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Football Analytics With Python R

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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

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

Data Analytics In Football

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Author : Daniel Memmert
language : en
Publisher: Routledge
Release Date : 2018-05-30

Data Analytics In Football written by Daniel Memmert and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-30 with Sports & Recreation categories.

Data Analytics in Football provides students, researchers and coaches with a firm grounding in the principles of modern performance analysis. It offers an insight into the use of positional data, exploring how it can be collected, modelled, analysed and interpreted. Introducing cutting-edge methods, the book challenges long-held assumptions and encourages a new way of thinking about football analysis. Based on data collected from the German Bundesliga and the UEFA Champions League, the book seeks to define the role of positional data in football match analysis by exploring topics such as: What is positional data analysis and how did it emerge from conventional match analysis? How can positional data be collected and which technologies can be used? What are the benefits of a data-driven approach to decision making in football? What Key Performance Indicators based on positional data should be used? How can traditional match analysis be complemented by using positional data and advanced KPIs? How can these new methods evolve in the future? Accessibly written, packed full of examples from elite football and supplemented with expert interviews (Ralf Rangnick, Urs Siegenthaler and others), Data Analytics in Football is a thought-provoking, rigorously evidence-based guide to the use of data analytics in football performance analysis. As such, it is a vital resource for any student, researcher or coach interested in performance analysis and skill acquisition, or anyone interested in football more generally.

Mathletics

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Author : Wayne L. Winston
language : en
Publisher: Princeton University Press
Release Date : 2012-03-18

Mathletics written by Wayne L. Winston and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-18 with Mathematics categories.

How math can be used to improve performance and predict outcomes in professional sports Mathletics is a remarkably entertaining book that shows readers how to use simple mathematics to analyze a range of statistical and probability-related questions in professional baseball, basketball, and football, and in sports gambling. How does professional baseball evaluate hitters? Is a singles hitter like Wade Boggs more valuable than a power hitter like David Ortiz? Should NFL teams pass or run more often on first downs? Could professional basketball have used statistics to expose the crooked referee Tim Donaghy? Does money buy performance in professional sports? In Mathletics, Wayne Winston describes the mathematical methods that top coaches and managers use to evaluate players and improve team performance, and gives math enthusiasts the practical tools they need to enhance their understanding and enjoyment of their favorite sports—and maybe even gain the outside edge to winning bets. Mathletics blends fun math problems with sports stories of actual games, teams, and players, along with personal anecdotes from Winston's work as a sports consultant. Winston uses easy-to-read tables and illustrations to illuminate the techniques and ideas he presents, and all the necessary math concepts—such as arithmetic, basic statistics and probability, and Monte Carlo simulations—are fully explained in the examples. After reading Mathletics, you will understand why baseball teams should almost never bunt, why football overtime systems are unfair, why points, rebounds, and assists aren't enough to determine who's the NBA's best player—and much, much more. In a new epilogue, Winston discusses the stats and numerical analysis behind some recent sporting events, such as how the Dallas Mavericks used analytics to become the 2011 NBA champions.

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.

Behavioral Data Analysis With R And Python

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Author : Florent Buisson
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-06-15

Behavioral Data Analysis With R And Python written by Florent Buisson 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 2021-06-15 with Business & Economics categories.

Harness the full power of the behavioral data in your company by learning tools specifically designed for behavioral data analysis. Common data science algorithms and predictive analytics tools treat customer behavioral data, such as clicks on a website or purchases in a supermarket, the same as any other data. Instead, this practical guide introduces powerful methods specifically tailored for behavioral data analysis. Advanced experimental design helps you get the most out of your A/B tests, while causal diagrams allow you to tease out the causes of behaviors even when you can't run experiments. Written in an accessible style for data scientists, business analysts, and behavioral scientists, thispractical book provides complete examples and exercises in R and Python to help you gain more insight from your data--immediately. Understand the specifics of behavioral data Explore the differences between measurement and prediction Learn how to clean and prepare behavioral data Design and analyze experiments to drive optimal business decisions Use behavioral data to understand and measure cause and effect Segment customers in a transparent and insightful way

Data Science And Analytics With Python R And Spss Programming

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Author : V.K. Jain
language : en
Publisher: KHANNA PUBLISHING HOUSE
Release Date :

Data Science And Analytics With Python R And Spss Programming written by V.K. Jain and has been published by KHANNA PUBLISHING HOUSE this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

The Book has been written completely as per AICTE recommended syllabus on "Data Sciences". SALIENT FEATURES OF THE BOOK: Explains how data is collected, managed and stored for data science. With complete courseware for understand the key concepts in data science including their real-world applications and the toolkit used by data scientists. Implement data collection and management. Provided with state of the arts subjectwise. With all required tutorials on R, Python and Bokeh, Anaconda, IBM SPSS-21 and Matplotlib.

Python And R For The Modern Data Scientist

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Author : Rick J. Scavetta
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-06-22

Python And R For The Modern Data Scientist written by Rick J. Scavetta 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 2021-06-22 with Computers categories.

Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists from the Python and R communities along the path to becoming bilingual. By recognizing the strengths of both languages, you'll discover new ways to accomplish data science tasks and expand your skill set. Authors Rick Scavetta and Boyan Angelov explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. You'll learn how to use Python and R together in real-world settings and broaden your job opportunities as a bilingual data scientist. Learn Python and R from the perspective of your current language Understand the strengths and weaknesses of each language Identify use cases where one language is better suited than the other Understand the modern open source ecosystem available for both, including packages, frameworks, and workflows Learn how to integrate R and Python in a single workflow Follow a case study that demonstrates ways to use these languages together

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.

Text Analytics With Python

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Author : Dipanjan Sarkar
language : en
Publisher: Apress
Release Date : 2016-11-30

Text Analytics With Python written by Dipanjan Sarkar and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-30 with Computers categories.

Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. What You Will Learn: Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure Builda text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summarization, and cluster popular movie synopses and analyze the sentiment of movie reviews Implement Python and popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and Pattern Who This Book Is For : IT professionals, analysts, developers, linguistic experts, data scientists, and anyone with a keen interest in linguistics, analytics, and generating insights from textual data

Football Analytics With Python R

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