A comparison of performance indicators between the four South African teams and the winners of the 2005 Super 12 Rugby competition. What separates top from bottom?
Authors: Prim, Sebastian; van Rooyen, Michele; Lambert, Michael
Source: International Journal of Performance Analysis in Sport, Volume 6, Number 2, November 2006 , pp. 126-133(8)
Publisher: University of Wales Institute, Cardiff
Abstract:The South African regional teams participating in the Super 12 rugby union competition seem to under-perform compared to the performance of the national team in the Tri-Nations competition against similar Australasian opposition. The aim of this study was to compare various performance parameters between the four South African Super 12 teams (Bulls, 3rd position; Stormers, 9th position; Cats, 11th position; and Sharks, 12th position) and the eventual winners, the Crusaders from New Zealand. Nine games from the 2005 Super 12 season were analysed. These nine games included the four South African teams playing against the Crusaders and against each other (one game, Stormers v Sharks, was lost due to technical problems). All game analyses were performed after the tournament using a digital analysis software program (Sportscode Elite version 5.4.24, Sportstec, Australia). Ball possession, tries scored and various performance indicators associated with successful ball retention and attacking effectiveness in the tackle situation (as obtained through a panel of elite coaches and analysts) were quantified.
There were no statistically significant differences between the teams for the total amount of ball possession per match (Crusaders 1057±216s, Bulls 1048±158s, Cats 852±73s, Sharks 1078±84s and Stormers 984±186s) or time of each movement involving ball possession (Crusaders 15.2±3.0s, Bulls 15.5±1.9s, Cats 13.0±1.0s, Sharks 16.9±2.3s and Stormers 15.0±3.8s). There were no significant differences between the number of tries scored (Crusaders 6±4, Bulls 4±3, Cats 3±1, Sharks 3±2 and Stormers 2±1 tries), number of offloads (Crusaders 19±12, Bulls 12±4, Cats 13±5, Sharks 15±4 and Stormers 17±5 offloads), turnovers won (Crusaders 3±3, Bulls 4±2, Cats 5±1, Sharks 2±1 and Stormers 5±1 turnovers) or conceded (Crusaders 4±1, Bulls 3±2, Cats 4±2, Sharks 5±1 and Stormers 6±2 turnovers). There were no statistically significant differences between the number of times the different teams committed 0, 1, 2 or 3 support players when they were tackled. There were also no statistical differences in the number of times the various teams committed 0, 1, 2 and 3 support players to counter-ruck once they had made a tackle.
Due to the relatively small sample size, there is a risk of making a type II error (i.e. missing significant differences) between the variables analysed. However when these data are inspected using a visually striking box and whisker plot, there are noticeable differences between the styles of play of the teams. Future studies should investigate whether this form of data analysis is valid, particularly when having to give feedback to coaches of elite teams, involving analyses in which the sample size may always lack statistical power.
Document Type: Research Article
Publication date: November 1, 2006