Analyzing predictive approaches in martial arts research

IF 0.7 Q4 HOSPITALITY, LEISURE, SPORT & TOURISM Pedagogy of Physical Culture and Sports Pub Date : 2023-08-30 DOI:10.15561/26649837.2023.0408
Y. Tropin, L. Podrigalo, N. Boychenko, Olha O. Podrihalo, O. Volodchenko, D. Volskyi, M. Roztorhui
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Abstract

Background and Study Aim. Predicting the results of martial arts competitions is an important task that attracts the attention of both sports analysts and fans of these sports. The objective of this study is to perform an analytical examination of publications on martial arts prediction, with the aim of identifying the primary research directions in this field. Materials and Methods. the bibliometric analysis of PubMed database data was used to create a sample of studies at 18.05.2023. The keywords "prediction", "martial arts" were used for the search. A total of 151 publications were found. The first publication was dated 1983. VOSviewer 1.6.19 program was used: keyword analysis method and direct citation analysis with the construction of bibliometric maps, the visualization of cluster density, weights – citations. Results. 51 journals from 21 countries were identified. The unconditional leader among the countries is the United States (16 journals). Between 1983 and May 18, 2023, 741 scientific works were found. The analysis involved 67 authors whose link strength was more than 0. Eight clusters were identified. They were characterized by the presence of 271 links with total link strength of 276. The number of items in the clusters did not have a significant difference; this can be explained by the popularity of all directions in the research. The authors of the seventh and eighth clusters had the most publications. To visualize the network 63 items (keywords) were selected. They were grouped into 4 clusters. The network includes 951 links; the total link strength is 4027. The most popular studies are highlighted. These studies include the following keywords: "humans", "martial arts", "female", "male", "athletes", "young adult", "middle aged". Conclusions. The analysis of the bibliometric maps revealed the tendencies of scientific research and highlighted the priority areas. The relevance of the problem of prediction in martial arts is confirmed. An increase in the number of publications in PubMed database over the past decade has been observed. The main areas of research include martial arts, health, sports training, and humans. Most publications focus on utilizing artificial intelligence and machine learning techniques for predicting competition outcomes. Additionally, they explore the application of analytical tools to uncover patterns in data and identify critical factors that impact competition results. Modern technologies and the availability of big data open up new possibilities for predicting competitive success in martial arts.
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武术研究中的预测方法分析
背景与研究目的。武术比赛结果预测是体育分析人士和武术爱好者关注的一项重要任务。本研究的目的是对有关武术预测的出版物进行分析审查,旨在确定该领域的主要研究方向。材料与方法。使用PubMed数据库数据的文献计量学分析,于2023年5月18日创建研究样本。搜索关键词是“预测”、“武术”。共发现151份出版物。第一次出版的日期是1983年。采用VOSviewer 1.6.19软件:关键词分析法和直接引文分析法,构建文献计量图,可视化聚类密度、权值-被引次数。确定了来自21个国家的51种期刊。排名第一的是美国(16种)。从1983年到2023年5月18日,共发现了741件科学作品。该分析涉及67位链接强度大于0的作者。确定了八个集群。它们的特点是存在271个链接,总链接强度为276。聚类中项目的数量没有显著差异;这可以用研究中各个方向的流行来解释。第七组和第八组的作者发表的论文最多。为了使网络可视化,我们选择了63个项目(关键词)。他们被分成4组。该网络包括951条链路;链路总强度为4027。重点介绍了最受欢迎的研究。这些研究包括以下关键词:“人类”、“武术”、“女性”、“男性”、“运动员”、“青壮年”、“中年”。通过对文献计量图的分析,揭示了科学研究的趋势,突出了重点领域。证实了预测问题在武术中的相关性。在过去的十年中,PubMed数据库中的出版物数量有所增加。主要研究领域包括武术、健康、运动训练和人类。大多数出版物都集中在利用人工智能和机器学习技术来预测竞争结果。此外,他们还探索了分析工具的应用,以揭示数据中的模式,并确定影响竞争结果的关键因素。现代技术和大数据的可用性为预测武术的竞争成功开辟了新的可能性。
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来源期刊
Pedagogy of Physical Culture and Sports
Pedagogy of Physical Culture and Sports Social Sciences-Education
CiteScore
2.00
自引率
0.00%
发文量
45
审稿时长
6 weeks
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