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Author: Ted Kwartler
Publisher: John Wiley & Sons Incorporated
ISBN: 9781119598084
Category : Mathematics
Languages : en
Pages : 0
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Book Description
Introduction to R -- Data Vizualization & Dashboards: Best practices -- Geospatial Data: Understanding changing baseball player behavior -- Machine Learning Basics: Modeling football draft patterns, pick number & clusters among athletes -- Logistic Regression: Explaining basketball wins & losses with coefficients -- Natual Language Processing: Understanding cricket fan topics & sentiment -- Linear Optimization: Programmatically seleting an optimal fantasy football lineup.
Author: Ted Kwartler
Publisher: John Wiley & Sons Incorporated
ISBN: 9781119598084
Category : Mathematics
Languages : en
Pages : 0
Get Book Here
Book Description
Introduction to R -- Data Vizualization & Dashboards: Best practices -- Geospatial Data: Understanding changing baseball player behavior -- Machine Learning Basics: Modeling football draft patterns, pick number & clusters among athletes -- Logistic Regression: Explaining basketball wins & losses with coefficients -- Natual Language Processing: Understanding cricket fan topics & sentiment -- Linear Optimization: Programmatically seleting an optimal fantasy football lineup.
Author: Ted Kwartler
Publisher: John Wiley & Sons
ISBN: 1119598079
Category : Medical
Languages : en
Pages : 276
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Book Description
Sports Analytics in Practice with R A practical guide for those looking to employ the latest and leading analytical software in sport In the last twenty years, sports organizations have become a data-driven business. Before this, most decisions in sports were qualitatively driven by subject-matter experts. In the years since numerous teams found success with “Money Ball” analytical perspectives, the industry has sought to advance its analytical acumen to improve on- and off-field outcomes. The increasing demand for data to inform decisions for coaches, scouts, and players before and during sporting events has led to intriguing efforts to build upon this quantitative approach. As this methodology for assessing performance has matured and grown in importance, so too has the open-source R software emerged as one of the leading analytical software packages. In fact, R is a top 10 programming language that is useful in academia and industry for statistics, machine learning, and rapid prototyping. Sports Analytics in Practice with R neatly marries these two advances to teach basic analytics for sports-related use—from cricket to baseball, from basketball to tennis, from soccer to sports gambling, and more. Sports Analytics in Practice with R readers will also find: A broad perspective of sports, focusing on a wide range of sports rather than just one The first book of its kind that features coding examples Case study approach throughout the book Companion website including data sets to work through alongside the explanations Sports Analytics in Practice with R is a helpful tool for students and professionals in the sports management field, but also for sports enthusiasts who have a coding background.
Author: Gil Fried
Publisher: Taylor & Francis
ISBN: 1317212886
Category : Business & Economics
Languages : en
Pages : 279
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Book Description
The increasing availability of data has transformed the way sports are played, promoted and managed. This is the first textbook to explain how the big data revolution is having a profound influence across the sport industry, demonstrating how sport managers and business professionals can use analytical techniques to improve their professional practice. While other sports analytics books have focused on player performance data, this book shows how analytics can be applied to every functional area of sport business, from marketing and event management to finance and legal services. Drawing on research that spans the entire sport industry, it explains how data is influencing the most important decisions, from ticket sales and human resources to risk management and facility operations. Each chapter contains real world examples, industry profiles and extended case studies which are complimented by a companion website full of useful learning resources. Sport Analytics: A data-driven approach to sport business and management is an essential text for all sport management students and an invaluable reference for any sport management professional involved in operational research.
