PERFORMANCE PROFILLING AND DATA ANALYTICS IN ELITE SHORT TRACK SPEED SKATING: A CASE STUDY OF THE HUNGARIAN OLYMPIC TEAM

Imre Emil

doi:10.35120/medisij040415i

Authors

Imre Emil Hungarian University Of Sport Science, Hungary Author

DOI:

https://doi.org/10.35120/medisij040415i

Keywords:

data analysis, performance optimization, short track speed skating, biomechanics

Abstract

This study explores the composition and performance of the Hungarian Olympic short track speed skating team, with a focus on data-driven analysis to assess trends, strategies, and athlete development. Hungary has emerged as a competitive force in short track speed skating, notably securing its first Winter Olympic gold medal in 2018. By compiling biographical and performance data of team members across multiple Olympic cycles, the analysis identifies key factors contributing to success, including age, experience, specialization (e.g., 500m vs. 1500m), and team dynamics in relay events. Advanced performance metrics such as lap times, split consistency, and overtaking patterns are examined using statistical and machine learning techniques to uncover predictive indicators of medal contention. The research also highlights the importance of strategic decision-making, pacing, and positioning, especially in relay events where Hungary has consistently excelled. This study provides insights into how data analysis can be used to enhance training, selection, and race strategies, offering a model for other national teams seeking to improve performance through evidence-based approaches.

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