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International Journal of Performance Analysis in Sport Volume 17, 2017 - Issue 6
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Research Articles

Team performance indicators that predict match outcome and points difference in professional rugby league

Nimai ParmarLondon Sport Institute, Faculty of Science and Technology, Middlesex University, London, UKCorrespondence[email protected]
ORCID Iconhttp://orcid.org/0000-0001-5540-123X
ORCID Icon,
Nic JamesLondon Sport Institute, Faculty of Science and Technology, Middlesex University, London, UKORCID Iconhttp://orcid.org/0000-0002-4181-9501
ORCID Icon,
Mike HughesCentre for Performance Analysis, ITC, Carlow, Ireland
,
Huw JonesNatural Sciences, Faculty of Science and Technology, Middlesex University, London, UK
&
Gary HearneDesign Engineering & Mathematics, Faculty of Science and Technology, Middlesex University, London, UK
Pages 1044-1056 | Received 22 Nov 2017, Accepted 17 Dec 2017, Published online: 10 Jan 2018

Citations (8)

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Nimai Parmar, Nic James, Gary Hearne & Ben Jones. (2018) Using principal component analysis to develop performance indicators in professional rugby league. International Journal of Performance Analysis in Sport 18:6, pages 938-949.
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Articles from other publishers (7)

C. J. Wedding, M. A. Gomez, C. T. Woods, W. H. Sinclair & A. S. Leicht. (2022) Effect of match-related contextual factors on positional performance in the national rugby league. International Journal of Sports Science & Coaching 18:3, pages 832-838.
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Corey James Wedding, Carl Thomas Woods, Wade Heath Sinclair & Anthony Scott Leicht. (2022) Operational Insights into Analysing Team and Player Performance in Elite Rugby League: A Narrative Review with Case Examples. Sports Medicine - Open 8:1.
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Gordon Rennie, Dan Weaving, Brian Hart, Nicholas Dalton-Barron & Ben Jones. (2022) Tackle and ball carrier demands of rugby league: a seven-year league-wide study including over 1,000,000 tackle events. Journal of Science and Medicine in Sport 25:10, pages 850-854.
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Marcos Roberto Brasil, Aruacã Gelli Rocha Ferreira da Silva, Vinicius Machado de Oliveira, Angelica Miki Stein, Timothy Gustavo Cavazzotto & Ana Carolina Paludo. (2022) Análise de desempenho da seleção brasileira de voleibol masculina: Análise da participação na II Liga das Nações. Educación Física y Ciencia 24:2, pages e218.
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Tianyu Guan, Robert Nguyen, Jiguo Cao & Tim Swartz. (2022) In-game win probabilities for the National Rugby League. The Annals of Applied Statistics 16:1.
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Alexandru Nicolae Ungureanu, Corrado Lupo & Paolo Riccardo Brustio. (2021) A Machine Learning Approach to Analyze Home Advantage during COVID-19 Pandemic Period with Regards to Margin of Victory and to Different Tournaments in Professional Rugby Union Competitions. International Journal of Environmental Research and Public Health 18:23, pages 12711.
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Sebastian Wenninger, Daniel Link & Martin Lames. (2020) Performance of machine learning models in application to beach volleyball data.. International Journal of Computer Science in Sport 19:1, pages 24-36.
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