Int J Sports Med 2020; 41(05): 300-305
DOI: 10.1055/a-1073-7851
Training & Testing
© Georg Thieme Verlag KG Stuttgart · New York

A Reduction in Match-to-match Variability Using Maximal Mean Analyses in Sub-elite Soccer

1   Centre for Exercise and Sports Science Research, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
,
Anthony John Blazevich
1   Centre for Exercise and Sports Science Research, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
,
Chris Richard Abbiss
1   Centre for Exercise and Sports Science Research, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
,
Fadi Maʼayah
1   Centre for Exercise and Sports Science Research, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
2   School of Education, Curtin University, Bentley, Australia
› Author Affiliations
Further Information

Publication History



accepted 10 November 2019

Publication Date:
20 January 2020 (online)

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Abstract

The match-to-match variability of external loads in National Premier League soccer competition was determined. Global positioning systems (GPS) data were collected from 20 sub-elite soccer players over 2–10 matches from a single season. Match data were collected from during one season. Twenty-six matches were recorded and 10 were utilised within final match-to-match analysis based on stringent data selection criteria. A symmetric moving average algorithm was applied to GPS data over specific time windows (1, 5, 10, 60, 300 and 600 s), and maximal speed and metabolic power values then calculated at each time interval during each match. Match-to-match coefficients of variation (CV) were greatest for sprint-speed running distance (36.3–43.6%) when comparing 2 vs. 10 matches. CVs for maximal mean speed (4.9–7.0%) and metabolic power (4.4–9.6%) ranged from good to moderate. As the variability of absolute high-speed distance values are greater, and therefore less reliable, their use as indicators of performance is reduced, suggesting that maximal mean analyses could be used as an alternative in the assessment of match running performance during competitive matches.