Author: Ted Kwartler
Publisher: John Wiley & Sons
ISBN: 1119282012
Category : Mathematics
Languages : en
Pages : 320
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Book Description
A reliable, cost-effective approach to extracting priceless business information from all sources of text Excavating actionable business insights from data is a complex undertaking, and that complexity is magnified by an order of magnitude when the focus is on documents and other text information. This book takes a practical, hands-on approach to teaching you a reliable, cost-effective approach to mining the vast, untold riches buried within all forms of text using R. Author Ted Kwartler clearly describes all of the tools needed to perform text mining and shows you how to use them to identify practical business applications to get your creative text mining efforts started right away. With the help of numerous real-world examples and case studies from industries ranging from healthcare to entertainment to telecommunications, he demonstrates how to execute an array of text mining processes and functions, including sentiment scoring, topic modelling, predictive modelling, extracting clickbait from headlines, and more. You’ll learn how to: Identify actionable social media posts to improve customer service Use text mining in HR to identify candidate perceptions of an organisation, match job descriptions with resumes, and more Extract priceless information from virtually all digital and print sources, including the news media, social media sites, PDFs, and even JPEG and GIF image files Make text mining an integral component of marketing in order to identify brand evangelists, impact customer propensity modelling, and much more Most companies’ data mining efforts focus almost exclusively on numerical and categorical data, while text remains a largely untapped resource. Especially in a global marketplace where being first to identify and respond to customer needs and expectations imparts an unbeatable competitive advantage, text represents a source of immense potential value. Unfortunately, there is no reliable, cost-effective technology for extracting analytical insights from the huge and ever-growing volume of text available online and other digital sources, as well as from paper documents—until now.
Author: Benjamin C. Alamar
Publisher: Columbia University Press
ISBN: 023155589X
Category : Sports & Recreation
Languages : en
Pages : 219
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Book Description
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.
Author: Jared P. Lander
Publisher: Pearson Education
ISBN: 0321888030
Category : Computers
Languages : en
Pages : 464
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Book Description
A guide to using and understanding the 'R' computer programming language.
Author: Dean Oliver
Publisher: U of Nebraska Press
ISBN: 164012389X
Category : Sports & Recreation
Languages : en
Pages : 417
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Book Description
Journey "inside the numbers" for an exceptional set of statistical tools and rules that can help explain the winning, or losing, ways of a basketball team. Basketball on Paper doesn't diagram plays or explain how players get in shape, but instead demonstrates how to interpret player and team performance. Dean Oliver highlights general strategies for teams when they're winning or losing and what aspects should be the focus in either situation. He describes and quantifies the jobs of team leaders and role players, then discusses the interactions between players and how to achieve the best fit. Oliver conceptualizes the meaning of teamwork and how to quantify the value of different types of players working together. He examines historically successful NBA teams and identifies what made them so successful: individual talent, a system of putting players together, or good coaching. Oliver then uses these statistical tools and case studies to evaluate the best players in history, such as Magic Johnson, Wilt Chamberlain, Bill Russell, and Charles Barkley and how they contributed to their teams' success. He does the same for some of the NBA's "oddball" players-Manute Bol, Muggsy Bogues, and Dennis Rodman and for the WNBA's top players. Basketball on Paper is unique in its incorporation of business and analytical concepts within the context of basketball to measure the value of players in a cooperative setting. Whether you're looking for strategies or new ideas to throw out while watching the ballgame at a sports bar, Dean Oliver'sBasketball on Paper will give you amazing new insights into teamwork, coaching, and success.
