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Reducing Big Data to Principal Components for Position-Specific Futsal Training.

Markel Rico-González1,2, Jordi Illa3, Fabio Yuzo Nakamura4,5

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Summary

Big data analysis simplifies training load assessment in elite futsal. Key variables like accelerations and distance covered differentiate player positions, enabling personalized training and game analysis.

Keywords:
game analysisindoor footballprincipal component analysisteam sporttracking

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Area of Science:

  • Sports Science
  • Biomechanics
  • Exercise Physiology

Background:

  • Effective training prescription in elite sports requires rapid assessment and interpretation of training/competition loads.
  • Multivariate data analysis can simplify complex big data for practical application.
  • Understanding position-specific demands in futsal is crucial for optimizing player performance.

Purpose of the Study:

  • To identify key variables from big data analyses that best describe the behavior of elite futsal players across different playing positions.
  • To determine position-specific performance indicators for goalkeepers, defenders, wingers, and forwards in futsal.

Main Methods:

  • Collected big data from four top-level Spanish futsal teams during a national tournament.
  • Applied Principal Component Analysis (PCA) to group and analyze numerous variables related to player movement and load.
  • Identified key variables explaining 62-81% of total variance in player behavior, categorized by playing position.

Main Results:

  • Goalkeeper performance was linked to accelerations per minute, maximum acceleration, impacts per minute, and takeoffs per minute.
  • Defender behavior was characterized by distance covered at specific speeds (6-12 km/h and 18-21 km/h) and landing frequencies.
  • Winger and pivot performance highlighted the importance of accelerations, decelerations, and aerobic endurance, particularly for wingers.

Conclusions:

  • Specific big data variables effectively differentiate the physical demands of futsal playing positions.
  • Findings facilitate individualized training programs and enhance game analysis for elite futsal players.
  • PCA is a valuable tool for simplifying complex sports performance data to inform coaching strategies.