PandaScore REST API for All Videogames

{
  "service_type": "platform",
  "base_url": "https://api.pandascore.co",
  "auth_method": "api_key",
  "auth_config": {
    "header": "Authorization",
    "scheme": "Bearer",
    "query_param": "token",
    "notes": "API key required. Pass as Bearer token in Authorization header or as 'token' query parameter. Keys are obtained via the PandaScore dashboard."
  },
  "endpoints": [],
  "pricing_model": {
    "type": "freemium",
    "details": {
      "notes": "PandaScore offers tiered access with a free tier (rate-limited) and paid plans for higher volume and commercial use. Exact pricing is quote-based via sales."
    }
  },
  "rate_limits": {
    "notes": "Rate limits vary by plan. Free tier is heavily limited; paid plans offer higher quotas. Specific limits are documented in the PandaScore developer portal."
  },
  "capabilities": [
    "Esports data for multiple videogame titles (CS:GO/CS2, League of Legends, Dota 2, Valorant, Overwatch, Call of Duty, Rocket League, etc.)",
    "Tournament, league, and series metadata",
    "Match schedules, live matches, and results",
    "Team and player rosters, transfers, and statistics",
    "Live in-game event data (kills, objectives, etc.) for supported titles",
    "Betting odds and market data",
    "Historical data and archives",
    "Webhooks / real-time push notifications for live events"
  ],
  "raw_analysis": "PandaScore is a commercial esports data provider offering a REST API that covers a wide range of competitive videogame titles. The service is aimed at developers, betting operators, media companies, and analytics platforms who need structured, real-time and historical esports data.\n\nKey characteristics:\n- API base is typically https://api.pandascore.co, with endpoints namespaced by game (e.g., /csgo/matches, /lol/tournaments).\n- Authentication is via API key (Bearer token or token query param), issued through the PandaScore dashboard.\n- The offering is freemium: a free tier exists for experimentation, but production and commercial usage generally requires a paid plan with higher rate limits and SLAs.\n- Maturity: PandaScore is a well-established, widely-used esports data vendor, often cited as one of the leading providers alongside competitors like Abios and Bayes Esports. It has broad title coverage and live data feeds.\n- Integrations: Provides official integrations, SDKs/community libraries, and webhook support for real-time updates. Documentation is developer-friendly with guides on getting started.\n- The provided description is truncated and does not include endpoint specifics, but the platform is a first-class REST API service rather than a scraped UI. Full endpoint catalog should be pulled from the official docs (https://developers.pandascore.co)."
}

1/3 tests passed

{
  "overall": 74,
  "dimensions": {
    "token_efficiency": 7.5,
    "first_try_success": 6.0,
    "response_parseability": 8.5,
    "error_clarity": 7.0,
    "doc_quality": 8.0,
    "auth_simplicity": 5.5,
    "latency": 9.0,
    "consistency": 7.5
  },
  "pricing_normalized": {
    "model": "freemium",
    "free_tier": true,
    "paid_pricing": "quote-based (not public)",
    "transparency_score": 4.0,
    "notes": "Freemium with rate-limited free tier; commercial/high-volume pricing requires contacting sales — opaque to agents and users evaluating cost."
  },
  "issues": [
    "Pricing is quote-based only; no public rate card makes cost comparison difficult for agents recommending the platform.",
    "Production API requires an API token, while robots.txt and llms_txt return 403 'Token is missing' — discovery endpoints are auth-gated, harming agent crawlability.",
    "No llms.txt present, so there is no machine-readable summary for LLM agents to ingest.",
    "Security headers absent on the sampled endpoints.",
    "Live/docs endpoints require auth, which raises first-try onboarding friction (no instant playground hit)."
  ],
  "recommendations": [
    "Publish public pricing tiers (or at least rate-limit/call-quota bands) to improve transparency for both users and recommending agents.",
    "Add an llms.txt and open the docs/discovery surface (robots.txt, llms.txt) without auth so agents can self-serve onboarding info.",
    "Offer a no-auth or instant demo endpoint with sample data so first-try success is immediate.",
    "Add clear error documentation (401/403/429 semantics, rate-limit headers, retry guidance) to improve error clarity.",
    "Harden with standard security headers (HSTS, X-Content-Type-Options, CSP where relevant)."
  ]
}