Unlike traditional sports, esports analysis is built almost entirely on digital data: match history, player statistics, champion/weapon pick rates, tournament schedules. Most of this data is public, but it is scattered and regional.
Data Sources
The official API should always be the first choice. Other sources are complementary and require attention to the terms of use.
The Regionality Problem
Many esports sites change their content according to the visitor's region: different leagues, different languages, different broadcasting rights. Building a global data set requires observing from several regions.
Define a separate collection job for each region; merge the results into a single schema.
Collection Architecture
The normalization step is critical: the same team may appear under a different name on different sites; keep a mapping table.
Ethical and Legal Boundaries
- Do not collect personal data (player contact details, identity information).
robots.txtand the terms of use; do not force your way into restricted areas.- Do not put load on source sites — low rates, night hours, caching.
- Pay attention to local legislation for uses related to betting and games of chance.
Regulations on betting and games of chance in Türkiye are strict. This article is written in the context of statistical analysis and content production; it does not support any use aimed at illegal betting activity.
For collection infrastructure, web scraping proxy, for region selection our location list and for scale rotating proxy pages.