Fundamentals

Learn the fundamentals of the opinionated, flexible data structure PandaScore uses to map esports competitions across all video games.

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Coming from sports?

This page uses examples from esports and traditional sports to explain PandaScore data structure.

Leagues

Leagues are the top-level data structure used to represent a competition. Leagues are commonly named after the competition they represent. A league includes one or several children Series.

Examples

  • FIFA World Cup
  • The International

Series

Series represent a single timely occurrence of their parent League. A series includes one or several children Tournaments.

Examples

  • FIFA World Cup ā€” 2018
  • The International ā€” 2018

Tournaments

Tournaments represent a stage in their parent Series. A tournament includes one or several children matches that contribute to a unique standing and possible winner.

Examples

  • FIFA World Cup ā€” 2018 ā€” Group C
  • The International ā€” 2018 ā€” Playoffs

Matches

Matches represent a team-versus-team or player-versus-player confrontation between two participants of a parent Tournament. A match includes one or several children Games.

Matches is the most in-depth generic data structure. Despite many common properties, the data structure for Games (and below) is specific to each video game.

Examples

  • FIFA World Cup ā€” 2018 ā€” Group C ā€” Denmark vs Australia (only 1 game)
  • The International ā€” 2018 ā€” Playoffs ā€” Final: OG vs PSG.LGD (5 games)

In-game results should be retrieved via game-level endpoints (only available for video games supporting Historical Data).

Recap diagram

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Data Structure


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