Analyzing Volleyball Data on a Compositional Regression Model Approach: An Application to the Brazilian Men's Volleyball Super League 2011/2012 Data

TL;DR

This paper introduces a novel compositional regression model approach for analyzing volleyball match data, demonstrating its effectiveness through simulation and application to the Brazilian Men's Volleyball Super League 2011/2012.

Contribution

It develops a new compositional data regression methodology tailored for volleyball performance analysis, with estimation via maximum likelihood and validation through real data application.

Findings

Effective modeling of volleyball data using compositional regression.

Simulation confirms accuracy of the estimation procedure.

Application to real data illustrates practical utility.

Abstract

Volleyball has become a competitive sport with high physical and technical performance. Matches results are based on the players and teams'skills as technical and tactical strategies to succeed in a championship. At this point, some studies are carried out on the performance analysis of different match elements, contributing to the development of this sport. In this paper, we proposed a new approach to analyze volleyball data. The study is based on the compositional data methodology modeling in regression model. The parameters are obtained through the maximum likelihood. We performed a simulation study to evaluate the estimation procedure in compositional regression model and we illustrated the proposed methodology considering real data set of volleyball.