Estimating the peak age of chess players through statistical and machine learning techniques.

ABSTRACT: Because chess is played in formal tournaments and competitive environments, it requires physical and mental endurance. This endurance declines as the years progress and can decrease the player's performance. As the player's age increases, elements such as strategic thinking, game analysis, and psychological endurance come to the fore. In chess, age is the most important variable, although it is not the sole determinant of a player's abilities and achievements. In this study, the age at which Grandmaster level chess players reach the highest ELO levels and the 2,700 ELO threshold was predicted. For this purpose, 12 forecasting models were created using 11 machine learning methods with various variables. The model results were interpreted and the age at which some promising young players rea

SUBMITTER: Erilli NA 

PROVIDER: S-EPMC12485108 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature