Rugby sevens is a field-based team sport and a derivative of 15-a-side rugby union. Its inclusion in the 2016 Olympic Games has furthered scientific interest in the development and performance of elite players (Henderson et al., 2018). As such, a substantial body of research has quantified the external load demands in Sevens' match-play particularly at elite levels. Studies demonstrate an intermittent high-intensity profile requiring players to recurrently perform bouts of high-speed running and hard acceleration and deceleration actions combined with repeated collisions notably during tackle events (Couderc et al., 2019). This external load varies, albeit not substantially, according to positional group - backs and forwards (Suarez-Arrones et al., 2014). In-match demands are considered intense with a unique interplay of physical, technical, and tactical capacities necessary to play rugby sevens (Ross et al., 2015b). Indeed, research shows that the relative running demands of elite rugby sevens (total distance covered and that travelled at high-speeds per minute of play) are substantially greater than those observed in the elite 15-a-side format: +45% and +135% respectively (Higham et al., 2012). Work has also reported substantially greater high-intensity running demands in international versus lower standard sevens teams (Ross et al., 2015b).
These intense demands can generate fatigue represented by fluctuations in running activity across the course of match-play. Indeed, small to large reductions in locomotor activity (e.g., frequency of intense actions, distances travelled) have generally been observed between the first and second halves (Furlan et al., 2015; Granatelli et al., 2014; Higham et al., 2012; Murray and Varley, 2015; Suarez-Arrones et al., 2014; Couderc et al., 2018). While declines occurred irrespective of score line or opponent ranking (Murray and Varley, 2015), to our knowledge no studies have adjusted data according to effective game time thereby removing the potentially confounding impact of half-to-half differences in stoppage time (for example due to injury or substitutions). Similarly, no studies have tailored competitive running data according to players' individual physical characteristics (e.g., maximal aerobic speed and maximal running speed). If these characteristics are accounted for, a substantial shift in actual external load demands can occur (Reardon et al., 2015).
Finally, to our knowledge, no studies have examined whether there is an accumulation of fatigue over the course of competition represented by a decline in external load metrics towards the end of match-play (e.g., final minute). Similarly, only limited information exists (Furlan et al., 2015) on transient changes in metrics notably collision events following peak periods of activity in rugby sevens and additional research is necessary. The aim of this study therefore was to assess in-match physical performance fluctuations represented by external load in elite rugby sevens players.
This study was conducted over two seasons in male elite players (n = 15, age: 25.8 [+ or -] 3.6 years; height: 1.82 [+ or -] 0.10 m; body mass: 88.9 [+ or -] 13.5 kg) belonging to the French national rugby sevens team participating in the HSBC World Sevens Series (seasons 2012-2013 and 2013-2014). The reference team was ranked 9 and 10th at the end of the 2012-2013 and 2013-2014 World Sevens Series respectively.
Altogether, 32 matches were analyzed for a total of 63 match-observations (players x matches). Only players who completed the entire match were included in the analysis. In order to conduct inter-positional comparisons, players were subdivided into forwards (positions 1 to 3; match observations: n = 29) and backs (positions 4 to 7; n = 34).
To ensure player confidentiality, all performance data were anonymized before the analysis. Prior to participation, all the players received comprehensive verbal and written explanations of the study and gave their written informed consent to participate in conformity with the recommendations of the Declaration of Helsinki. These data arose as a condition of selection for their national team in which player performance was routinely measured over the course of the competitive season (Winter and Maughan, 2009). The Federation Francaise de Rugby granted permission to publish the present data at the end of the 2016/2017 competitive season.
Data collection procedures
Running load: During each match, players wore a portable GPS device (SensorEverywhere, Digital Simulation, France), sampling at 16Hz. This system tracked the movements of the player over the entire course of the match. The GPS system was placed in a customized pocket in their playing shirt and located between the scapulae. To limit potential inter-unit variability, each player wore the same unit for the entire duration of the season. Fifteen minutes prior to the start of each match, the GPS units were activated to ensure clear satellite reception. The data were captured and computed using propriety SensorEverywhere Analyser software (Digital Simulation, France). Data were excluded if one of the following criteria was not met: number of satellites 2 and visual inspection of raw traces of velocity report irregularities (Malone et al., 2017). The mean number of satellites and HDOP during match play were 8 [+ or -] 1 and 1.35 [+ or -] 0.34 respectively. Research conducted to compare the quality of data derived from the present GPS devices in comparison to a gold standard system (radar) has demonstrated a trivial difference for typical error of measurement and small for maximal sprinting speed (0.5, [+ or -]0.1%) and maximal acceleration (3.9, [+ or -]0.6%) respectively (Lacome et al., 2019).
Contact load: An operator coded each contact related action (tackles, collisions, mauls, scrums) using video analysis software (SportsCode, Hudl, USA) to provide a sum for contact events. Active participation in a scrum was judged to be from the front row engagement to break up or when the player was seen to be detached following the release of the ball (Roberts et al., 2008). Active participation in periods of rucking and mauling was timed from when the player's shoulder entered into contact with the ruck or maul to their detachment from the event (Lacome et al., 2014). Tackles were considered actions when a player physically attempted to stop a ball carrier whilst on their feet (Lacome et al., 2014) and collisions were events when physical contact was made between an attacker with a player in the defensive line (Gabbett et al., 2011). The same analysis software was also used to quantify effective playing time (total time the ball was in play) as this contextual factor can strongly influence time-related changes in running and skill-related performance in team sports (Carling and Dupont, 2011).
To verify the reliability of match coding, an intrauser reliability study was conducted. For effective playing time a trivial Typical Error (i.e. TE) was observed (Standardized TE: 0.10 [+ or -] 0.07 (2.0 [+ or -] 1.4%)), while for contact related actions a small TE was obtained (Standardized TE: 0.37 [+ or -] 0.26 (12.2 [+ or -] 9.6%)).
Data processing: To synchronize running and contact load data, a timestamp marker was created both in the GPS and video analysis software at match kick-off (when the ball hit the ground). This synchronization enabled importation of contact-related data derived from the Sports-code software into the propriety GPS software. Data collected during stoppage time were not included in the analysis to facilitate in- (halves) and between-match comparisons.
Individual values for maximal aerobic speed (MAS) and maximal sprinting speed (MSS) were used to adjust data for high and very-high speed running thresholds. MAS was determined using an intermittent progressive running test adapted from the test...