THE USE OF CLASSIFICATION AND REGRESSION TREE WHEN CLASSIFYING WINNING AND LOSING BASKETBALL TEAMS
Abstract
The aim of the present study was to identify the best predictors when classifying winning and losing
teams in basketball in consideration of situational variables by the classification and regression tree (CRT) non-parametric analysis. The sample was composed of 1,404 balanced games (score-differences: 1-14 points) from the Spanish EBA Basketball League that presented high heterogeneity and a non-parametric distribution. These games were split into faster- and slower-paced games according to ball possessions per game (using a cluster k-means). The CRT analysis was used to predict which game-related variable/s better classified winning and losing teams during slower- and faster-paced games. In total, this approach explained 72% of the total variance in the slower- and 69.3% in the faster-paced games. The results identified importance of defensive rebounds (100%), successful free-throws (94.7%), assists (86.1%), and fouls committed (55.9%) for the classification of winning and losing teams in the fast-paced games. Conversely, in the slow-paced games the better classification of winning or losing teams was accomplished by the following variables: successful free-throws (100%), defensive rebounds (82.3%), fouls committed (68.4%), assists (66.9%), successful 2- point (62.2%) and 3-point field-goals (61.6%). The influence of situational variables was identified only for team quality in the slow-paced games. The present findings allow coaches for a better control of games and competition.
Key words: classification and regression tree, performance analysis, team sport, match analysis
Downloads
How to Cite
Issue
Section
License
Copyright (c) 2017 Kinesiology
![Creative Commons License](http://i.creativecommons.org/l/by/4.0/88x31.png)
This work is licensed under a Creative Commons Attribution 4.0 International License.
At Faculty of Kinesiology we recognize that access to quality research is vital to the scientific community and beyond. Kinesiology is non-profit journal and all costs of publishing and peer review process are covered by the publisher itself or other funding sources like Ministry of Science and Education of the Republic of Croatia. Full text papers are also available free of charge at http://hrcak.srce.hr/kineziologija. There are no restrictions on self archiving of any form of paper (preprint, postprint and publisher's version).
Articles are distributed under the terms of the CC BY - NC 4.0
Kinesiology does not charge any fees to authors to submit or publish articles in our journal.