A comparison of rolling averages versus discrete time epochs for assessing the worst-case scenario locomotor demands of professional soccer match-play.
OBJECTIVES
To compare fixed epochs (FIXED) and rolling averages (ROLL) for quantifying worst-case scenario ('peak') running demands during professional soccer match-play, whilst assessing contextual influences.


DESIGN
Descriptive, observational.


METHODS
Twenty-five outfield players from an English Championship soccer club wore 10-Hz microelectromechanical systems during 28 matches. Relative total and high-speed (>5.5ms-1) distances were averaged over fixed and rolling 60-s to 600-s epochs. Linear mixed models compared FIXED versus ROLL and assessed the influence of epoch length, playing position, starting status, match result, location, formation, and time-of-day.


RESULTS
Irrespective of playing position or epoch duration, FIXED underestimated ROLL for total (∼7-10%) and high-speed (∼12-25%) distance. In ROLL, worst-case scenario relative total and high-speed distances reduced from 190.1±20.4mmin-1 and 59.5±23.0mmin-1 in the 60-s epoch, to 120.9±13.1mmin-1 and 14.2±6.5mmin-1 in the 600-s epoch, respectively. Worst-case scenario total distance was higher for midfielders (∼9-16mmin-1) and defenders (∼3-10mmin-1) compared with attackers. In general, starters experienced higher worst-case scenario total distance than substitutes (∼3.6-8.5mmin-1), but lower worst-case scenario high-speed running over 300-s (∼3mmin-1). Greater worst-case scenario total and high-speed distances were elicited during wins (∼7.3-11.2mmin-1 and ∼2.7-7.9mmin-1, respectively) and losses (∼2.7-5.7mmin-1 and ∼1.4-2.2mmin-1, respectively) versus draws, whilst time-of-day and playing formation influenced worst-case scenario high-speed distances only.


CONCLUSIONS
These data indicate an underestimation of worst-case scenario running demands in FIXED versus ROLL over 60-s to 600-s epochs while highlighting situational influences. Such information facilitates training specificity by enabling sessions to be targeted at the most demanding periods of competition.
['Fereday|Kieran|K|', 'Hills|Samuel P|SP|', 'Russell|Mark|M|', 'Smith|Jordan|J|', 'Cunningham|Dan J|DJ|', 'Shearer|David|D|', 'McNarry|Melitta|M|', 'Kilduff|Liam P|LP|']
D000328:Adult D054874:Athletic Performance D040362:Geographic Information Systems D006801:Humans D016014:Linear Models D012420:Running D012916:Soccer D013997:Time Factors D013996:Time and Motion Studies D055815:Young Adult
Running Activity profiles Fatigue Football Monitoring Physiology