A comparative analytical study of technical performance according to the biorhythm index as an applied artificial intelligence model on the U21 Volleyball World Championship

September 2025 , Pages 1137-1158

Authors

أ.م.د منتظر صاحب مهدي النويني 1 ; أ.م.د ماجد محمدأمين رحيم 1 ; L.Dr.Israa Hashim Jayan Naama Al-Sudani 2 ; L.Riyadi Muhammad Reda Abdulhussein Saud 2

1 جامعة كربلاء/ كلية التربية البدنية وعلوم الرياضة

2 University of Karbala / College of Physical Education and Sports Sciences

DOI logo 10.17656/jzsb.12222

Keywords

Abstract

This study aims to analyze the technical performance of the teams that qualified for the semi-finals of the 2021 FIVB Volleyball Men's U21 World Championship, using the biorhythm index as a tool for evaluating overall performance. It also seeks to identify the relationship between biorhythm and technical performance, derive a predictive equation to infer the relationship between the research variables, and create an artificial intelligence function (predictive model) based on linear regression. The research problem can be summarized in the following questions: To what extent can the biorhythm index explain changes in the technical performance of U21 volleyball players? And how can artificial intelligence be employed as an analytical model to improve our understanding of this relationship? The study relied on analytical data from the teams of Italy, Russia, Argentina, and Poland. The Dartfish program was used to analyze technical performance and Python functions. The results show the importance of balance between attack and defense, reducing errors, and raising the biorhythm index to achieve optimal performance. The most prominent conclusions were: the effectiveness of artificial intelligence in predicting technical performance. The use of the multiple linear regression model showed high accuracy in predicting the biorhythm of teams based on variables (attack success, defense success, and number of errors). Artificial intelligence provides powerful tools for analyzing relationships between variables. The most important recommendations were: analyzing videos using programs like Dartfish and combining them with predictive models to analyze offensive and defensive patterns, designing training programs based on the peak biorhythm of each player to ensure optimal performance, and combining artificial intelligence with video analysis to increase the accuracy in evaluating technical and tactical aspects, among other recommendations.

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  • First online11 September 2025
  • Published at11 September 2025

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