EconPapers    
Economics at your fingertips  
 

Identifying keys to win in the Chinese professional soccer league

Lijuan Mao, Zhaofang Peng, Hongyou Liu and Miguel-Angel Gómez

International Journal of Performance Analysis in Sport, 2016, vol. 16, issue 3, 935-947

Abstract: Quantifying correlations between soccer match statistics and match results is an effective way to identify key performance indicators of soccer competitions. In the current study, generalized linear modelling was employed to identify relationships between 21 performance-related variables and the match outcome (win, draw, loss). Data of all the 480 matches of the 2014 and 2015 season in the Chinese Football Association Super League were collected and analyzed. The cumulative logistic regression was run in the modelling taking the value of each performance-related variable as an independent variable to predict the logarithm of the odds of winning. Relationships were evaluated with magnitude-based inferences and were expressed as effects of a two-standard-deviation increase in the value of each variable on the change in the probability of a team winning a match. Modelling was performed in four match contexts of team and opposition end-of-season rank (classified as upper and lower ranked teams). Shot on Target (positive), Shot Accuracy (positive), Cross Accuracy (trivial), Tackle (trivial) and Yellow Card (trivial) were the five variables that showed consistent effects in all four match contexts, other effects varied depending on the strength of team and opposition. Quantified relationships can provide useful information to coaches and performance analysts in practice of different match scenarios.

Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/24748668.2016.11868940 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:rpanxx:v:16:y:2016:i:3:p:935-947

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RPAN20

DOI: 10.1080/24748668.2016.11868940

Access Statistics for this article

International Journal of Performance Analysis in Sport is currently edited by Peter O'Donoghue

More articles in International Journal of Performance Analysis in Sport from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:rpanxx:v:16:y:2016:i:3:p:935-947