Team performance indicators that predict match outcome and points difference in professional rugby league
Article
Parmar, N., James, N., Hughes, M., Jones, H. and Hearne, G. 2017. Team performance indicators that predict match outcome and points difference in professional rugby league. International Journal of Performance Analysis in Sport. 17 (6), pp. 1044-1056. https://doi.org/10.1080/24748668.2017.1419409
Type | Article |
---|---|
Title | Team performance indicators that predict match outcome and points difference in professional rugby league |
Authors | Parmar, N., James, N., Hughes, M., Jones, H. and Hearne, G. |
Abstract | Performance indicators allow for the objective quantification of performance, however, limited PI research for professional rugby league exists. Therefore, this paper assessed 24 relative PIs (home value minus away) from all 27 rounds of the 2012, 2013 and 2014 European Super League seasons, collected by Opta, amounting to 567 matches. Backwards logistic (match outcome) and linear (points difference) regression models were used alongside exhaustive Chi-Square Automatic Interaction Detection decision trees to identify performance indicators (PIs) and key performance indicators. Teams had a higher chance of winning and would gain more points when they scored first (OR = 1.6, β = 2.4) and increased completed sets (OR = 1.2, β = 1.2) by one unit. Conversely, teams had a lower chance of winning when they increased scoots (OR = 0.9, β = −0.2). However, some PIs which were thought to be important (as identified by previous literature) were removed from the analysis thus calling into question the appropriateness of stepwise methods. Future research may consider utilising dimension reduction techniques when analysing large data-sets that encompass multiple variables. |
Keywords | Performance indicators; rugby league; regression; decision trees |
Research Group | Performance Analysis at the London Sport Institute |
Publisher | Taylor & Francis (Routledge) |
Journal | International Journal of Performance Analysis in Sport |
ISSN | 2474-8668 |
Electronic | 1474-8185 |
Publication dates | |
Online | 10 Jan 2018 |
02 Nov 2017 | |
Publication process dates | |
Deposited | 23 Jan 2018 |
Submitted | 22 Nov 2017 |
Accepted | 17 Dec 2017 |
Output status | Published |
Accepted author manuscript | |
Copyright Statement | This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Performance Analysis in Sport on 10/01/2018, available online: http://www.tandfonline.com/10.1080/24748668.2017.1419409 |
Digital Object Identifier (DOI) | https://doi.org/10.1080/24748668.2017.1419409 |
Web of Science identifier | WOS:000424788000017 |
Language | English |
https://repository.mdx.ac.uk/item/876q0
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