Performance indicators that predict success in an English professional League One soccer team

2.50
Hdl Handle:
http://hdl.handle.net/2436/344343
Title:
Performance indicators that predict success in an English professional League One soccer team
Authors:
Harrop, Kerys; Nevill, Alan M.
Abstract:
The purpose of the present study was to identify performance indicators that may discriminate between games a soccer team won, drew and lost. A second aim was to identify those variables that best predict success for the team. The sample comprised of 46 matches played by a League One soccer team during the 2012-2013 domestic season. Offensive and defensive game-related statistics were gathered Match location was also considered. A Kruskal Wallis test and binary logistic regression were used to identify those indicators associated with success (wins). The Kruskal Wallis test identified significant differences in the number of passes, percentage of successful passes and passes made in the opposition half Significantly more passes and passes in the opposition half were made when the team lost compared to when they won and drew games (P<0.05). A significantly lower percentage of successful passes were completed when the team drew (P<0.05). The results of the binary logistic regression concluded that the team should perform fewer passes and dribbles but complete more successful passes and shots to be successful. The results indicate that for the team to be successful they should implement a direct style of play.
Citation:
International Journal of Performance Analysis in Sport, Volume 14, Number 3, December 2014, pp. 907-920(14)
Publisher:
University of Wales Institute, Cardiff
Journal:
International Journal of Performance Analysis in Sport
Issue Date:
Dec-2014
URI:
http://hdl.handle.net/2436/344343
Additional Links:
http://www.ingentaconnect.com/content/uwic/ujpa/2014/00000014/00000003/art00020
Type:
Article
Language:
en
ISSN:
1474-8185
Appears in Collections:
Sport, Exercise and Health Research Group

Full metadata record

DC FieldValue Language
dc.contributor.authorHarrop, Kerysen_GB
dc.contributor.authorNevill, Alan M.en_GB
dc.date.accessioned2015-02-10T14:17:22Z-
dc.date.available2015-02-10T14:17:22Z-
dc.date.issued2014-12-
dc.identifier.citationInternational Journal of Performance Analysis in Sport, Volume 14, Number 3, December 2014, pp. 907-920(14)en_GB
dc.identifier.issn1474-8185-
dc.identifier.urihttp://hdl.handle.net/2436/344343-
dc.description.abstractThe purpose of the present study was to identify performance indicators that may discriminate between games a soccer team won, drew and lost. A second aim was to identify those variables that best predict success for the team. The sample comprised of 46 matches played by a League One soccer team during the 2012-2013 domestic season. Offensive and defensive game-related statistics were gathered Match location was also considered. A Kruskal Wallis test and binary logistic regression were used to identify those indicators associated with success (wins). The Kruskal Wallis test identified significant differences in the number of passes, percentage of successful passes and passes made in the opposition half Significantly more passes and passes in the opposition half were made when the team lost compared to when they won and drew games (P<0.05). A significantly lower percentage of successful passes were completed when the team drew (P<0.05). The results of the binary logistic regression concluded that the team should perform fewer passes and dribbles but complete more successful passes and shots to be successful. The results indicate that for the team to be successful they should implement a direct style of play.en_GB
dc.language.isoenen
dc.publisherUniversity of Wales Institute, Cardiffen_GB
dc.relation.urlhttp://www.ingentaconnect.com/content/uwic/ujpa/2014/00000014/00000003/art00020en_GB
dc.titlePerformance indicators that predict success in an English professional League One soccer teamen
dc.typeArticleen
dc.identifier.journalInternational Journal of Performance Analysis in Sporten_GB
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