Game-play characteristics differ between the European Super League and the National Rugby League: Implications for coaching and talent recruitment

Abstract

Objectives To compare the game-play characteristics between the European Super League and the National Rugby League competitions. Methods Eleven team performance indicators were extracted from each match played by every European Super League and National Rugby League team over their respective 2016 season. Data were averaged, classified according to competition (two levels: European Super League and National Rugby League) and modelled using univariate and multivariate techniques. Specifically, effect size statistics enabled between group comparisons, while non-metric multidimensional scaling enabled multivariate insights into competition dissimilarity. Results Seven of the 11 performance indicators showed ‘large’ to ‘very large’ effects. Notably, National Rugby League game-play generated fewer ‘line breaks’, ‘errors’, ‘tackles’ and ‘dummy half runs’ relative to European Super League game-play ( d > 1.2). Despite the National Rugby League generating fewer ‘all runs’ ( d = 1.27 [0.57–1.95]), game-play in this competition generated greater ‘all run distances’ relative to the European Super League ( d = 1.78 [1.02–2.51]). Non-metric multidimensional scaling revealed clear multivariate competition dissimilarity, with European Super League and National Rugby League teams orienting distinctive positions on the ordination surface. Further, there was a greater spread in the relative positioning of National Rugby League teams compared to European Super League teams, indicating greater team dissimilarity within the National Rugby League. Conclusions Our observations may be explained by differing competition rule interpretations, in addition to differing game strategies and player skill capabilities. Both coaches and talent recruitment managers associated with these competitions may consider our data to assist with the identification and recruitment of suitable players from these respective competitions.

Quantifying the Collision Dose in Rugby League: A Systematic Review, Meta-analysis, and Critical Analysis

“…From these 39 studies, participants were drawn from teams in the NRL, SL, Australian State Leagues (predominantly the Queensland Cup [QCup]), International, Australian Under 20's National Youth Competition (NYC), and amateur competitions (see Table 2). The remaining four studies reported on participants with collisions analysed via video footage at the competition level [1,28,41,68].…”

“…Of the studies that compared cohorts between competition standards, one study compared cohorts from the NRL to Qcup [71], one study compared NRL cohorts to NSWCup [32], two studies compared NRL to SL [1,65], two studies compared NRL to NYC [23,68], and one study compared international to NRL [41]. Studies typically compared the collision dose either at the overall team level or within positional groupings.…”

“…Four studies reported on absolute collision frequency at the game or competition level via video notational analysis [1,28,41,68] (see Table 3). At the competition level, there were differences between the frequency of collisions undertaken within NRL and SL matches, with SL teams completing more ball carries per match, with a relatively similar tackle load [1]. Furthermore, Woods et al identified that NRL teams complete a greater number of tackles and ball carries when compared to their NYC counterparts [68].…”

“…Rugby league is an invasion contact sport played in over 14 countries, in which senior male rugby league consists of two 40-min halves [1]. A match is contested by 13 players on two opposing teams.…”

The Performance Evolution of Match Play Styles in the Spanish Professional Basketball League

“…Prior studies have employed multivariate modelling such as nMDS to investigate match play differences across seasons and/or competitions in various sports such as Netball [18], Rugby League [19] and Australian Football [16]. This non-linear approach has clearly shown the idiosyncrasy of teams' performances and provided a unique examination and visualization of sporting evolution [16,18,19]. Further, it has identified team adaptations employed by successful teams that could be utilised by others to enhance future success [18,19].…”