Machine Learning in Sports Open Approach for Next Play Analytics
This open access book provides cutting-edge work on machine learning in sports analytics, emphasizing the integration of computer vision, data analytics, and machine learning to redefine strategic sports analysis. This book not only covers the essential methodologies of capturing and analyzing real...
Uloženo v:
| Hlavní autor: | |
|---|---|
| Médium: | E-kniha |
| Jazyk: | angličtina |
| Vydáno: |
Singapore
Springer Nature
2025
|
| Edice: | SpringerBriefs in Computer Science |
| Témata: | |
| ISBN: | 9819614449, 9789819614448 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | This open access book provides cutting-edge work on machine learning in sports analytics, emphasizing the integration of computer vision, data analytics, and machine learning to redefine strategic sports analysis. This book not only covers the essential methodologies of capturing and analyzing real sports data but also pioneers the integration of real-world analytics with digital modeling, advancing the field toward sophisticated digital modeling in sports. Through a seamless blend of theoretical frameworks and practical applications, the book illustrates how these integrated technologies can be utilized to predict, evaluate, and suggest next plays in sports. By leveraging the power of machine learning, the book presents cutting-edge approaches to sports analytics, where data from actual games is enhanced with predictive simulations for strategic planning and decision-making. The use of digital modeling in sports opens up new dimensions of interaction between the physical play and its digital analysis, offering a comprehensive understanding that was previously unattainable. This book is an essential read for postgraduates, researchers, and technologists, who are interested in sports analysts. The book consists of five parts: Part I, which comprises a single chapter exploring the fundamentals and scope of learning-based sports analytics; Parts II, III, IV, and V review the various aspects of this field, including data acquisition with computer vision, predictive analysis and play evaluation with machine learning, potential play evaluation with learning-based agent modeling, and future perspectives and ecosystems on the field. This structure provides a comprehensive overview that will engage and inform researchers and practitioners interested in the intersection of analytical research and cutting-edge technology in sports. |
|---|---|
| AbstractList | This open access book provides cutting-edge work on machine learning in sports analytics, emphasizing the integration of computer vision, data analytics, and machine learning to redefine strategic sports analysis. This book not only covers the essential methodologies of capturing and analyzing real sports data but also pioneers the integration of real-world analytics with digital modeling, advancing the field toward sophisticated digital modeling in sports. Through a seamless blend of theoretical frameworks and practical applications, the book illustrates how these integrated technologies can be utilized to predict, evaluate, and suggest next plays in sports. By leveraging the power of machine learning, the book presents cutting-edge approaches to sports analytics, where data from actual games is enhanced with predictive simulations for strategic planning and decision-making. The use of digital modeling in sports opens up new dimensions of interaction between the physical play and its digital analysis, offering a comprehensive understanding that was previously unattainable. This book is an essential read for postgraduates, researchers, and technologists, who are interested in sports analysts. The book consists of five parts: Part I, which comprises a single chapter exploring the fundamentals and scope of learning-based sports analytics; Parts II, III, IV, and V review the various aspects of this field, including data acquisition with computer vision, predictive analysis and play evaluation with machine learning, potential play evaluation with learning-based agent modeling, and future perspectives and ecosystems on the field. This structure provides a comprehensive overview that will engage and inform researchers and practitioners interested in the intersection of analytical research and cutting-edge technology in sports. |
