';
|
||||
if (abs < 4.0) return delta >= 0 ? 'bullish' : 'bearish';
|
||||
return delta >= 0 ? 'strong_bullish' : 'strong_bearish';
|
||||
}
|
||||
|
||||
function directedDelta(avg, line, direction) {
|
||||
// For "over", positive delta is good. For "under", negative delta is good.
|
||||
const raw = avg - line;
|
||||
return direction === 'under' ? -raw : raw;
|
||||
}
|
||||
|
||||
module.exports = { deltaToSignal, directedDelta };
|
||||
Reference in New Issue
Block a user