Title: | Discriminatory Power of Women’s Handball Game-Related Statistics at the Olympic Games (2004-2016) |
Author: |
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Date: | 2018-06-13 |
Language: | English |
Scope: | 221-229 |
University/Institute: | University of Iceland Háskóli Íslands Háskólinn í Reykjavík Reykjavik University |
School: | Menntavísindasvið (HÍ) School of Education (UI) Tækni- og verkfræðideild (HR) School of Science and Engineering (RU) |
Department: | Faculty of Health Promotion, Sports and Leisure Studies (UI) Deild heilsueflingar, íþrótta og tómstunda (HÍ) |
Series: | Journal of Human Kinetics;62(1) |
ISSN: | 1899-7562 |
DOI: | 10.1515/hukin-2017-0172 |
Subject: | Handbolti; Kvennaíþróttir; Performance analysis; Notational analysis; Discriminant analysis; Match analysis; Goalkeeper; Markvarsla |
URI: | https://hdl.handle.net/20.500.11815/1838 |
Citation:Saavedra, J. M., Þorgeirsson, S., Chang, M., Kristjánsdóttir, H., & García-Hermoso, A. (2018). Discriminatory Power of Women’s Handball Game-Related Statistics at the Olympic Games (2004-2016). Journal of Human Kinetics, 62, 221–229. https://doi.org/10.1515/hukin-2017-0172
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Abstract:Sports performance analysis has been a growing field of study in the last decade. However, the number of studies in handball is small. The aims of this present study were (i) to compare handball game-related statistics by the match outcome (winning and losing teams) and (ii) to identify characteristics that discriminated performance in elite women’s handball. The game-related statistics of the 236 matches played in the last four Olympic Games (Athens, Greece, 2004; Beijing, China, 2008; London, United Kingdom, 2012; and Rio de Janeiro, Brazil, 2016) were analysed. Differences between match outcomes (winning or losing teams) were determined using the chi-squared statistic, also calculating the effect sizes of the differences. A discriminant analysis was then performed applying the sample-splitting method according to match outcomes. The results showed the differences between winning and losing teams were red cards and assists. Also, the discriminant analysis selected five variables (shots, goalkeeper-blocked shots, technical fouls, steals, and goalkeeper-blocked fast-break shots) that classified correctly 83% of matches. The selected variables included offensive and defensive predictors. Coaches and players can use these results as a reference against which to assess their performance and plan training.
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Rights:CC -NC-ND 3.0
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