Duration-specific running intensities of Australian Football match-play

Delaney, Jace A.; Thornton, Heidi R.; Burgess, Darren J.; Dascombe, Ben J.; Duthie, Grant M.

doi:10.1016/j.jsams.2016.11.009

Cited by 65 publications

(119 citation statements)

References 26 publications

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“…In particular, Vázquez-Guerrero et al (2019) showed that basketball players averaged 1.8 and 1.5 high-intensity accelerations and decelerations and covered a relative distance of 72.6 m min −1 . A similar trend has been observed in previous studies conducted in other sports, such as associated football (Abbott et al, 2018;Delaney et al, 2018;Martín-García et al, 2018;Casamichana et al, 2019), rugby (Delaney et al, 2016;Cunningham et al, 2018), Gaelic football (Malone et al, 2017), and Australian football (Delaney et al, 2017).…”

Section: Discussionsupporting

confidence: 89%

“…While some studies have determined the most demanding scenarios in physical demands during competition in intermittent team sports such as association football (Abbott et al, 2018;Delaney et al, 2018;Martín-García et al, 2018;Casamichana et al, 2019), rugby (Delaney et al, 2016;Cunningham et al, 2018), Gaelic football (Malone et al, 2017), and Australian football (Delaney et al, 2017) through different time average rolling durations, no studies are available that quantify physical demands during match play in basketball using this approach. A plethora of studies have examined the average (mainly per minute) and absolute physical demands of match play in basketball reporting that players usually cover 5-6 km at an average speed of 70-90 m min −1 and perform a total of 40-50 jumps (Stojanović et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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The Most Demanding Scenarios of Play in Basketball Competition From Elite Under-18 Teams

et al. 2020

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The main purpose of this study was to describe the most demanding scenarios of match play in basketball through a number of physical demand measures (high-intensity accelerations and decelerations, relative distance covered, and relative distance covered in established speed zones) for four different rolling average time epochs (30, 60, 180, and 300 s) during an official international tournament. A secondary purpose was to identify whether there were significant differences in physical demand measures among playing positions (centers, guards, and forwards) and levels (two best classified teams in the tournament and remaining teams), match scoring (winning, losing, and drawing), and playing periods (match quarter) at the moment of the most demanding scenarios. Data were collected from 94 male under 18 (U18) elite basketball players (age: 17.4 ± 0.7 years; stature: 199.0 ± 11.9 cm; body mass: 87.1 ± 13.1 kg) competing in a Euroleague Basketball Tournament. Measures were compared via a Bayesian inference analysis. The results revealed the presence of position-related differences [Bayesian factor (BF) > 10 (at least strong evidence) and standardized effect size (δ) > 0.6 (at least moderate)] so that centers covered a lower relative distance at speed zone 1 and had lower high-intensity accelerations and decelerations than guards. However, the Bayesian analysis did not demonstrate the existence of significant differences in any physical demand measure in relation to the playing level, match scoring, and playing periods at the moment of the most demanding scenarios. Therefore, this study provides coaches and strength and conditioning specialists with a most demanding scenario reference on physical demands that can be used as an upper limit threshold in the training and rehabilitation monitoring processes.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

The Most Demanding Scenarios of Play in Basketball Competition From Elite Under-18 Teams

et al. 2020

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“…Literature reports that the running demands of AF are high (Coutts et al, 2010;Delaney et al, 2017). As a result, a primary focus of AF training is to develop players' capacity in this area (Delaney et al, 2017); a performance test that provides a measure of running ability was therefore used in this study. Traditionally, AF clubs have used a 3 km time trial in order to assess aerobic capacity (Gastin et al, 2013;Piggott et al, 2015).…”

Section: × 1 Km Time Trialsmentioning

confidence: 99%

Interdisciplinary Sport Research Can Better Predict Competition Performance, Identify Individual Differences, and Quantify Task Representation

Piggott

Müller

Chivers

et al. 2020

Front. Sports Act. Living

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Sport performance consists of interacting individual, task and environmental constraints, but research has used a monodisciplinary, rather than an interdisciplinary approach to understand performance. This study used Australian football (AF) as the exemplar sport to investigate the value of an interdisciplinary approach to understand sport performance. Through this, it was also possible to quantify individual differences and representative task design. Fifty-nine semi-professional Australian footballers participated. Based upon accessibility, combinations of these players completed physiological (3 × 1 km trial) and perceptual-cognitive-motor (small-sided game, SSG) tests, with coach rating of psychological skill (mental toughness coach, MTC). Univariate monodisciplinary models indicated that all tests predicted disposal efficiency; 3 × 1 km trial (p = 0.047), SSG (p = 0.001), and MTC (p = 0.035), but only the SSG predicted coaches' vote (p = 0.003). A multivariate interdisciplinary model indicated that SSG and MTC tests predicted disposal efficiency with a better model fit than the corresponding univariate model. The interdisciplinary model formulated an equation that could identify individual differences in disposal efficiency. In addition, the interdisciplinary model showed that the higher representative SSG test contributed a greater magnitude to the prediction of competition performance, than the lower representative MTC rating. Overall, this study demonstrates that a more comprehensive understanding of sport performance, individual differences, and representative tasks, can be obtained through an interdisciplinary approach.

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“…Previous research in soccer [20], Australian football [21], and Gaelic football [22] has demonstrated that maximal mean analyses (i. e. rolling averages) during match play can be used to monitor performance and assist in training prescription. More recently, analyses using shorter time windows through maximal mean analyses (i. e. 1, 5 and 10 s) has been shown to determine an individual's capacity to achieve and maintain both speed and P met at higher running speeds [19].…”

Section: Introductionmentioning

confidence: 99%

Comparing Maximal Mean and Critical Speed and Metabolic Powers in Elite and Sub-elite Soccer

et al. 2020

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The quantification of maximal mean speed (MMS), maximal mean metabolic power (MMPmet), critical speed (CS) and critical metabolic power (CPmet) was conducted over full A-League (elite) and National Premier League (NPL; sub-elite) seasons. Comparisons were made between levels of soccer competition and playing positions (i. e. centre backs, full backs, central midfielders, wide midfielders and strikers). A symmetric moving average algorithm was applied to the GPS raw data using specific time windows (i. e. 1, 5, 10, 60, 300 and 600 s) and maximal values were obtained. Additionally, these maximal values were used to derive estimates of CS and CPmet. Maximal mean values, particularly during smaller time windows (i. e. 1 and 5 s), were greater in A-League match play. Only MMPmet1 was identified as being consistently different between competitions (P=<0.001–0.049) in all playing positions. Significance was only observed in CS (P=0.005) and CPmet (P=0.005) of centre backs between competitions. Centre backs were identified as the least energy demanding playing position. The present findings suggests that both maximal mean and critical analyses are suitable alternatives to common absolute distance and speed assessments of match running performance during competitive matches.

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Duration-specific running intensities of Australian Football match-play

Cited by 65 publications

References 26 publications

The Most Demanding Scenarios of Play in Basketball Competition From Elite Under-18 Teams

The Most Demanding Scenarios of Play in Basketball Competition From Elite Under-18 Teams

Interdisciplinary Sport Research Can Better Predict Competition Performance, Identify Individual Differences, and Quantify Task Representation

Comparing Maximal Mean and Critical Speed and Metabolic Powers in Elite and Sub-elite Soccer

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