VIDEO ANALYSIS BASED ON ARTIFICIAL INTELLIGENCE FOR ENHANCING TECHNICAL AND TACTICAL MOVEMENT CONTROL IN FREESTYLE WRESTLING

The aim of the investigation was to test meticulously an actionable alternatives of video-based analyses by using the AI in order to boost technical and tactical movements in freestyle wrestling. The research was continued by using the digital platform so called “WrestlingAI”, which was created in order to assist a supervised analysis of technical movements in wrestling, mistakes, joint-angle corrections, session differentiation and personalized recommendation from the AI. The platform itself has a huge amount of information including 68 analyzed overall training videos and also 22 unparalleled moves and finally 7 different classifications. This module which is analytical has 36 sessions which was recorded during the study, AI analyses which was total 8 within the recommendations for each of them and matches which included 235 videos. The most interesting thing is that contained a score form, full technical corrections, crucial blunders and casual notes for each session, indicators of the joint-angles, specialized technic demonstrations and feedback from the coach after reviewing the both AI and recommendations. The platform outputs illustrated an average form score of 70%, 77 total technical errors, 71 critical errors, and 2.1 errors per session. Analyzed more frequently was practice in real life, that was registered 24 lessons . The results show that the video analysis supported by AI repeatedly identifies technical errors, monitors the quality of session performance, and allows coaches to monitor individual correction tasks. Simultaneously, information accuracy from the platform has to be meticulously and demands the consequential confirmation by expert verification and maintained instructional evaluation. The received details substantiate the practical significance of combining AI-based systems into freestyle wrestling training whereas conserving decisions to the coaches to make it more effective and trusted.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-07
DOI
https://doi.org/10.5281/zenodo.22640946
Primary Topic
Martial Arts: Techniques, Psychology, and Education
Type
article
Field-Weighted Citation Impact
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article

VIDEO ANALYSIS BASED ON ARTIFICIAL INTELLIGENCE FOR ENHANCING TECHNICAL AND TACTICAL MOVEMENT CONTROL IN FREESTYLE WRESTLING

Fikrat Kerimov, Olga Goncharova, Bekzod Abduraxmonov, Janibek Muratov
Zenodo (CERN European Organization for Nuclear Research)
Martial Arts: Techniques, Psychology, and Education
article

VIDEO ANALYSIS BASED ON ARTIFICIAL INTELLIGENCE FOR ENHANCING TECHNICAL AND TACTICAL MOVEMENT CONTROL IN FREESTYLE WRESTLING

Fikrat Kerimov, Olga Goncharova, Bekzod Abduraxmonov, Janibek Muratov
article en

Abstract

The aim of the investigation was to test meticulously an actionable alternatives of video-based analyses by using the AI in order to boost technical and tactical movements in freestyle wrestling. The research was continued by using the digital platform so called “WrestlingAI”, which was created in order to assist a supervised analysis of technical movements in wrestling, mistakes, joint-angle corrections, session differentiation and personalized recommendation from the AI. The platform itself has a huge amount of information including 68 analyzed overall training videos and also 22 unparalleled moves and finally 7 different classifications. This module which is analytical has 36 sessions which was recorded during the study, AI analyses which was total 8 within the recommendations for each of them and matches which included 235 videos. The most interesting thing is that contained a score form, full technical corrections, crucial blunders and casual notes for each session, indicators of the joint-angles, specialized technic demonstrations and feedback from the coach after reviewing the both AI and recommendations. The platform outputs illustrated an average form score of 70%, 77 total technical errors, 71 critical errors, and 2.1 errors per session. Analyzed more frequently was practice in real life, that was registered 24 lessons . The results show that the video analysis supported by AI repeatedly identifies technical errors, monitors the quality of session performance, and allows coaches to monitor individual correction tasks. Simultaneously, information accuracy from the platform has to be meticulously and demands the consequential confirmation by expert verification and maintained instructional evaluation. The received details substantiate the practical significance of combining AI-based systems into freestyle wrestling training whereas conserving decisions to the coaches to make it more effective and trusted.

Zenodo (CERN European Organization for Nuclear Research)
Ministry of Health of the Republic of Uzbekistan (UZ), Ministry of Innovative Development of the Republic of Uzbekistan
Openalex Percentile: Top 7%
Martial Arts: Techniques, Psychology, and Education
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