Sports Analytics and Data Science

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Release : 2015-11-18
Genre : Business & Economics
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Book Rating : 413/5 ( reviews)

Sports Analytics and Data Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Sports Analytics and Data Science write by Thomas W. Miller. This book was released on 2015-11-18. Sports Analytics and Data Science available in PDF, EPUB and Kindle. This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. This up-to-the-minute reference will help you master all three facets of sports analytics — and use it to win! Sports Analytics and Data Science is the most accessible and practical guide to sports analytics for everyone who cares about winning and everyone who is interested in data science. You’ll discover how successful sports analytics blends business and sports savvy, modern information technology, and sophisticated modeling techniques. You’ll master the discipline through realistic sports vignettes and intuitive data visualizations–not complex math. Every chapter focuses on one key sports analytics application. Miller guides you through assessing players and teams, predicting scores and making game-day decisions, crafting brands and marketing messages, increasing revenue and profitability, and much more. Step by step, you’ll learn how analysts transform raw data and analytical models into wins: both on the field and in any sports business.

Sports Analytics

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Release : 2024-05-28
Genre : Sports & Recreation
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Book Rating : 89X/5 ( reviews)

Sports Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Sports Analytics write by Benjamin C. Alamar. This book was released on 2024-05-28. Sports Analytics available in PDF, EPUB and Kindle. Data and analytics have the potential to provide sports organizations with a competitive advantage both on and off the field. Yet even as the use of analytics in sports has become commonplace, teams regularly find themselves making big investments without significant payoff. This book is a practical, nontechnical guide to incorporating sports data into decision making, giving leaders the knowledge they need to maximize their organization’s investment in analytics. Benjamin C. Alamar—a leading expert who has built high-performing analytics groups—surveys the current state of the use of data in sports, including both specifics around the tools and how to deploy them most effectively. Sports Analytics offers a clear, easily digestible overview of data management, statistical models, and information systems and a detailed understanding of their vast possibilities. It walks readers through the essentials of understanding the value of different types of data and strategies for building and managing an analytics team. Throughout, Alamar illustrates the value of analytics with real-world examples and case studies from both the sports and business sides. Sports Analytics has guided a range of sports professionals to success since its original publication in 2013. This second edition adds examples and strategies that focus on using data on the business side of a sports organization, provides concrete strategies for incorporating different types of data into decision making, and updates all discussions for the rapid technological developments of the last decade.

Sport Business Analytics

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Release : 2016-11-18
Genre : Computers
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Book Rating : 275/5 ( reviews)

Sport Business Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Sport Business Analytics write by C. Keith Harrison. This book was released on 2016-11-18. Sport Business Analytics available in PDF, EPUB and Kindle. Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group. The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in: Ticket pricing Season ticket member retention Fan engagement Sponsorship valuation Customer relationship management Digital marketing Market research Data visualization. This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations. Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics.

Machine Learning and Data Mining for Sports Analytics

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Release : 2020-12-09
Genre : Computers
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Book Rating : 121/5 ( reviews)

Machine Learning and Data Mining for Sports Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning and Data Mining for Sports Analytics write by Ulf Brefeld. This book was released on 2020-12-09. Machine Learning and Data Mining for Sports Analytics available in PDF, EPUB and Kindle. This book constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. Due to the COVID-19 pandemic the conference was held online. The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.

Basketball Data Science

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Release : 2020-01-03
Genre : Business & Economics
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Book Rating : 260/5 ( reviews)

Basketball Data Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Basketball Data Science write by Paola Zuccolotto. This book was released on 2020-01-03. Basketball Data Science available in PDF, EPUB and Kindle. Using data from one season of NBA games, Basketball Data Science: With Applications in R 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, Basketball Data Science with R is suitable for students, technicians, coaches, data analysts and applied researchers. Features: One of the first books to provide statistical and data mining methods for the growing field of analytics in basketball Presents tools for modelling graphs and figures to visualize the data Includes real world case studies and examples, such as estimations of scoring probability using the Golden State Warriors as a test case Provides the source code and data so readers can do their own analyses on NBA teams and players