Match-related statistics discriminating between playing positions during the men’s 2011 Rugby World Cup

Villarejo, Diego; Palao, José-Manuel; Ortega, Enrique; Gómez-Ruano, Miguel-Ángel; Kraak, Wilbur

doi:10.1080/24748668.2015.11868779

Cited by 13 publications

(23 citation statements)

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“…Performance indicator research is important as it allows for sport performance to be measured empirically. It has been conducted in various sports such as soccer (Castellano and Casamichana & Lago, 2012;Jones, James & Mellalieu, 2004;Lago-Peñas, Lago-Ballesteros & Rey, 2011), rugby union (Bishop & Barnes, 2013;Hughes, Hughes, Williams, James, Vučković & Locke, 2012;Villarejo, Palao, Ortega, Gomez-Ruano & Kraak, 2015) and basketball (Csataljay, O'Donoghue, Hughes & Dancs, 2009;Gómez, Lorenzo, Ibañez & Sampaio, 2013;Puente, Coso & Salinero, 2015). However, few papers have analysed performance indicators in rugby league (Parmar, James, Hughes, Jones and Hearne, 2017;Woods, Leicht, Jones and Till, 2018;Woods, Sinclair & Robertson, 2017).…”

Section: Introductionmentioning

confidence: 99%

Using principal component analysis to develop performance indicators in professional rugby league

Parmar

James

Hearne

et al. 2018

International Journal of Performance Analysis in Sport

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Section: Introductionmentioning

confidence: 99%

Using principal component analysis to develop performance indicators in professional rugby league

Parmar

James

Hearne

et al. 2018

International Journal of Performance Analysis in Sport

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“… 0 5 [ 71 , 83 , 84 , 93 , 94 ] 2 [ 68 , 85 ] Performance—what Complete season/tournament? 12 [ 13 – 15 , 18 , 20 , 21 , 51 , 55 , 57 , 75 , 97 , 108 ] 9 [ 56 , 58 , 86 , 87 , 95 , 96 , 98 – 100 ] Is the research from a one-off tournament(s)? 8 [ 55 – 57 , 87 , 95 , 97 , 99 , 100 ] 13 [ 13 – 15 , 18 , 20 , 21 , 51 , 58 , 75 , 86 , 96 , 98 , 108 ] Includes data from more than one season/tournament?…”

Section: Main Textmentioning

confidence: 99%

“… 12 [ 13 – 15 , 18 , 20 , 21 , 51 , 55 , 57 , 75 , 97 , 108 ] 9 [ 56 , 58 , 86 , 87 , 95 , 96 , 98 – 100 ] Is the research from a one-off tournament(s)? 8 [ 55 – 57 , 87 , 95 , 97 , 99 , 100 ] 13 [ 13 – 15 , 18 , 20 , 21 , 51 , 58 , 75 , 86 , 96 , 98 , 108 ] Includes data from more than one season/tournament? 11 [ 13 – 15 , 18 , 20 , 21 , 51 , 58 , 75 , 96 , 108 ] 10 [ 55 …”

Section: Main Textmentioning

confidence: 99%

The what and how of video analysis research in rugby union: a critical review

et al. 2018

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BackgroundVideo analysis is a common tool used in rugby union research to describe match performance. Studies using video analysis range from broad statistical studies of commercial databases to in-depth case-studies of specific match events. The range of types of studies using video analysis in rugby union, and how different studies apply the methodology, can make it difficult to compare the results of studies and translate the findings to a real-world setting. In attempt to consolidate the information on video analysis in rugby, a critical review of the literature was performed.Main bodyNinety-two studies were identified. The studies were categorised based on the outcome of the study and the type of research question, sub-categorised as ‘what’ and ‘how’ studies. Each study was reviewed using a number of questions related to the application of video analysis in research.There was a large range in the sample sizes of the studies reviewed, with some of the studies being under-powered. Concerns were raised of the generalisability of some of the samples. One hundred percent of ‘how’ studies included at least one contextual variables in their analyses, with 86% of ‘how’ studies including two or more contextual variables. These findings show that the majority of studies describing how events occur in matches attempted to provide context to their findings. The majority of studies (93%) provided practical applications for their findings.ConclusionThe review raised concerns about the usefulness of the some of the findings to coaches and practitioners. To facilitate the transfer and adoption of research findings into practice, the authors recommend that the results of ‘what’ studies inform the research questions of ‘how’ studies, and the findings of ‘how’ studies provide the practical applications for coaches and practitioners.Electronic supplementary materialThe online version of this article (10.1186/s40798-018-0142-3) contains supplementary material, which is available to authorized users.

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“…A player match impact (or efficacy) weighting, similar to that devised by Lim et al (2009) is a key aspect of this study. Villarejo et al (2015) used performance indicators to measure the characteristics of player performance by position in winning and losing teams. The data were gathered from all 48 matches of the Rugby World Cup in 2011.…”

Section: Nonementioning

confidence: 99%

“…This study grouped the out-half with the centre positions, as opposed to the study by Lim et al (2009) who considered the positions individually, restricting the ability to compare data between them. The large number of games analysed by Villarejo et al (2015), whilst providing greater data stability, may also obscure important data due to a number of mismatches during that tournament. The average points gap in matches between tier one and tier two nations was 20 points, and seven games had a winning margin of greater than 50 points (World Rugby, Formerly International Rugby Board, 2011), therefore the importance of specific performance indicators to match outcome may change, relative to the strength of the opponents.…”

Section: Nonementioning

confidence: 99%

Profiling half-back play in rugby union and the impact of substitutions

Hughes

Smyth

2018

jhse

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An exploratory method of quantifying the impact of individual players in rugby union was developed and applied to both half-back positions in 2015 Rugby World Cup matches with a view to firstly test the validity of these systems by profiling players, and secondly, if successful, to assess the impact of substitutions. A match impact scoring system was devised using questionnaire responses of an expert group of professional rugby analysts and experienced international coaches. The scoring system weighted each game action in a positive or negative manner according to the impact on team performance. It was found that the proposed method produced valid and reliable data concerning player performance. It was applied to half-backs substituted with more than 20 mins playing time left, the two 20 min period, before and after substitution, were compared. A "non-substituted" control group were also analysed, in both the first and final 20 minutes of competition. It was found that for the scrum-half position, the starting players produced a higher median 'efficacy' score than replacement players 27.46, (std. dev. +10.06) and 20.42, (+12.45). The best performing scrum-half group were the 60-80-minute non-replaced players 29 (+9.0). For the out-half position, it was found that the highest median 'efficacy' was achieved by the replacement player group 18.80, (+ 11.00), with the non-replaced 60-80-minute group performing worst 14.40, (+ 7.09). Future research should develop the methods applied in this study to define player profiles for each position on the rugby field. It is suggested that these profiles should use score difference between the teams to take into account the strength of the teams involved. The concept of a weighted individual player efficacy system has been demonstrated in the sport of rugby union, but could be applied in any team sport where greater individual player performance data is required.

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Match-related statistics discriminating between playing positions during the men’s 2011 Rugby World Cup

Cited by 13 publications

References 2 publications

Using principal component analysis to develop performance indicators in professional rugby league

Using principal component analysis to develop performance indicators in professional rugby league

The what and how of video analysis research in rugby union: a critical review

Profiling half-back play in rugby union and the impact of substitutions

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