Author: Philippe J. S. De Brouwer
Publisher: John Wiley & Sons
ISBN: 1119632722
Category : Mathematics
Languages : en
Pages : 928
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Book Description
Introduces professionals and scientists to statistics and machine learning using the programming language R Written by and for practitioners, this book provides an overall introduction to R, focusing on tools and methods commonly used in data science, and placing emphasis on practice and business use. It covers a wide range of topics in a single volume, including big data, databases, statistical machine learning, data wrangling, data visualization, and the reporting of results. The topics covered are all important for someone with a science/math background that is looking to quickly learn several practical technologies to enter or transition to the growing field of data science. The Big R-Book for Professionals: From Data Science to Learning Machines and Reporting with R includes nine parts, starting with an introduction to the subject and followed by an overview of R and elements of statistics. The third part revolves around data, while the fourth focuses on data wrangling. Part 5 teaches readers about exploring data. In Part 6 we learn to build models, Part 7 introduces the reader to the reality in companies, Part 8 covers reports and interactive applications and finally Part 9 introduces the reader to big data and performance computing. It also includes some helpful appendices. Provides a practical guide for non-experts with a focus on business users Contains a unique combination of topics including an introduction to R, machine learning, mathematical models, data wrangling, and reporting Uses a practical tone and integrates multiple topics in a coherent framework Demystifies the hype around machine learning and AI by enabling readers to understand the provided models and program them in R Shows readers how to visualize results in static and interactive reports Supplementary materials includes PDF slides based on the book’s content, as well as all the extracted R-code and is available to everyone on a Wiley Book Companion Site The Big R-Book is an excellent guide for science technology, engineering, or mathematics students who wish to make a successful transition from the academic world to the professional. It will also appeal to all young data scientists, quantitative analysts, and analytics professionals, as well as those who make mathematical models.
Author: Kirk Patrick Goldsberry
Publisher: Mariner Books
ISBN: 1328767515
Category : Sports & Recreation
Languages : en
Pages : 257
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Book Description
"Beautifully illustrated and sharply written, SprawlBall is both a celebration and a critique of the 3-point shot. If you want to understand how the modern NBA came to be, you'll need to read this book." --Nate Silver, editor of fivethirtyeight.com From the leading expert in the exploding field of basketball analytics, a stunning infographic decoding of the modern NBA: who shoots where, and how. The field of basketball analytics has leaped to overdrive thanks to Kirk Goldsberry, whose visual maps of players, teams, and positions have helped teams understand who really is the most valuable player at any position. SprawlBall combines stunning visuals, in-depth analysis, fun, behind-the-scenes stories and gee-whiz facts to chart a modern revolution. From the introduction of the 3-point line to today, the game has changed drastically . . . Now, players like Steph Curry and Draymond Green are leading the charge. In chapters like "The Geography of the NBA," "The Interior Minister (Lebron James)," "The Evolution of Steph Curry," and "The Investor (James Harden)," Goldsberry explains why today's on-court product--with its emphasis on shooting, passing, and spacing--has never been prettier or more democratic. And it's never been more popular. For fans of Bill Simmons and FreeDarko, SprawlBall is a bold new vision of the game, presenting an innovative, cutting-edge look at the sport based on the latest research, as well as a visual and infographic feast for fans.
Author: Leonard C Maclean
Publisher: World Scientific
ISBN: 9811250227
Category : Business & Economics
Languages : en
Pages : 587
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Book Description
This book is a collection of applications of analytic techniques to a number of popular sports including baseball, basketball, hockey, Jai Alai, NFL football and horseracing. We focus on both the statistics of the sporting events and betting strategies on the events. The subject is fascinating as there are many twists and subtle complicated decisions.Sports analytics applies mathematical and statistical methods to important questions in the structure and performance of sporting activities using the same basic methods and approaches as data analysts in other disciplines.Sports games and events are a fruitful area for study and to evaluate betting strategies as there is extensive data and mean reversion. With prices changing continuously, risk arbitrage bets can be made. Moreover, little errors, like a penalty to a player or an error in a call by a referee, can change the score of a game and corresponding betting prices. The collection and analysis of in-game data can inform players, coaches and staff on effective decision making during sporting events.Novel features of the book include: an analysis of who were the greatest baseball batters; analyses of the players most important to team success (and they are not necessarily the best players) in basketball, NFL football and hockey; a tutorial on risk arbitrage and its applications to NFL football and NBA basketball; a discussion of many ad hoc decision rules by coaches and players and what was really optimal; in the racing section we discuss breeding, the analysis of various bets like the Rainbow and ordinary Pick 6, a discussion and betting on the most important races and a visit to the Breeders' Cup with Ed Thorp to demonstrate the place and show system in action.
