Search Results

You are looking at 1 - 1 of 1 items for

  • Author: Nacho Torreño x
  • Refine by Access: All Content x
Clear All Modify Search
Restricted access

Nacho Torreño, Diego Munguía-Izquierdo, Aaron Coutts, Eduardo Sáez de Villarreal, Jose Asian-Clemente, and Luis Suarez-Arrones

Purpose:

To analyze the match running profile, distance traveled over successive 15 min of match play, heart rates (HRs), and index of performance efficiency (effindex) of professional soccer players with a global positioning system (GPS) and HR in official competition.

Methods:

Twenty-six professional players were investigated during full matches in competitive club-level matches (N = 223). Time–motion data and HR were collected using GPS and HR technology.

Results:

The relative total distance was 113 ± 11 m/min, with substantial differences between halves. For all playing positions, a substantial decrease in total distance and distance covered at >13.0 km/h was observed in the second half in comparison with the first. The decrease during the second half in distance covered at >13.0 km/h was substantially higher than in total distance. The average HR recorded was 86.0% maximal HR, and the relationship between external and internal load (effindex) was 1.3, with substantial differences between halves in all playing positions, except strikers for effindex. Wide midfielders reflected substantially the lowest mean HR and highest effindex, whereas center backs showed substantially the lowest effindex of all playing positions.

Conclusions:

The current study confirmed the decrement in a player’s performance toward the end of a match in all playing positions. Wide midfielders displayed the highest and fittest levels of physical and physiological demands, respectively, whereas center backs had the lowest and least-fit levels of physical and physiological demands, respectively. The position-specific relationship between external and internal load confirms that players with more overall running performance during the full match were the best in effindex.