Integration Guide

This guide walks you through integrating ALT Sports Data into your sportsbook platform, from installing the SDK to pulling live events and odds in production.

Diagram showing the sportsbook integration workflow from setup through live event and market operations.

Installation

npm install altsportsdata

pip install altsportsdata

Authentication

Store your API key securely as an environment variable:

export ALTSPORTSDATA_API_KEY="your-production-key"

import { AltSportsData } from 'altsportsdata';

const client = new AltSportsData({
  apiKey: process.env.ALTSPORTSDATA_API_KEY
});

from altsportsdata import AltSportsData
import os

client = AltSportsData(
    api_key=os.getenv('ALTSPORTSDATA_API_KEY')
)

Integration Workflow

The typical integration follows four steps: discover leagues, review their data, pull events and markets, then handle errors gracefully.

Step 1. Discover leagues

Find leagues that match your sportsbook's sport coverage goals:

const leagues = await client.leagues.list({
  sportType: 'Soccer',
  tier: 'elite',
  limit: 100
});

for (const league of leagues.data) {
  console.log(`${league.name} (${league.country}) - Tier: ${league.tier}`);
}

leagues = client.leagues.list(
    sport_type='Soccer',
    tier='elite',
    limit=100
)

for league in leagues.data:
    print(f"{league.name} ({league.country}) - Tier: {league.tier}")

Step 2. Check league readiness

Before integrating a league, check its data quality and readiness score to confirm it meets your standards:

const readiness = await client.leagues.readiness('league_001');

console.log(`Overall Score: ${readiness.data.overall_score}/1000`);
console.log('Dimensions:', readiness.data.dimensions);

readiness = client.leagues.readiness('league_001')

print(f"Overall Score: {readiness.data.overall_score}/1000")
print(f"Dimensions: {readiness.data.dimensions}")

Step 3. Pull events and markets

Once you have selected your leagues, fetch upcoming events and their associated market data:

const events = await client.events.list({
  leagueId: 'league_001',
  dateFrom: '2026-03-01',
  dateTo: '2026-03-31'
});

events = client.events.list(
    league_id='league_001',
    date_from='2026-03-01',
    date_to='2026-03-31'
)

Step 4. Handle errors

Production integrations should handle common error cases explicitly:

try {
  const league = await client.leagues.get('invalid_id');
} catch (error) {
  if (error.code === 'RESOURCE_NOT_FOUND') {
    console.error('League not found');
  } else if (error.code === 'RATE_LIMIT_EXCEEDED') {
    console.error('Rate limit exceeded');
  } else {
    console.error('API error:', error.message);
  }
}

from altsportsdata.exceptions import (
    ResourceNotFoundError,
    RateLimitError
)

try:
    league = client.leagues.get('invalid_id')
except ResourceNotFoundError:
    print('League not found')
except RateLimitError:
    print('Rate limit exceeded')
except Exception as e:
    print(f'API error: {e}')

Production best practices

Cache responses -- store league and event data locally to minimize API calls and reduce latency for your users
Monitor rate limits -- check X-RateLimit-Remaining and X-RateLimit-Reset response headers to stay within your plan's limits
Implement retry logic -- use exponential backoff for transient 5xx errors and 429 rate limit responses
Filter early -- use query parameters to request only the leagues, date ranges, and sport types you need, reducing payload size and processing time

Next steps

Full API Reference -- detailed endpoint documentation for every resource
SDKs -- TypeScript and Python client libraries
Authentication -- API key management and security
Error Reference -- complete list of error codes and their meanings

Integration Guide

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