Sports analytics : data-driven sports and decision intelligence / A Mansurali, P. Mary Jeyanthi, Dieu Hack-Polay, Ali B. Mahmoud, editors.
| Format | Electronic |
| Publication | Cham : Springer, 2024. |
| Description | 1 online resource (x, 238 pages) : illustrations (some color) |
| Supplemental Content | EBSCOhost |
| Subjects |
| Other author/creator | Mansurali, A., editor. |
| Other author/creator | Jeyanthi, P. Mary, editor. |
| Other author/creator | Hack-Polay, Dieu, editor. |
| Other author/creator | Mahmoud, Ali B., editor. |
| Contents | Introduction -- Visualizing in Sports Analytics -- IoT and Block Chain in Sports -- Sports Revenue Analytics -- Sports Marketing Analytics -- Forecasting in Sports -- Machine learning & AI in sports -- Classification and Regression techniques for sports -- Sports Analytics in different sports -- 'Sports analytics data'-Who uses it? -- Case Studies -- Conclusion. |
| Abstract | In "Sports Analytics: Data-Driven Sports and Decision Intelligence," embark on a journey through the exhilarating world of sports enhanced by the power of data-driven insights. From the nail-biting moments on the field to the strategic decisions behind the scenes, this comprehensive guide unveils the secrets that propel teams to victory and champions to greatness.It explores the cutting-edge techniques and methodologies that revolutionize the way we understand and analyze sports performance. From player evaluations to game strategies, injury prevention to fan engagement, this book equips you with the tools to gain a competitive edge in any sport. Whether you're a coach, player, analyst, or simply a passionate fan, this book will change the way you see the game. This book details how to use analytics and machine learning to highlight key performance indicators (KPIs) of sports for analysis. The authors show how to apply various statistical techniques, machine learning and data mining algorithms for on-field and off-field analysis. They go on to show how analytical algorithms are used in the sports ecosystem to derive solutions for the team and leadership, helping team managers and coaches to monitor games and player information through dashboards. The book then shows how to deploy machine learning algorithms for validating and improving teams and players performance. The book is relevant to professionals and academics working in machine learning and data analysis related to sports. Shows how to apply machine learning and data mining algorithms for on-field and off-field analysis; Details how to use machine learning to highlight key performance indicators of sports for performance analysis; Relevant to professionals and academics working in machine learning and data analysis related to sports. |
| General note | Includes index. |
| Source of description | Online resource; title from PDF title page (SpringerLink, viewed October 10, 2024). |
| Issued in other form | Print version: Mansurali, A. Sports Analytics Cham : Springer,c2024 9783031635724 |
| ISBN | 9783031635731 (electronic bk.) |
| ISBN | 3031635736 (electronic bk.) |
| Standard identifier# | 10.1007/978-3-031-63573-1 |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |