S1 Raw data -
收藏NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/S1_Raw_data_-/27735503
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In the Paris Olympic cycle, South Korean women’s athlete An Se-young rose to the top of the 2023 BWF Olympic points with a win rate of 89.5%. With An Se-young as the subject, this paper aims to carry out technical and tactical analysis of women’s badminton singles and formulate a prediction model based on machine learning. Firstly, An’s technical and tactical statistics are analyzed and presented in a proposed "three-stage" data classification method. Secondly, we improve our “three-stage” machine learning dataset using video analysis of 10 matches (21 point games) where An Se-young faced off against four other players ranked in the top five of the World Badminton Federation (BWF) in week 44 of 2023. Finally, we establish a prediction model for the scoring and losing of points in the women’s badminton singles based on the ‘Decision tree’, ‘Random forest’, ‘XGBoost’, ‘Support vector’ and ‘K-proximity’ algorithms, and analyze the effectiveness of this model. The results show that the improved data classification is reasonable and can be used to predict the final score of a match. When the support vector machine uses the RBF function kernel, the accuracy reaches its highest at 87.5%, and the consistency of this prediction model is strong. An’s playstyle is sustained and unified; she does not seek continuous pressure, but rather exploits and maximizes her aggression following any mistake made by her opponents, immediately utilizing assault methods such as kills or dives, often resulting in the conversion of points during the subsequent 2–3 strikes.
在巴黎奥运会周期中,韩国女子羽毛球运动员安洗莹以89.5%的胜率登顶2023年世界羽毛球联合会(BWF)奥运积分榜榜首。本研究以安洗莹为研究对象,旨在开展女子羽毛球单打项目的技战术分析,并构建基于机器学习的预测模型。首先,本研究对安洗莹的技战术统计数据进行分析,并采用本文提出的“三阶段”数据分类方法进行呈现;其次,本研究通过对2023年第44周安洗莹对阵4名位列世界羽联(BWF)前五的选手的10场21分制赛事进行视频解析,优化了“三阶段”机器学习数据集;最后,本研究基于决策树(Decision tree)、随机森林(Random forest)、XGBoost、支持向量(Support vector)以及K近邻(K-proximity)算法,构建了女子羽毛球单打项目的得分与失分预测模型,并对该模型的有效性进行了分析。研究结果表明,优化后的三阶段数据分类方法具备合理性,可用于预测赛事最终比分。其中,当支持向量机采用径向基函数(RBF)核时,模型准确率最高可达87.5%,且该预测模型的一致性较强。安洗莹的打法风格连贯统一,并不追求持续施加压迫,而是在对手出现失误后抓住机会,最大化发挥进攻优势,即刻通过杀球、扑球等突击手段得分,通常可在随后的2-3拍回合中完成得分转换。
创建时间:
2024-11-14



