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However, no \nstudies have verified whether Japanese professional level (J.League) game performance data reflects \nthe skills required for soccer offense. Although Factor analysis can be used as a method to confirm \nthis problem, there is a problem that it is difficult to properly use hyperparameters such as factor \nextraction method, rotation method, and number of factors in exploratory factor analysis. Therefore, \nin practice, inefficient analysis work is repeated. Against this background, in this study, we first \ndeveloped a program (PAHFA: a Program that Analyzes all Hyperparameters in Factor Analysis) \nthat is practically effective in exploratory factor analysis, and verified its practicality. Then, using \nthe game performance big data (45 variables, 147,032 plays) of offense in J.League referenced to the \nprevious research, the purpose was to elucidate the factor structure by exploratory factor analysis. \nAs a result, it became clear that PAHFA has practicality. 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Jリーグの攻撃プレーにおける ゲーム・パフォーマンス・ビッグデータの因子構造 - 探索的因子分析における実用的プログラムを適用して -
https://shizusan.repo.nii.ac.jp/records/1915
https://shizusan.repo.nii.ac.jp/records/191515c8ee54-d833-4675-bd3b-24f26f0ea359
名前 / ファイル | ライセンス | アクション |
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06徐広孝_6584 (678.9 kB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2022-02-28 | |||||
タイトル | ||||||
タイトル | Jリーグの攻撃プレーにおける ゲーム・パフォーマンス・ビッグデータの因子構造 - 探索的因子分析における実用的プログラムを適用して - | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Factor Structure of Game Performance Big Data in Offensive Play of Japan Professional Football League: Applying a Practical Program in Exploratory Factor Analysis | |||||
言語 | ||||||
言語 | jpn | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | Soccer | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | Game performance | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | big data | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | Offensive play | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | Exploratory factor analysis | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | Program development | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
徐, 広孝
× 徐, 広孝× 中西, 健一郎× 青木, 優× Jo, Hirotaka× Nakanishi, Kenichiro× Aoki, Masaru |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Previous studies on skill evaluation and scale construction using game performance data of soccer are based on the premise that the data reflect the skills required for soccer offense. However, no studies have verified whether Japanese professional level (J.League) game performance data reflects the skills required for soccer offense. Although Factor analysis can be used as a method to confirm this problem, there is a problem that it is difficult to properly use hyperparameters such as factor extraction method, rotation method, and number of factors in exploratory factor analysis. Therefore, in practice, inefficient analysis work is repeated. Against this background, in this study, we first developed a program (PAHFA: a Program that Analyzes all Hyperparameters in Factor Analysis) that is practically effective in exploratory factor analysis, and verified its practicality. Then, using the game performance big data (45 variables, 147,032 plays) of offense in J.League referenced to the previous research, the purpose was to elucidate the factor structure by exploratory factor analysis. As a result, it became clear that PAHFA has practicality. In addition, the game performance big data in offense of J.League was composed of 14 variables and 6 factors, and its content validity was confirmed. However, this factor structure is not a completely simple structure, and a task remains to elucidate a more robust factor structure. |
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書誌情報 |
スポーツと人間 : 静岡産業大学論集 en : Sport and human beings : Journal of Shizuoka Sangyo University 巻 6, 号 2, p. 65-84, 発行日 2022-02-28 |