Files
vyndr/src/services/parlayScanService.js
T
builtbykev 411cb6f196 feat: Feature 2.1 — Parlay Scan with correlation detection + monetization
POST /api/scan/parlay — authenticated parlay analysis:
- Supabase JWT auth middleware (auth.getUser verification)
- 5 correlation types detected between legs (same_game, same_team,
  same_player_conflicting, positive_correlation, blowout_cascade)
- Overall parlay grading (A/B/C/D) with correlation penalty adjustments
- Free tier: 5 scans/month, atomic scan count increment
- Scan 5: full analysis + personalized upgrade pitch
- Scan 6+: 403 block with upgrade pitch
- Pitch personalization from scan history (top stats, grades, tier rec)
- DB writes: picks + scan_sessions per scan

30 new tests, 158 total (131 Node.js + 27 Python), all passing

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-21 12:45:15 -04:00

174 lines
5.2 KiB
JavaScript

const { analyzeProp } = require('./propAnalyzer');
const { getOdds } = require('./oddsService');
const { detectCorrelations } = require('./correlationEngine');
const { gradeParlayFromLegs } = require('./parlayGrader');
const { generateUpgradePitch } = require('./upgradePitch');
const { getSupabaseServiceClient } = require('../utils/supabase');
async function scanParlay(user, legs) {
const supabase = getSupabaseServiceClient();
const isFree = user.tier === 'free';
// Scan count check (atomic for free tier)
if (isFree) {
if (user.scan_count >= 5) {
// Already exhausted — return 403 with pitch
const pitch = await generateUpgradePitch(supabase, user.id, null);
return {
blocked: true,
scan_count: user.scan_count,
scans_remaining: 0,
upgrade_pitch: pitch,
};
}
}
// Analyze all legs
const legResults = [];
for (const leg of legs) {
const result = await analyzeProp(leg);
legResults.push(result);
}
// Fetch odds data for correlation detection (spreads, game context)
let spreads = [];
try {
const oddsData = await getOdds('nba');
spreads = oddsData.spreads || [];
// Attach game context to leg results for correlation detection
for (const leg of legResults) {
const matchingProps = (oddsData.props || []).filter(
(p) => p.player.toLowerCase().includes(leg.player.toLowerCase())
);
if (matchingProps.length > 0) {
const prop = matchingProps[0];
leg._gameTime = prop.game_time;
// Resolve team from season avg
const seasonStep = leg.reasoning?.steps?.season_avg;
const team = leg._resolvedTeam || null;
// Use the team from the analysis context
if (leg.reasoning?.steps?.situational?.home_away?.context === 'home') {
leg._team = prop.home_team;
} else if (leg.reasoning?.steps?.situational?.home_away?.context === 'away') {
leg._team = prop.away_team;
}
}
}
} catch (_) {
// Correlation detection is best-effort
}
// Detect correlations
const correlationFlags = detectCorrelations(legResults, spreads);
// Grade the parlay
// Attach composite scores from individual analyses for parlay grading
for (const leg of legResults) {
// Reconstruct composite from the reasoning steps
const steps = leg.reasoning?.steps;
if (steps) {
const seasonDelta = steps.season_avg?.vs_line || 0;
const recentDelta = steps.recent_form?.vs_line || 0;
leg._composite = (Math.abs(seasonDelta) + Math.abs(recentDelta)) / 2;
} else {
leg._composite = 0;
}
}
const { grade: parlayGrade, confidence: parlayConfidence } = gradeParlayFromLegs(
legResults,
correlationFlags
);
// Write to database
const pickIds = [];
for (const leg of legResults) {
const { data: pick, error } = await supabase
.from('picks')
.insert({
user_id: user.id,
player: leg.player,
stat_type: leg.stat_type,
line: leg.line,
book: leg.book || 'unknown',
direction: leg.direction,
grade: leg.grade,
edge_pct: leg.edge_pct,
reasoning: leg.reasoning?.summary || '',
kill_conditions: (leg.kill_conditions_triggered || []).map((k) => k.code),
confidence: leg.confidence,
})
.select('id')
.single();
if (pick) pickIds.push(pick.id);
}
// Write scan session
const { data: session } = await supabase
.from('scan_sessions')
.insert({
user_id: user.id,
legs: pickIds,
final_grade: parlayGrade,
kill_conditions: correlationFlags
.filter((f) => f.impact !== 'positive')
.map((f) => f.type),
correlation_notes: JSON.stringify(correlationFlags),
})
.select('id')
.single();
// Atomic scan count increment for free tier
let newScanCount = user.scan_count;
if (isFree) {
const { data: updated } = await supabase
.from('users')
.update({ scan_count: user.scan_count + 1 })
.eq('id', user.id)
.eq('scan_count', user.scan_count)
.select('scan_count')
.single();
newScanCount = updated?.scan_count ?? user.scan_count + 1;
}
// Build response legs (stripped of internal fields)
const responseLegs = legResults.map((leg, i) => ({
index: i,
player: leg.player,
stat_type: leg.stat_type,
line: leg.line,
direction: leg.direction,
grade: leg.grade,
confidence: leg.confidence,
edge_pct: leg.edge_pct,
kill_conditions: leg.kill_conditions_triggered || [],
reasoning_summary: leg.reasoning?.summary || '',
}));
// Generate upgrade pitch at scan 5
let upgradePitch = null;
if (isFree && newScanCount >= 5) {
upgradePitch = await generateUpgradePitch(supabase, user.id, {
grade: parlayGrade,
legs: responseLegs,
});
}
return {
blocked: false,
scan_id: session?.id || null,
parlay_grade: parlayGrade,
parlay_confidence: parlayConfidence,
correlation_flags: correlationFlags,
legs: responseLegs,
scan_count: newScanCount,
scans_remaining: isFree ? Math.max(0, 5 - newScanCount) : null,
upgrade_pitch: upgradePitch,
};
}
module.exports = { scanParlay };