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

Area of Science:

• Sports Science
• Biomechanics
• Exercise Physiology

Background:

• Understanding external load variability is crucial for optimizing training and performance in elite soccer.
• Global positioning systems (GPS) are widely used to quantify player workloads during matches.
• Sub-elite soccer players may exhibit different load profiles compared to professional athletes.

Purpose of the Study:

• To determine the match-to-match variability of external loads in National Premier League soccer.
• To assess the reliability of different external load metrics for evaluating soccer performance.
• To compare the variability of sprint distance, maximal mean speed, and metabolic power.

Main Methods:

• Collected GPS data from 20 sub-elite soccer players over 2-10 matches.
• Applied a symmetric moving average algorithm to GPS data over various time windows (1-600s).
• Calculated maximal speed and metabolic power at each time interval during matches.

Main Results:

• Match-to-match coefficients of variation (CV) were highest for sprint-speed running distance (36.3-43.6%).
• CVs for maximal mean speed (4.9-7.0%) and metabolic power (4.4-9.6%) indicated moderate to good reliability.
• High-speed distance variability reduces its reliability as a performance indicator.

Conclusions:

• Maximal mean speed and metabolic power are more reliable measures of running performance in soccer matches than absolute high-speed distance.
• These findings suggest alternative methods for assessing match running performance in competitive soccer.
• Coaches and sports scientists should consider using maximal mean speed and metabolic power for load monitoring.