Sports Analytics And Data Science
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Sports Analytics And Data Science
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Author : Thomas W. Miller
language : en
Publisher: FT Press
Release Date : 2015-11-18
Sports Analytics And Data Science written by Thomas W. Miller and has been published by FT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-18 with Business & Economics categories.
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 And Data Science
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Author : Thomas W. Miller
language : en
Publisher: Financial Times/Prentice Hall
Release Date : 2015
Sports Analytics And Data Science written by Thomas W. Miller and has been published by Financial Times/Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Data mining categories.
TO BUILD WINNING TEAMS AND SUCCESSFUL SPORTS BUSINESSES, GUIDE YOUR DECISIONS WITH DATA 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. Thomas W. Miller, leader of Northwestern University's pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R and Python code, interpreting your results, and more. 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. Whether you're a team executive, coach, fan, fantasy player, or data scientist, this guide will be a powerful source of competitive advantage... in any sport, by any measure. All data sets, extensive R and Python code, and additional examples available for download at http: //www.ftpress.com/miller/ This exceptionally complete and practical guide to sports data science and modeling teaches through realistic examples from sports industry economics, marketing, management, performance measurement, and competitive analysis. Thomas W. Miller, faculty director of Northwestern University's pioneering Predictive Analytics program, shows how to use advanced measures of individual and team performance to judge the competitive position of both individual athletes and teams, and to make more accurate predictions about their future performance. Miller's modeling techniques draw on methods from economics, accounting, finance, classical and Bayesian statistics, machine learning, simulation, and mathematical programming. Miller illustrates them through realistic case studies, with fully worked examples in both R and Python. Sports Analytics and Data Science will be an invaluable resource for everyone who wants to seriously investigate and more accurately predict player, team, and sports business performance, including students, teachers, sports analysts, sports fans, trainers, coaches, and team and sports business managers. It will also be valuable to all students of analytics and data science who want to build their skills through familiar and accessible sports applications Gain powerful, actionable insights for: Understanding sports markets Assessing players Ranking teams Predicting scores Making game day decisions Crafting marketing messages Promoting brands and products Growing revenues Managing finances Playing what-if games And much more
Sports Analytics And Data Science
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Author : Thomas W. Miller
language : en
Publisher:
Release Date : 2015
Sports Analytics And Data Science written by Thomas W. Miller and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Sports categories.
Sports Analytics
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Author : Ambikesh Jayal
language : en
Publisher: Routledge
Release Date : 2018-06-12
Sports Analytics written by Ambikesh Jayal and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-12 with Sports & Recreation categories.
As the analysis of big datasets in sports performance becomes a more entrenched part of the sporting landscape, so the value of sport scientists and analysts with formal training in data analytics grows. Sports Analytics: Analysis, Visualisation and Decision Making in Sports Performance provides the most authoritative and comprehensive guide to the use of analytics in sport and its application in sports performance, coaching, talent identification and sports medicine available. Employing an approach-based structure and integrating problem-based learning throughout the text, the book clearly defines the difference between analytics and analysis and goes on to explain and illustrate methods including: Interactive visualisation Simulation and modelling Geospatial data analysis Spatiotemporal analysis Machine learning Genomic data analysis Social network analysis Offering a mixed-methods case study chapter, no other book offers the same level of scientific grounding or practical application in sports data analytics. Sports Analytics is essential reading for all students of sports analytics, and useful supplementary reading for students and professionals in talent identification and development, sports performance analysis, sports medicine and applied computer science.
Football Analytics With Python R
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Author : Eric A. Eager
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-08-15
Football Analytics With Python R written by Eric A. Eager and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-15 with Computers categories.
Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data. Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to: Apply basic statistical concepts to football datasets Describe football data with quantitative methods Create efficient workflows that offer reproducible results Use data science skills such as web scraping, manipulating data, and plotting data Implement statistical models for football data Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny And more
Basketball Data Science
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Author : Paola Zuccolotto
language : en
Publisher: CRC Press
Release Date : 2020-01-03
Basketball Data Science written by Paola Zuccolotto and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-03 with Business & Economics categories.
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 MBA 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.
Sports Analytics
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Author : Benjamin C. Alamar
language : en
Publisher: Columbia University Press
Release Date : 2013-08-06
Sports Analytics written by Benjamin C. Alamar and has been published by Columbia University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-06 with Sports & Recreation categories.
Benjamin C. Alamar founded the first journal dedicated to sports statistics, the Journal of Quantitative Analysis in Sports. He developed and teaches a class on sports analytics for managers at the University of San Francisco and has published numerous cutting-edge studies on strategy and player evaluation. Today, he cochairs the sports statistics section of the International Statistics Institute and consults with several professional teams and businesses in sports analytics. There isn't a better representative of this emerging field to show diverse organizations how to implement analytics into their decision-making strategies, especially as analytic tools grow increasingly complex. Alamar provides a clear, easily digestible survey of the practice and a detailed understanding of analytics' vast possibilities. He explains how to evaluate different programs and put them to use. Using concrete examples from professional sports teams and case studies demonstrating the use and value of analytics in the field, Alamar designs a roadmap for managers, general managers, and other professionals as they build their own programs and teach their approach to others.
Machine Learning And Data Mining For Sports Analytics
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Author : Ulf Brefeld
language : en
Publisher: Springer
Release Date : 2019-04-06
Machine Learning And Data Mining For Sports Analytics written by Ulf Brefeld and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-06 with Computers categories.
This book constitutes the refereed post-conference proceedings of the 5th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in Dublin, Ireland, in September 2018. The 12 full papers presented together with 4 challenge papers were carefully reviewed and selected from 24 submissions. The papers present a variety of topics, covering the team sports American football, basketball, ice hockey, and soccer, as well as the individual sports cycling and martial arts. In addition, four challenge papers are included, reporting on how to predict pass receivers in soccer.
Machine Learning And Data Mining For Sports Analytics
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Author : Ulf Brefeld
language : en
Publisher: Springer Nature
Release Date : 2020-12-09
Machine Learning And Data Mining For Sports Analytics written by Ulf Brefeld and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-09 with Computers categories.
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.
Data Analysis In Sport
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Author : Peter O'Donoghue
language : en
Publisher: Routledge
Release Date : 2014-10-24
Data Analysis In Sport written by Peter O'Donoghue and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-24 with Medical categories.
Making sense of sports performance data can be a challenging task but is nevertheless an essential part of performance analysis investigations. Focusing on techniques used in the analysis of sport performance, this book introduces the fundamental principles of data analysis, explores the most important tools used in data analysis, and offers guidance on the presentation of results. The book covers key topics such as: The purpose of data analysis, from statistical analysis to algorithmic processing Commercial packages for performance and data analysis, including Focus, Sportscode, Dartfish, Prozone, Excel, SPSS and Matlab Effective use of statistical procedures in sport performance analysis Analysing data from manual notation systems, player tracking systems and computerized match analysis systems Creating visually appealing ‘dashboard’ interfaces for presenting data Assessing reliability. The book includes worked examples from real sport, offering clear guidance to the reader and bringing the subject to life. This book is invaluable reading for any student, researcher or analyst working in sport performance or undertaking a sport-related research project or methods course