Listening

Hopp.it operates like a real-time trading engine that continuously monitors live events across multiple domains. Our event listening infrastructure serves as the foundation for instantaneous market creation and resolution.

Data Integration Architecture

Our platform connects to multiple licensed enterprise data providers to ensure comprehensive coverage and eliminate single points of failure:

Sports Data Pipeline

• Primary Sources: Genius Sports, Stats Perform, and ESPN APIs deliver real-time updates on score changes, player positions, possession percentages, and game clock information

• Event Granularity: Goals, cards, substitutions, corners, fouls, and other significant match events with microsecond-precision timestamps

• Player Analytics: Individual statistics including shots on target, passes completed, distance covered, and tactical positioning

• Contextual Data: Weather conditions, referee decisions, VAR reviews, injury updates, team form, and head-to-head records

E-sports Integration

• Game State Data: Direct feeds from tournament organizers provide kill counts, objective captures, economy status, and map control percentages

• Tactical Breakdown: Detailed analysis of executions, weapon purchases, and positioning with frame-perfect accuracy

• Tournament Context: Bracket progression, series scores, and format-specific data points synchronized with broadcast streams

News Monitoring System

• Verified Sources: Integration with reputable news organizations like Reuters, Bloomberg, CNN, and BBC

• Social Media Analysis: Trending topics analysis with authenticity verification protocols

• Content Curation: Pre-approved sources that meet strict quality and reliability standards

Data Processing & Validation

All incoming data streams undergo standardization before entering our internal event bus:

Temporal Synchronization: Events are normalized to UTC with microsecond precision to ensure accurate sequencing across global time zones.

Format Normalization: Data is converted to consistent internal schemas regardless of source format, enabling seamless processing across different providers.

Deduplication: Advanced algorithms identify and merge duplicate events from multiple sources, preventing data pollution and ensuring clean event streams.

Confidence Scoring: Each data point receives a reliability score (0-100) based on source credibility, historical accuracy, and cross-verification status.

Quality Assurance & Resilience

Multi-Source Verification

Critical events undergo cross-verification protocols where important outcomes require confirmation from at least two independent providers with confidence scores above 85%.

Conflict Resolution

When data sources disagree, our weighted scoring system automatically resolves conflicts based on historical source reliability and real-time confidence metrics.

Failover Systems

• Geographic distribution of data ingestion points ensures continuous operation even during regional network issues

• Automatic failover to secondary providers activates within 5 seconds when primary sources experience outages

• Intelligent queuing systems handle data spikes during high-activity periods like goal flurries or viral news events