Performance Optimization
1. Use Batch Endpoints
Always use the multi-odds endpoint when fetching odds for multiple events: Bad:2. Implement Caching
Cache responses based on data type and freshness requirements:Data Type | TTL | Reason |
---|---|---|
Sports list | 1 hour+ | Rarely changes |
Leagues list | 1 hour | Rarely changes |
Pre-match events | 5-10 minutes | Updated periodically |
Pre-match odds | 30-60 seconds | Changes frequently |
Live events | 10-30 seconds | Changes very frequently |
Live odds | 5-10 seconds | Changes in real-time |
3. Select Bookmakers Wisely
Don’t fetch odds from all 250+ bookmakers:Rate Limit Management
1. Implement Rate Limiting
Track and respect API rate limits:2. Handle 429 Responses
Implement exponential backoff for rate limit errors:3. Monitor Usage
Track your API usage to avoid hitting limits:Error Handling
1. Graceful Degradation
Handle missing data gracefully:2. Validate Responses
Always validate API responses:3. Timeout Handling
Set timeouts for API requests:Security Best Practices
1. Secure API Keys
Never expose API keys in client-side code!
2. Validate Input
Always validate user input before using it in API calls:Data Management
1. Database Schema
Store odds data efficiently:2. Store Historical Data
Keep historical odds for analysis:3. Cleanup Old Data
Regularly clean up stale data:Monitoring & Logging
1. Log Important Events
2. Set Up Alerts
Monitor critical metrics:Testing
1. Unit Tests
2. Integration Tests
Summary Checklist
Performance
Performance
- ✅ Use batch endpoints when possible
- ✅ Implement appropriate caching
- ✅ Select relevant bookmakers only
- ✅ Minimize unnecessary API calls
Rate Limiting
Rate Limiting
- ✅ Implement rate limiting logic
- ✅ Handle 429 responses with backoff
- ✅ Monitor and track usage
- ✅ Use multi-endpoints efficiently
Error Handling
Error Handling
- ✅ Validate all responses
- ✅ Handle missing data gracefully
- ✅ Implement request timeouts
- ✅ Log errors properly
Security
Security
- ✅ Never expose API keys client-side
- ✅ Use environment variables
- ✅ Validate all user input
- ✅ Implement server-side proxy
Data Management
Data Management
- ✅ Design efficient database schema
- ✅ Store historical data when needed
- ✅ Clean up old data regularly
- ✅ Index time-series queries