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      Operational Insights into Analysing Team and Player Performance in Elite Rugby League: A Narrative Review with Case Examples

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          Abstract

          In professional team sports, like Rugby League, performance analysis has become an integral part of operational practices. This has helped practitioners gain deeper insight into phenomena like team and athlete behaviour and understanding how such behaviour may be influenced by various contextual factors. This information can then be used by coaches to design representative practice tasks, inform game principles and opposition strategies, and even support team recruitment practices. At the elite level, the constant evolution of sports technology (both hardware and software) has enabled greater access to information, making the role of the performance analyst even more valuable. However, this increase in information can create challenges regarding which variables to use to help guide decision-making, and how to present it in ways that can be utilised by coaches and other support staff. While there are published works exploring aspects of performance analysis in team sports like Rugby League, there is yet to be a perspective that explores the various operational uses of performance analysis in Rugby League, the addition of which could help guide the practices of emerging performance analysts in elite organisations like the Australian National Rugby League and the European Super League. Thus, this narrative review—with accompanying case examples—explores the various ways performance analysis can help address pertinent operational questions commonly encountered when working in high-performance sport.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40798-022-00535-7.

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          Random Forests

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            An Introduction to Logistic Regression Analysis and Reporting

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              Evolution of match performance parameters for various playing positions in the English Premier League.

              This study aimed to investigate position-specific evolution of physical and technical performance parameters in the English Premier League (EPL). Match performance observations (n=14700) were collected using a multiple-camera computerized tracking system across seven seasons (2006-07 to 2012-13). Data were analyzed relative to five playing positions: central defenders (n=3792), full backs (n=3420), central midfielders (n=3200), wide midfielders (n=2136) and attackers (n=2152). High-intensity running distance increased in the final season versus the first season in all playing positions (p<.05, ES: 0.9-1.3) with full backs displaying the greatest increase (∼36% higher in 2012-13). Similar trends were observed for sprint distance with full backs demonstrating the most pronounced increase across the seven seasons (36-63%, p<.001, ES: 0.8-1.3). Central players (central defenders and midfielders) illustrated the most pronounced increases in total passes and pass success rate (p<.05, ES: 0.7-0.9) whilst wide players (full backs and wide midfielders) demonstrated only small-moderate increases in total passes and pass success rate (p<.05, ES: 0.6-0.8). The data demonstrates that evolving tactics in the EPL have impacted on the physical demands of wide players and the technical requirements of central players. These findings could be used for talent identification or position-specific physical and technical training.
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                Author and article information

                Contributors
                corey.wedding@my.jcu.edu.au
                Journal
                Sports Med Open
                Sports Med Open
                Sports Medicine - Open
                Springer International Publishing (Cham )
                2199-1170
                2198-9761
                3 December 2022
                3 December 2022
                December 2022
                : 8
                : 140
                Affiliations
                [1 ]GRID grid.1011.1, ISNI 0000 0004 0474 1797, Sport and Exercise Science, , James Cook University, ; Townsville, QLD Australia
                [2 ]North Queensland Cowboys Rugby League Football Club, Townsville, QLD Australia
                [3 ]GRID grid.1019.9, ISNI 0000 0001 0396 9544, Institute for Health and Sport, , Victoria University, ; Melbourne, Australia
                Author information
                http://orcid.org/0000-0001-5070-2869
                http://orcid.org/0000-0002-7129-8938
                http://orcid.org/0000-0002-0125-0111
                http://orcid.org/0000-0002-0537-5392
                Article
                535
                10.1186/s40798-022-00535-7
                9719574
                36462122
                abe00d50-d711-41ed-a2c0-57f2da3ee377
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 1 November 2021
                : 15 November 2022
                Categories
                Review Article
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                © The Author(s) 2022

                rugby league,data analysis,performance analysis,team sport,sports technology

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