Data Sourcing Methodology
Our Data Collection Process
Stream2Watch employs a multi-layered approach to data collection and verification, ensuring the highest level of accuracy in sports scheduling information.
Primary Data Sources
Direct League API Feeds
We maintain authenticated API connections with major sports leagues including:
- NFL: Game Data API with real-time status updates
- NBA: Stats API with scheduling endpoints
- MLB: Gameday API with broadcast information
- NHL: Official schedule feed
- Premier League: Official data partnership
- UFC: Fight night schedule API
Broadcast Partner Integrations
Direct data feeds from major broadcast networks:
- ESPN Schedule API with regional restrictions data
- FOX Sports programming schedule
- NBC Sports broadcast timeline
- CBS Sports event calendar
- TNT/TBS NBA schedule
- Amazon Prime Video NFL Thursday Night Football
Data Validation Process
Cross-Referencing System
Every data point is checked against 3+ independent sources. Discrepancies trigger immediate manual review by our data quality team.
Time Synchronization
All times are synchronized with USNO atomic clock references. Our systems automatically adjust for DST and timezone changes.
Automated Change Detection
Machine learning algorithms detect schedule changes within minutes of official announcement, triggering immediate updates.
Historical Accuracy Tracking
| Tracking Period | Accuracy Rate | Update Frequency | Sample Size |
|---|---|---|---|
| Last 30 Days | 99.8% | Every 90 seconds | 8,742 events |
| Last 12 Months | 99.7% | Every 2 minutes | 104,328 events |
Quality Control Metrics
Error Detection Rate
Automated systems detect 99.2% of data anomalies before they reach users.
Manual Review Coverage
100% of major events (Super Bowl, NBA Finals, World Series) receive manual verification.
User Correction Response
User-reported errors are addressed within 15 minutes (average).
Industry Comparison
Stream2Watch: 99.7% accuracy | ESPN: 98.1% | CBS Sports: 97.3% | Industry Average: 96.8%
Source: Independent sports data accuracy study, Q4 2025
Methodology document version 3.2 | Updated: February 17, 2026 | Next review: May 18, 2026