Rugby sevens is a complex team sport requiring a combination of fitness and physical ability (Higham et al., 2012; 2013), execution of technical skills (Meir, 2012), and tactical and strategic considerations (Hughes and Jones, 2005) for success at the international level. The dynamic match environment can make it difficult for coaches and support staff to identify which elements of physical, technical, and tactical development to target to enhance the probability of successful performance. Match analysis is often used to provide an objective and unbiased record of team activity to assess and monitor performance. However, it is unclear which performance indicators should be monitored to evaluate team performance in rugby sevens.
A performance indicator is a variable that characterizes some aspect of performance (Hughes and Bartlett, 2002). To be meaningful and useful, performance indicators should be related to a successful performance outcome. Research is required to characterize the technical and tactical aspects of team play related to successful performance in rugby sevens. In team sports such as rugby sevens, the primary criterion for assessing a team's performance is the match outcome, determined by the points scored by each team. The final point difference, that is, the margin of victory or loss, provides important contextual information relating to how well matched the competing teams are and the relative success of the tactics and strategies employed. Team performance indicators should therefore be considered in relation not only to winning (Jones et al., 2004; Ortega et al., 2009), but also points scored in close matches (Vaz et al., 2011; Vaz et al., 2010).
Team performance indicators describing individual or collective skills or match events may fluctuate as a function of situational variables such as, environmental conditions, officiating style, and each team's technical strengths and weaknesses (Taylor et al., 2008). Analyses of limited data sets, such as those of a single tournament or team, may be heavily influenced by these variables and not truly representative of international-level competition. By analyzing a large sample of matches from different national teams, played under varying conditions, issues related to match volatility are minimized and performance indicators commonly associated with successful performances can be identified.
Identifying performance indicators related to scoring points and winning in rugby sevens is useful to develop reference values for international matches. These values can be used by coaches and support staff to inform practical guidelines for technical and tactical development. Reference values can assist in understanding the variability of team performance, and aid coaches in establishing quantifiable objectives for training and competition performance, as well as aid in evaluating the efficacy of training interventions and tactical changes. Knowledge of performance indicators can also be used to create performance profiles to predict team behaviors and performance outcomes. The purpose of this study was to characterize common team performance indicators in international rugby sevens matches and calculate the typical within-team variability and between-team differences in these values. The effect of changes or differences in performance indicators on points scoring and probability of winning within and between teams was then quantified.
Match statistics from 196 men's international matches played over four tournaments of the 2011/2012 International Rugby Board (IRB) Sevens World Series were analyzed. Match data were retrieved from the official IRB tournament website (http://www.irbsevens.com). Team performance indicators representing totals of a given event for each team in each match were divided into four categories: match development, scoring, set-piece play, and phase play (Table 1). Match development indicators described the time with the ball and number of law infringements for a given team. Scoring indicators described the number of points scored or conceded and the way and frequency in which points were scored. Set-piece play indicators described the frequency and outcome of line-outs thrown, scrums fed and restarts kicked by the team. Phase play indicators described how the team used the ball when in possession. The performance indicators were analyzed as absolute values and as values standardized per min of possession time or per try scored.
Data were imported into the Statistical Analysis System (version 9.3, SAS Institute, Cary, NC) for analysis. Mean values and true between-team and within-team standard deviation (SD) for common team performance indicators were calculated using a mixed-model reliability analysis with a random effect for team. Mean values were estimated as the intercept of the model with the between-team standard deviation calculated from the random effect, and the within-team standard deviation calculated from the residual variance. A standard deviation representing observed between-team match-to-match typical differences was calculated as the square root of the sum of the true between-team and within-team variances. Intra-class correlation coefficients representing match-to-match reliability of performance indicators were calculated as the true between-team variance divided by the observed between-team variance.
Performance indicators representing events occurring on average more than once per match, and not directly representing points-scoring actions, were further analyzed for their relationship with points scored by a team and the probability of winning. A mixed model with the performance indicator as a linear fixed effect, a random effect for team, and an interaction effect for performance indicator and team, was employed to characterize the relationship between the performance indicator and points scored within each team. This model allowed for the possibility of individual team differences in the relationship between the performance indicator and points scored. An additional interaction effect for team and the tournament at which matches were played, allowing for individual team differences in the relationship at different tournaments, was removed from the model because it explained no additional variance in points scored. A linear relationship between performance indicators and points scored was deemed appropriate after assessment of a quadratic trend yielded no additional meaningful information. A linear model was also favored for its simpler interpretation. The effect of a change within a team in performance indicator value on points scored was assessed by multiplying the slope of the relationship by two within-team standard deviations (Hopkins et al., 2009). Two standard deviations represents the change within a team from a typically low performance indicator value (-1 SD) to a typically high value (+1 SD).
A between-team effect of...