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Sequential movement pattern-mining (SMP) in field-based team-sport: A framework for quantifying spatiotemporal data and improve training specificity?. SportRxiv, doi:xxx.

While many (popular) cultural studies focus on the discursive construction, and dominant meanings created in and through events, shows and individuals, there has been a relative dearth of studies that examine the production practices of those who create these mediated entities. As such, this project seeks to help fill the relative void left in production practice studies, by critically evaluating the 2003 Little League World Series (LLWS). We will argue that the cultivation of this event was part of a wider (un)spoken social and political project to position the United States as a country which was to be exalted as a space of widespread diversity, acceptance of difference, and to be revered for its inherent greatness (Ferguson 2004). Further, through our critique of the veritable meaning makers for the LLWS, this project aims to illuminate the power they have in reifying particular in this case overwhelmingly positive understandings of those who hold political sway at particular moments in time. This article concludes by looking back at the 2003 American socio-political moment through a 2007 lens, a time when the republic is unquestionably more wary towards the Bush Presidency, the War in Iraq, and the government more generally.

This study aims to (a) quantify the movement patterns during rugby league match-play and (b) identify if differences exist by levels of competition within the movement patterns and units through the sequential movement pattern (SMP) algorithm. Global Positioning System data were analysed from three competition levels; four Super League regular (regular-SL), three Super League (semi-)Finals (final-SL) and four international rugby league (international) matches. The SMP framework extracted movement pattern data for each athlete within the dataset. Between competition levels, differences were analysed using linear discriminant analysis (LDA). Movement patterns were decomposed into their composite movement units; then Kruskal-Wallis rank-sum and Dunn post-hoc were used to show differences. The SMP algorithm found 121 movement patterns comprised mainly of "walk" and "jog" based movement units. The LDA had an accuracy score of 0.81, showing good separation between competition levels. Linear discriminant 1 and 2 explained 86% and 14% of the variance. The Kruskal-Wallis found differences between competition levels for 9 of 17 movement units. Differences were primarily present between regular-SL and international with other combinations showing less differences. Movement units which showed significant differences between competition levels were mainly composed of low velocities with mixed acceleration and turning angles. The SMP algorithm found 121 movement patterns across all levels of rugby league match-play, of which, 9 were found to show significant differences between competition levels. Of these nine, all showed significant differences present between international and domestic, whereas only four found differences present within the domestic levels. This study shows the SMP algorithm can be used to differentiate between levels of rugby league and that higher levels of competition may have greater velocity demands. KEYWORDS Global positioning systems; team sports; data analytics Highlights. This study shows that movement patterns and movement units can be used to investigate team sports through the application of the SMP framework . One hundred and twenty-one movement patterns were found to be present within rugby league match-play, with the walk-and jog-based movement units most prevalent. No movement pattern was unique to a single competition level. . Further analysis revealed that the majority of movement units analysed had significant differences between international and domestic rugby league, whereas only four movement units (i.e. f,m,n,q) had significant differences within the two domestic rugby league levels. . International rugby league had higher occurrences of the movement patterns consisting of higher velocity movement units (ie. T,S,y). This suggests that international rugby league players may need greater high velocity exposure in training.

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