Replication Data for: Is There a Relative Age Effect in eSports?

This dataset contains individual-level information on professional and semi-professional eSports players and is used to study the presence of the Relative Age Effect (RAE) in competitive eSports. The Relative Age Effect refers to systematic advantages experienced by individuals born earlier in a selection year, a phenomenon well documented in traditional sports. This dataset supports an empirical analysis of whether similar age-related advantages exist in eSports, a domain primarily driven by cognitive, strategic, and reaction-based skills rather than physical attributes. The dataset includes 56,895 eSports players from multiple countries and competitive years. It combines demographic information with performance outcomes measured through prize earnings. The data were used to estimate the effect of birth timing on financial success in eSports using both conventional regression models and Causal Random Forest (CRF) methods. Variables country: Country of nationality of the player. year: Year in which the prize earnings were recorded. prize: Total prize money earned by the player in the given year (monetary units as reported in the original sources). birth: Player’s date of birth, used to construct birth month and relative age measures.