{"product_id":"basketball-data-science-with-applications-in-r-paperback","title":"Basketball Data Science: With Applications in R - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003ePaola Zuccolotto\u003c\/b\u003e (Author), \u003cb\u003eMarica Manisera\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eUsing data from one season of NBA games, \u003cstrong\u003eBasketball Data Science: With Applications in R\u003c\/strong\u003e is the perfect book for anyone interested in learning and applying data analytics in basketball. Whether assessing the spatial performance of an NBA player's shots or doing an analysis of the impact of high pressure game situations on the probability of scoring, this book discusses a variety of case studies and hands-on examples using a custom R package. The codes are supplied so readers can reproduce the analyses themselves or create their own. Assuming a basic statistical knowledge, \u003cstrong\u003eBasketball Data Science with R\u003c\/strong\u003e is suitable for students, technicians, coaches, data analysts and applied researchers.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eFeatures\u003c\/strong\u003e: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eOne of the first books to provide statistical and data mining methods for the growing field of analytics in basketball\u003c\/li\u003e \u003cli\u003ePresents tools for modelling graphs and figures to visualize the data\u003c\/li\u003e \u003cli\u003eIncludes real world case studies and examples, such as estimations of scoring probability using the Golden State Warriors as a test case\u003c\/li\u003e \u003cli\u003eProvides the source code and data so readers can do their own analyses on NBA teams and players\u003c\/li\u003e\n\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePaola Zuccolotto \u003c\/strong\u003eand \u003cstrong\u003eMarica Manisera\u003c\/strong\u003e are, respectively, Full and Associate Professor of Statistics at the University of Brescia. Paola Zuccolotto is the scientific director of the Big \u0026amp; Open Data Innovation Laboratory (BODaI-Lab), where she coordinates, together with Marica Manisera, the international project Big Data Analytics in Sports (BDsports).\u003c\/p\u003e\n\u003cp\u003eThey carry out scientific research activity in the field of Statistical Science, both with a methodological and applied approach. They authored\/co-authored several scientific articles in international journals and books, participated to many national and international conferences, also as organizers of specialized sessions, often on the topic of Sports Analytics. They regularly act as scientific reviewers for the world's most prestigious journals in the field of Statistics. \u003c\/p\u003e\n\u003cp\u003ePaola Zuccolotto is a member of the Editorial Advisory Board of the Journal of Sports Sciences, while Marica Manisera is Associate Editor of the Journal of Sports Analytics; both of them are guest co-editors of special issues of international journals on Statistics in Sports. The International Statistical Institute (ISI) delegated them the task of revitalizing its Special Interest Group (SIG) on Sports Statistics. Marica Manisera is the Chair of the renewed ISI SIG on Sport. \u003cbr\u003eBoth of them teach undergraduate and graduate courses in the field of Statistics and are responsible for the scientific area dedicated to Sport Analytics at the PhD \"Analytics for Economics and Management\" of the University of Brescia. They also teach courses and seminars on Sports Analytics in University Masters on Sports Engineering and specialized training projects devoted to people operating in the sports world. They supervise students' internships, final reports and master's theses on the subject of Statistics, often with applications to sport data. They also work in collaboration with high-school teachers, creating experimental educational projects to bring students closer to quantitative subjects through Sport Analytics.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 244\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.6 x 9.2 x 6.1 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e January 14, 2020\u003c\/div\u003e\n            \u003c\/ul\u003e","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":52482264465715,"sku":"9781138600799","price":126.86,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0300\/5595\/6612\/files\/MzZja3N2K3FUd0ZsZHBKVGFKMzBMQT09.webp?v=1759737493","url":"https:\/\/www.vysn.com\/en-ca\/products\/basketball-data-science-with-applications-in-r-paperback","provider":"VYSN","version":"1.0","type":"link"}