| Author | Fujii, Keisuke |
| Author_xml | – sequence: 1 fullname: Fujii, Keisuke |
| BookMark | eNpNj8lKBDEYhAMq6IzzAIqHfoFolj_bRZDBDVo8KF5Dkk6P0TFpEi--vT2MB09VRcFH1QId5pIjQmeUXFJC1JVRGhtNsZGYAggsDtBizkbOCcwxWrX2QQjhQJmk8gSdP7nwnnLs-uhqTnnTpdy9TKV-t1N0NLpti6s_XaK3u9vX9QPun-8f1zc9doxxLjFw5oWKjDgZIIweTABvIEDUgvogx0GqwChz3kQJepwnDuCUptHrIcaRL9H1HlzcFLOdavpy9ccWl-w2-br3u6bUjWXECkLsPF8ou7sszQy4-A8YivOlfDZLhQZq-C8a0VEa |
| ContentType | eBook |
| DBID | V1H A7I |
| DOI | 10.1007/978-981-96-1445-5 |
| DatabaseName | DOAB: Directory of Open Access Books OAPEN |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: V1H name: DOAB: Directory of Open Access Books url: https://directory.doabooks.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| ExternalDocumentID | oai_library_oapen_org_20_500_12657_100769 158419 |
| GrantInformation_xml | – fundername: Japan Science and Technology Agency |
| GroupedDBID | A7I AABBV AALJR AAQKC ABEEZ ACBJQ AEKFX AIQUZ ALMA_UNASSIGNED_HOLDINGS ALNDD BBABE CZZ EIXGO IEZ SBO TPJZQ V1H Z5O Z7R Z7S Z7U Z7V Z7W Z7X Z7Y Z7Z Z81 Z82 Z83 Z84 Z85 Z87 Z88 AAMOQ |
| ID | FETCH-LOGICAL-a22336-432b57e20a6c4cfb49c4b94c4e851bc6fd67c212ab9e648f978d4a781eb8deef3 |
| IEDL.DBID | A7I |
| ISBN | 9819614449 9789819614448 |
| IngestDate | Wed Dec 10 14:59:41 EST 2025 Wed Nov 19 10:00:50 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-a22336-432b57e20a6c4cfb49c4b94c4e851bc6fd67c212ab9e648f978d4a781eb8deef3 |
| OpenAccessLink | https://library.oapen.org/handle/20.500.12657/100769 |
| PageCount | 127 |
| ParticipantIDs | oapen_primary_oai_library_oapen_org_20_500_12657_100769 oapen_doabooks_158419 |
| PublicationCentury | 2000 |
| PublicationDate | 2025 |
| PublicationDateYYYYMMDD | 2025-01-01 |
| PublicationDate_xml | – year: 2025 text: 2025 |
| PublicationDecade | 2020 |
| PublicationPlace | Singapore |
| PublicationPlace_xml | – name: Singapore |
| PublicationSeriesTitle | SpringerBriefs in Computer Science |
| PublicationYear | 2025 |
| Publisher | Springer Nature |
| Publisher_xml | – name: Springer Nature |
| SSID | ssj0003412616 |
| Score | 2.4862387 |
| Snippet | This open access book provides cutting-edge work on machine learning in sports analytics, emphasizing the integration of computer vision, data analytics, and... |
| SourceID | oapen |
| SourceType | Publisher |
| SubjectTerms | Artificial intelligence Basketball Computer science Computing and Information Technology Cyber-physical systems Cybernetics and systems theory Deep learning Electronics and communications engineering Electronics engineering Football Information theory Machine learning Modeling Prediction Real-world data Reference, Information and Interdisciplinary subjects Reinforcement learning Research and information: general Soccer Sports Sports and Active outdoor recreation Technology, Engineering, Agriculture, Industrial processes |
| Subtitle | Open Approach for Next Play Analytics |
| Title | Machine Learning in Sports |
| URI | https://directory.doabooks.org/handle/20.500.12854/158419 https://library.oapen.org/handle/20.500.12657/100769 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV07T8MwED5By8BUHkW0PJSBNVUSO3Y8I6oiQcWAqm6WHxfUJUVt4fdzdtLCzBIpOSWxP8XxfWffdwAPUlo0DFVqCiZS7kyZGsYNjSvhDBPGi7jLd_Ei5_NquVRvXVLY9jd2MVkbYvNxJb9VGyCSPimzIIYgypAsTvRbHUNfhGrUwSGSz4fICv2XiRaIVl1H0YwXOA-viJIdTtR-fbOTmCVDqkRKpjItQ-mj8PY_88x08L8WnkEfQ87CORxhcwGDfaWGpBu4lzB-jXsmMenkVD-SVZPEAufbISymT--Ps7SrikBwFiwAygpbSiwyIxx3teXKcau440jek3Wi9kI6mpGMVSh4VVMHPTeyytFWHrFmV9Br1g1eQ8IzX9FDvDQKiRcWFiubYaZqw71FxkcwjN3Ufm2C07_VOTksuRqBbK9_tpIYOohUd8Do1kLA6CLThIiOiOgWkfG_77yB0yLU3o3hj1vo7TZfeAcn7nu32m7u4ydAx0U--wGtgazV |
| linkProvider | Open Access Publishing in European Networks |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=book&rft.title=Machine+Learning+in+Sports&rft.au=Fujii%2C+Keisuke&rft.series=SpringerBriefs+in+Computer+Science&rft.date=2025-01-01&rft.pub=Springer+Nature&rft.isbn=9789819614448&rft_id=info:doi/10.1007%2F978-981-96-1445-5&rft.externalDBID=A7I&rft.externalDocID=oai_library_oapen_org_20_500_12657_100769 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9789819614448/lc.gif&client=summon&freeimage=true |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9789819614448/mc.gif&client=summon&freeimage=true |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9789819614448/sc.gif&client=summon&freeimage=true |