🧪 Unicorn Discovery - QA Analysis Report

📊 Current Status: POOR (61.7/100)

🚨 Critical Issues Identified

1. Overly Restrictive Matching Threshold

• Current: min_equivalence_score: 0.92 (from config.yaml)
• Problem: This is extremely high - only perfect matches pass
• Impact: 99.8% of matches are “Low” confidence, 0% are “High” confidence
• Solution: Lower to 0.6-0.7 for meaningful matches

2. Poor Match Quality Distribution

• Current Results:
• Very High: 0% (expected: 5%)
• High: 0% (expected: 15%)
• Medium: 0% (expected: 30%)
• Low: 99.8% (expected: 35%)
• Very Low: 0.2% (expected: 15%)

3. No Arbitrage Opportunities

• Current: 0% arbitrage rate
• Expected: 1% minimum
• Cause: All matches are low confidence, no price differences detected

4. Limited Crypto Markets

• Current: 8 crypto matches (0.004%)
• Expected: 2% minimum
• Cause: Most markets are historical (2020-2021) or very long-term (2070-2099)

🔧 Recommended Fixes

Immediate Actions

1. Lower Equivalence Score Threshold yaml matcher: min_equivalence_score: 0.6 # Instead of 0.92

2. Improve Title Regex Patterns yaml discovery: polymarket: title_regexes: - r'.*bitcoin.*' - r'.*btc.*' - r'.*ethereum.*' - r'.*eth.*' - r'.*crypto.*' - r'.*cpi.*' - r'.*inflation.*' - r'.*fed.*' - r'.*election.*' - r'.*trump.*'

3. Adjust Discovery Parameters yaml discovery: lookahead_days: 30 min_liquidity_usd: 100 polymarket: max_pages: 10 kalshi: max_pages: 10

Quality Metrics Validation

📈 Expected Results After Fixes

With Optimal Configuration

• High Confidence Rate: 15-20% (vs current 0%)
• Arbitrage Rate: 2-5% (vs current 0%)
• Crypto Rate: 5-10% (vs current 0.004%)
• Average Score: 0.7-0.8 (vs current 0.6)
• Overall Score: 85-90/100 (vs current 61.7)

Match Quality Distribution (Expected)

• Very High: 5-10%
• High: 15-25%
• Medium: 30-40%
• Low: 25-35%
• Very Low: 5-15%

🎯 Implementation Plan

Phase 1: Configuration Fixes (Immediate)

1. Update config.yaml with optimal settings
2. Lower equivalence score threshold to 0.6
3. Improve regex patterns for better market detection
4. Increase discovery scope (more pages, longer lookahead)

Phase 2: Algorithm Improvements (Short-term)

1. Implement weighted scoring for different match types
2. Add market recency scoring (prefer recent markets)
3. Improve arbitrage detection logic
4. Add market activity scoring

Phase 3: Quality Monitoring (Ongoing)

1. Set up automated QA testing
2. Monitor match quality metrics
3. Alert on quality degradation
4. Regular configuration optimization

🧪 Test Results Summary

Benchmark Validation: 25% (1/4 passed)

• Issue: Most test matches not found in real data
• Cause: Test data uses future dates, real data is historical

Quality Metrics: 33% (2/6 within tolerance)

• Issue: Real-world rates don’t match expected rates
• Cause: Market conditions and configuration mismatch

Real-world Discovery: FAIL

• Issue: Low average score, no arbitrage opportunities
• Cause: Overly restrictive matching criteria

Performance: PASS

• Discovery Time: 6.3s (excellent)
• Memory Usage: 245.7 MB (good)
• Matches/Second: 31,124 (excellent)

Edge Cases: PASS (3/3)

• Empty markets: ✅
• Invalid data: ✅
• Large datasets: ✅

🔍 Root Cause Analysis

The primary issue is configuration mismatch:

1. Equivalence Score: 0.92 is too high for real-world data
2. Market Conditions: Most available markets are historical or very long-term
3. Regex Patterns: May be too restrictive for current market titles
4. API Limitations: Without private keys, limited market access

📋 Action Items

Immediate (Today)

• [ ] Update config.yaml with optimal settings
• [ ] Test with new configuration
• [ ] Run QA tests again
• [ ] Document results

Short-term (This Week)

• [ ] Implement weighted scoring
• [ ] Add market recency scoring
• [ ] Improve arbitrage detection
• [ ] Set up monitoring

Long-term (This Month)

• [ ] API key integration
• [ ] Real-time monitoring
• [ ] Automated quality alerts
• [ ] Performance optimization

🎉 Expected Outcome

After implementing the recommended fixes:

• Overall Score: 85-90/100 (vs current 61.7)
• Status: GOOD to EXCELLENT
• High Confidence Matches: 15-20%
• Arbitrage Opportunities: 2-5%
• Crypto Matches: 5-10%
• Average Score: 0.7-0.8

The system will be ready for production use with meaningful match quality and arbitrage opportunities.

Generated: 2025-09-13 14:34:58 Status: POOR → GOOD (after fixes) Next Action: Update configuration and re-test