Method of mathematical processing of results in powerlifting for determining the greatest athletes in the overall score

Guk, V. and Stetsenko, A. (2017) Method of mathematical processing of results in powerlifting for determining the greatest athletes in the overall score. Вісник Черкаського університету. Серія Прикладна математика. Інформатика (№ 1-2). pp. 3-15.

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Abstract

Special coefficients and formulas used in powerlifting for determining the strongest powerlifters, regardless of division into bodyweight categories, require changes from time to time for more objective assessment of competitive results among all contestants. Lately, Wilks formula is used for this. However, according to the ratings of the strongest powerlifters calculated using this formula, representatives of light and heavy bodyweight categories predominantly win. The purpose of the work is to develop and substantiate a mathematical model that describes the statistical dependence of the results on the weight of the athlete's body. The analysis of results in the powerlifting total of powerlifters (520 people) and data about their bodyweight according to the materials of IPF World Men's Open Championships for the years 2012 to 2016 was carried out. The mathematical and statistical processing of the materials of the study was conducted and creation of logarithmic regression model based on the least squares method. It is shown that the relationship between the results of competitions in powerlifting and powerlifters bodyweight is best described by the log-linear function. Methods of finding the coefficients of this function are given here. It is proposed to convert powerlifters’ competitive results into conventional values with the help of logarithmic coefficients, calculated on the basis of data of previous competitions. The application of a logarithmic coefficient for calculating relative results in competitions in powerlifting allows to objectively choose the winners in the overall score.

Item Type: Article
Uncontrolled Keywords: powerlifting ; logarithmic regression model ; logarithmic coefficient formula ; overall score
Subjects: Фізкультура і спорт
Комп'ютерні науки
Комп'ютерні науки
Divisions: Навчально-науковий інститут фізичної культури, спорту і здоров’я
Факультет обчислювальної техніки, інтелектуальних та управляючих систем
Depositing User: Наукова Бібліотека
Date Deposited: 06 May 2020 05:09
Last Modified: 06 May 2020 05:09
URI: http://eprints.cdu.edu.ua/id/eprint/2625

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