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Sports Data Analysis by using Bivariate Poisson Models in the Bayesian Framework

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Title: Sports Data Analysis by using Bivariate Poisson Models in the Bayesian Framework

Authors: Sabina Shahin

Journal: Quaid-e-Awam University Research Journal of Engineering, Science & Technology

HEC Recognition History
Category From To
Y 2024-10-01 2025-12-31
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
Y 2020-07-01 2021-06-30
Z 2019-12-20 2020-06-30
Y 2015-03-12 2016-02-28
Z 2012-10-18 2015-03-11

Publisher: Quaid-e-Awam University of Engineering, Sciences & Technology, Nawabshah

Country: Pakistan

Year: 2023

Volume: 21

Issue: 1

Language: English

DOI: 10.52584/QRJ.2101.02

Keywords: Bayesian Analysis; Bivariate Poisson; Regression Models; Inflated Bivariate Poisson; Soccer data analysis

Categories
Sports Analytics (10) Regression Analysis (182) Bayesian Statistics (156) Mathematics (5170) Statistics (8857)

Abstract

Bivariate distribution models are commonly used to analyze sports data and data from various fields. These models are used to analyze discrete count data with two dependent variables in the data. In this research article, we have used Bivariate Poisson and Diagonally Inflated Bivariate Poisson regression models. We have proposed an estimation procedure in the Bayesian framework in conjunction with the augmentation of data. For parameter estimation, we use Gaussian priors and beta priors for both models. To illustrate the fitting performances of our suggested models we have performed real data analysis on English Premier League soccer data.

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