Football Analytics with Python & R

Football Analytics with Python & R

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  • Author: Eric A. Eager
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1492099597
  • Category : Computers
  • Languages : en
  • Pages : 352

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


Data Analytics in Football

Data Analytics in Football

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  • Author: Daniel Memmert
  • Publisher: Taylor & Francis
  • ISBN: 1003817041
  • Category : Sports & Recreation
  • Languages : en
  • Pages : 212

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 they can be collected, modeled, analyzed, and interpreted. Introducing cutting-edge methods, the book challenges long-held assumptions and encourages a new way of thinking about football analysis. The book seeks to define the role of positional data in football match analysis by exploring topics such as the following: 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 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? Based on data collected from active leagues and fully revised for the new second edition, the text now also examines data collection in relation to other sports, how a data-driven approach in decision-making is achieved by professional teams, the potential of the new methods of data collection, and how they could evolve in the future. Accessibly written, packed full of examples from elite football, and supplemented with expert interviews, 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.


Sports Analytics and Data Science

Sports Analytics and Data Science

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  • Author: Thomas W. Miller
  • Publisher: FT Press
  • ISBN: 0133887413
  • Category : Business & Economics
  • Languages : en
  • Pages : 576

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.


Python and R for the Modern Data Scientist

Python and R for the Modern Data Scientist

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  • Author: Rick J. Scavetta
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1492093378
  • Category : Computers
  • Languages : en
  • Pages : 199

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

Sports Analytics

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  • Author: Benjamin C. Alamar
  • Publisher: Columbia University Press
  • ISBN: 023155589X
  • Category : Sports & Recreation
  • Languages : en
  • Pages : 219

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.


Basketball Data Science

Basketball Data Science

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  • Author: Paola Zuccolotto
  • Publisher: CRC Press
  • ISBN: 0429894260
  • Category : Business & Economics
  • Languages : en
  • Pages : 219

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.


Behavioral Data Analysis with R and Python

Behavioral Data Analysis with R and Python

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  • Author: Florent Buisson
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1492061344
  • Category : Business & Economics
  • Languages : en
  • Pages : 361

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)

Data Science and Analytics (with Python, R and SPSS Programming)

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  • Author: V.K. Jain
  • Publisher: KHANNA PUBLISHING HOUSE
  • ISBN: 9386173670
  • Category : Computers
  • Languages : en
  • Pages : 276

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.


See the First Steps: Football Analytics

See the First Steps: Football Analytics

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  • Author: Rodney Paul
  • Publisher:
  • ISBN: 9781735524009
  • Category :
  • Languages : en
  • Pages : 150

See the First Steps: Football Analytics offers an introduction to the exciting world of charts and statistics surrounding the hot topic of analytics for the sport of football. Using NFL data from Pro Football Reference and Microsoft Excel Software, readers are introduced to a wide range of basic and advanced statistics, statistical concepts, and a variety of charts for data visualization.For teen readers, central concepts covered on the SAT, ACT, and in AP Statistics are noted in the book, along with hands-on experience computing measures of central tendency and dispersion, and plotting numerous charts illustrating league leaders, great individual performances, and relationships between NFL statistics from the 2019 season. For adults, the book provides a refresher on statistics in addition to building skills using charts in Excel. These proficiencies are great for analysis of the NFL and other sports and also provide valuable general abilities which are transferrable to work-related reports and presentations. See the First Steps: Football Analytics provides the means to share your love for the sport of football, while building valuable skills for young and old alike and offers the opportunity to work together as family and/or friends to enhance your love for the sport of football. The end goal is to provide a framework where you can do your own analytics of NFL players and teams to deepen your understanding and enjoyment of the game.


Sports Analytics in Practice with R

Sports Analytics in Practice with R

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  • Author: Ted Kwartler
  • Publisher: John Wiley & Sons Incorporated
  • ISBN: 9781119598084
  • Category : Mathematics
  • Languages : en
  • Pages : 0

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.