Relationship between external and internal loads of professional soccer players during full matches in official games using global positioning systems and heart-rate technology

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Journal Article
International Journal of Sports Physiology and Performance, 2016, 11 (7), pp. 940 - 946
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© 2016 Human Kinetics, Inc. Purpose: To analyze the match running profle, distance traveled over successive 15 min of match play, heart rates (HRs), and index of performance effciency (effindex) of professional soccer players with a global positioning system (GPS) and HR in offcial 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 frst. 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 midfelders re?ected substantially the lowest mean HR and highest effindex, whereas center backs showed substantially the lowest effindex of all playing positions. Conclusions: The current study confrmed the decrement in a player's performance toward the end of a match in all playing positions. Wide midfelders displayed the highest and fttest levels of physical and physiological demands, respectively, whereas center backs had the lowest and least-ft levels of physical and physiological demands, respectively. The position-specifc relationship between external and internal load confrms that players with more overall running performance during the full match were the best in effindex.
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