The role of passing network indicators in modeling football outcomes: an application using Bayesian hierarchical models

Abstract

Passes are undoubtedly the more frequent events in football and other team sports. Passing networks and their structural features can be useful to evaluate the style of play in terms of passing behavior, analyzing and quantifying interactions among players. The present paper aims to show how information retrieved from passing networks can have a relevant impact on predicting the match outcome. In particular, we focus on modeling both the scored goals by two competing teams and the goal difference between them. With this purpose, we fit these outcomes using Bayesian hierarchical models, including both in-match and network-based covariates to cover many aspects of the offensive actions on the pitch. Furthermore, we review and compare different approaches to include covariates in modeling football outcomes. The presented methodology is applied to a real dataset containing information on 125 matches of the 2016–2017 UEFA Champions League, involving 32 among the best European teams. From our results, shots on target, corners, and such passing network indicators are the main determinants of the considered football outcomes.

Peningkatan Passing Sepakbola Menggunakan Media Dinding pada Siswa Kelas V di MI Darul Ulum Sumberagung

“…Olahraga yaitu rangkaian aktivitas yang meliputi gerak tubuh, di katakan aktivitas karena olahraga mempunyai tujuan untuk memelihara dan meningkatkan keterampilan fisik serta tubuh sehat dan bugar. Pendidikan jasmani dan juga olahraga sudah mencakup semua aspek, yang dimana aspek tersebut meliputi Keterampilan gerak, Kebugaran jasmani, Keterampilan sosial, Keterampilan berfikir kritis, Stabilitas emosional, Penalaran, Tindakan moral, Aspek kehidupan sehat, dan juga mengenalkan kebersihan lingkungan (Ievoli, 2023;Yu, 2020). Semua ini sudah di rancang secara sistematis mencapai tujuan pendidikan nasional.…”