The Distribution of Match Activities Relative to the Maximal Mean Intensities in Professional Rugby League and Australian Football

Johnston, Rich D.; Thornton, Heidi R.; Wade, Janet; Devlin, Paul; Duthie, Grant M.

doi:10.1519/jsc.0000000000003613

Cited by 26 publications

(33 citation statements)

References 34 publications

(56 reference statements)

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“…The distribution (%) of volume was used rather than simply volume accumulated as this standardizes the variables assessed, and accounts for differing game time. In this research (Johnston et al, 2020), most match activities (quantified using total distance, accelerometer load, and impulse) were performed at ∼60% of peak match intensity for both professional Australian football (i.e., AFL) and rugby league (i.e., NRL) (Johnston et al, 2020). Further, within AFL, for the three movement variables investigated, athletes accumulated 13% of total distance, 7% of total impulse, and 11% of the total accelerometer load above 70% of the 1-min MM (Johnston et al, 2020).…”

Section: Introductionmentioning

confidence: 92%

“…Moving averages have been established as an effective and simple method to quantify fluctuations in intensity that occur during team-sport competition (Cunningham et al, 2018). Moving averages involve calculating the mean of a variable over a select period (i.e., 1 min), then forward shifting over the length of the dataset, where the maximum value of that period is then extracted (Johnston et al, 2020). This maximal mean (MM) value can be calculated across a range of movement variables, and regardless of the variable assessed, a consistent finding in research is an evident decline in intensity as the duration of the moving average increases (Delaney et al, 2016(Delaney et al, , 2017Duthie et al, 2019;Thornton et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Practically, MMs can be used as a guideline regarding the intensity of drills of differing duration with the purpose of exposing athletes to match intensity [i.e., during small-sided games (SSG)] (Duthie et al, 2019). Whilst MMs are extremely useful in the prescription of such training drills, it must be noted that the "peak" or maximal value attained throughout a match only occurs once, therefore not reflecting the overall fluctuating intensity of the match (Johnston et al, 2020). Indeed, one study showed little difference between professional and semi-professional rugby league competition in 1-10-min MMs; suggesting that these periods may not reflect the overall demands of competition (Johnston et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, one study showed little difference between professional and semi-professional rugby league competition in 1-10-min MMs; suggesting that these periods may not reflect the overall demands of competition (Johnston et al, 2019). Athletes may only reach this MM value or near this for 1-min of the game, therefore it may be unnecessary to expose athletes to this intensity for large volumes (Johnston et al, 2020), as per typical periodization principles. Further work is required to determine the quantity of work that is required at these intensities.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, an alternative method of describing the intensity of competition has been investigated where the distribution of volume covered relative to the 1-min MM value for a range of variables was presented (Johnston et al, 2020). Specifically, the intensity accumulated relative to the MM value was expressed in 10% buckets (i.e., 110-100%, 100-90%, all the way to 0).…”

Section: Introductionmentioning

confidence: 99%

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The aims were to investigate the externally measured weekly loads, and the distribution intensity relative to the 1-min maximal mean (MM) intensity of matches. Athletes (n = 28) wore 10 Hz GNSS devices during training and matches. For the descriptive analysis, a range of movement variables were collected, including total distance, high-speed distance, very high-speed distance, acceleration, and acceleration load. Using raw GNSS files, 1-min moving averages were calculated for speed (m·min−1) and acceleration (m·s−2), and were multiplied by time, specifying total distance (m), and by body mass to quantify impulse (kN·s−1). The distribution of distance and impulse accumulated at varied intensities relative to MMs was calculated, with percentages ranging from zero to 110%. Drills were categorized as either; warm-ups, skill drills, games (i.e., small-sided games), conditioning and matches. Linear mixed models determined if the distribution of intensity within each threshold (>50%) varied between drill types and matches, and if the distribution within drill types varied across the season. Effects were described using standardized effect sizes (ES) and 90% confidence limits (CL). Compared to matches, a higher proportion of distance was accumulated at 50% of the MM within warm-ups and conditioning (ES range 0.86–1.14). During matches a higher proportion of distance was accumulated at 60% of MM when compared to warms ups, skill drills and conditioning (0.73–1.87). Similarly, greater proportion of distance was accumulated between 70 and 100% MM in matches compared to skill drills and warm-ups (1.05–3.93). For impulse, matches had a higher proportion between 60 and 80% of the MM compared to conditioning drills (0.91–3.23). There were no other substantial differences in the proportion of impulse between matches and drill types. When comparing phases, during competition there was a higher proportion of distance accumulated at 50% MM than general preparation (1.08). A higher proportion of distance was covered at higher intensities within matches compared to drills. The proportion of impulse was higher between 60 and 80% MM within matches compared to conditioning. Practitioners can therefore ensure athletes are not only exposed to the intensities common within competition, but also the volume accumulated is comparable, which may have positive performance outcomes, but is also extremely important in the return to play process.

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Section: Introductionmentioning

confidence: 92%