A New Alpha Power Weibull Model for Analyzing Time-to-Event Data: A Case Study from Football. (9th February 2022)

• Record Type: Journal Article
• Authors: Shengjie, Gao; Craig, Alisa; Mekiso, Getachew Tekle
• Other Names: K Khosa Saima Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2022(2022)
• Publication Date: 2022-02-09
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2022/7257264
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Statistical methodologies have wider applications in exercise science, sports medicine, sports management, sports marketing, sports science, and other related sciences. These methods can be used to predict the winning probability of a team or individual in a match, the number of minutes that an individual player will spend on the ground, the number of goals to be scored by an individual player, the number of red/yellow cards that will be issued to an individual player or a team, etc. Keeping in view the importance and applicability of the statistical methodologies in sport sciences, healthcare, and other related sectors, this paper introduces a novel family of statistical models called new alpha power family of distributions. It is shown that numerous properties of the suggested method are similar to those of the new Weibull- X and exponential type distributions. Based on the novel method, a special model, namely, a new alpha power Weibull distribution, is studied. The new model is very flexible because the shape of its probability density function can either be right-skewed, decreasing, left-skewed, or increasing. Furthermore, the new distribution is also able to model real phenomena with bathtub-shaped failure rates. Finally, the usefulness/applicability of the proposed distribution is shown by analyzing the time-to-event datasets selected from different football matches during 1964–2018.