{"created":"2023-06-19T09:10:01.828708+00:00","id":1915,"links":{},"metadata":{"_buckets":{"deposit":"227fc73e-2dd4-4aca-83a5-f4a9f589d995"},"_deposit":{"created_by":13,"id":"1915","owners":[13],"pid":{"revision_id":0,"type":"depid","value":"1915"},"status":"published"},"_oai":{"id":"oai:shizusan.repo.nii.ac.jp:00001915","sets":["1:227:272:275"]},"author_link":["1448","2743","2662","1447","2133","2190"],"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2022-02-28","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicPageEnd":"84","bibliographicPageStart":"65","bibliographicVolumeNumber":"6","bibliographic_titles":[{"bibliographic_title":"スポーツと人間 : 静岡産業大学論集"},{"bibliographic_title":"Sport and human beings : Journal of Shizuoka Sangyo University","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Previous studies on skill evaluation and scale construction using game performance data of soccer \nare based on the premise that the data reflect the skills required for soccer offense. 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. In addition, the game performance big \ndata in offense of J.League was composed of 14 variables and 6 factors, and its content validity was \nconfirmed. However, this factor structure is not a completely simple structure, and a task remains \nto elucidate a more robust factor structure.","subitem_description_type":"Abstract"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"徐, 広孝"},{"creatorName":"ジョ, ヒロタカ","creatorNameLang":"ja-Kana"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中西, 健一郎"},{"creatorName":"ナカニシ, ケンイチロウ","creatorNameLang":"ja-Kana"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"青木, 優"},{"creatorName":"アオキ, マサル","creatorNameLang":"ja-Kana"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Jo, Hirotaka ","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Nakanishi, Kenichiro ","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Aoki, Masaru","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2022-03-16"}],"displaytype":"detail","filename":"06徐広孝_6584.pdf","filesize":[{"value":"678.9 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"06徐広孝_6584","url":"https://shizusan.repo.nii.ac.jp/record/1915/files/06徐広孝_6584.pdf"},"version_id":"c0a3b2d1-df2a-4027-9433-443f4bfe5896"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Soccer","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Game performance","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"big data","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Offensive play","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Exploratory factor analysis","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Program development","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"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 －","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"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 －"},{"subitem_title":"Factor Structure of Game Performance Big Data in Offensive Play  of Japan Professional Football League:  Applying a Practical Program in Exploratory Factor Analysis","subitem_title_language":"en"}]},"item_type_id":"10001","owner":"13","path":["275"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-02-28"},"publish_date":"2022-02-28","publish_status":"0","recid":"1915","relation_version_is_last":true,"title":["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 －"],"weko_creator_id":"13","weko_shared_id":-1},"updated":"2023-06-19T09:18:31.342466+00:00"}