Football Analytics With Python R

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Football Analytics with Python & R

Eric A. Eager,Richard A. Erickson

Author : Eric A. Eager,Richard A. Erickson
Publisher : "O'Reilly Media, Inc."
Page : 352 pages
File Size : 54,8 Mb
Release : 2023-08-15
Category : Computers
ISBN : 9781492099598

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Football Analytics with Python & R by Eric A. Eager,Richard A. Erickson Pdf

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

Daniel Memmert,Dominik Raabe

Author : Daniel Memmert,Dominik Raabe
Publisher : Taylor & Francis
Page : 212 pages
File Size : 43,7 Mb
Release : 2023-12-22
Category : Sports & Recreation
ISBN : 9781003817048

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Data Analytics in Football by Daniel Memmert,Dominik Raabe Pdf

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

Thomas W. Miller

Author : Thomas W. Miller
Publisher : FT Press
Page : 576 pages
File Size : 49,7 Mb
Release : 2015-11-18
Category : Business & Economics
ISBN : 9780133887419

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Sports Analytics and Data Science by Thomas W. Miller Pdf

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.

Test-Driven Development with Python

Harry Percival

Author : Harry Percival
Publisher : "O'Reilly Media, Inc."
Page : 624 pages
File Size : 52,9 Mb
Release : 2017-08-02
Category : Computers
ISBN : 9781491958650

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Test-Driven Development with Python by Harry Percival Pdf

By taking you through the development of a real web application from beginning to end, the second edition of this hands-on guide demonstrates the practical advantages of test-driven development (TDD) with Python. You’ll learn how to write and run tests before building each part of your app, and then develop the minimum amount of code required to pass those tests. The result? Clean code that works. In the process, you’ll learn the basics of Django, Selenium, Git, jQuery, and Mock, along with current web development techniques. If you’re ready to take your Python skills to the next level, this book—updated for Python 3.6—clearly demonstrates how TDD encourages simple designs and inspires confidence. Dive into the TDD workflow, including the unit test/code cycle and refactoring Use unit tests for classes and functions, and functional tests for user interactions within the browser Learn when and how to use mock objects, and the pros and cons of isolated vs. integrated tests Test and automate your deployments with a staging server Apply tests to the third-party plugins you integrate into your site Run tests automatically by using a Continuous Integration environment Use TDD to build a REST API with a front-end Ajax interface

Python and R for the Modern Data Scientist

Rick J. Scavetta,Boyan Angelov

Author : Rick J. Scavetta,Boyan Angelov
Publisher : "O'Reilly Media, Inc."
Page : 199 pages
File Size : 49,5 Mb
Release : 2021-06-22
Category : Computers
ISBN : 9781492093374

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Python and R for the Modern Data Scientist by Rick J. Scavetta,Boyan Angelov Pdf

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

Behavioral Data Analysis with R and Python

Florent Buisson

Author : Florent Buisson
Publisher : "O'Reilly Media, Inc."
Page : 361 pages
File Size : 42,7 Mb
Release : 2021-06-15
Category : Business & Economics
ISBN : 9781492061342

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Behavioral Data Analysis with R and Python by Florent Buisson Pdf

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

Basketball Data Science

Paola Zuccolotto,Marica Manisera

Author : Paola Zuccolotto,Marica Manisera
Publisher : CRC Press
Page : 219 pages
File Size : 51,8 Mb
Release : 2020-01-03
Category : Business & Economics
ISBN : 9780429894268

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Basketball Data Science by Paola Zuccolotto,Marica Manisera Pdf

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.

Text Analytics with Python

Dipanjan Sarkar

Author : Dipanjan Sarkar
Publisher : Apress
Page : 688 pages
File Size : 55,8 Mb
Release : 2019-05-21
Category : Computers
ISBN : 9781484243541

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Text Analytics with Python by Dipanjan Sarkar Pdf

Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. This second edition has gone through a major revamp and introduces several significant changes and new topics based on the recent trends in NLP. You’ll see how to use the latest state-of-the-art frameworks in NLP, coupled with machine learning and deep learning models for supervised sentiment analysis powered by Python to solve actual case studies. Start by reviewing Python for NLP fundamentals on strings and text data and move on to engineering representation methods for text data, including both traditional statistical models and newer deep learning-based embedding models. Improved techniques and new methods around parsing and processing text are discussed as well. Text summarization and topic models have been overhauled so the book showcases how to build, tune, and interpret topic models in the context of an interest dataset on NIPS conference papers. Additionally, the book covers text similarity techniques with a real-world example of movie recommenders, along with sentiment analysis using supervised and unsupervised techniques. There is also a chapter dedicated to semantic analysis where you’ll see how to build your own named entity recognition (NER) system from scratch. While the overall structure of the book remains the same, the entire code base, modules, and chapters has been updated to the latest Python 3.x release. What You'll Learn • Understand NLP and text syntax, semantics and structure• Discover text cleaning and feature engineering• Review text classification and text clustering • Assess text summarization and topic models• Study deep learning for NLP Who This Book Is For IT professionals, data analysts, developers, linguistic experts, data scientists and engineers and basically anyone with a keen interest in linguistics, analytics and generating insights from textual data.

Mathletics

Wayne L. Winston

Author : Wayne L. Winston
Publisher : Princeton University Press
Page : 391 pages
File Size : 45,5 Mb
Release : 2012-03-18
Category : Mathematics
ISBN : 9781400842070

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Mathletics by Wayne L. Winston Pdf

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.

Soccermatics

David Sumpter

Author : David Sumpter
Publisher : Bloomsbury Publishing
Page : 288 pages
File Size : 47,8 Mb
Release : 2016-05-05
Category : Mathematics
ISBN : 9781472924155

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Soccermatics by David Sumpter Pdf

'Football looked at in a very different way' Pat Nevin, former Chelsea and Everton star and football media analyst Football – the most mathematical of sports. From shot statistics and league tables to the geometry of passing and managerial strategy, the modern game is filled with numbers, patterns and shapes. How do we make sense of them? The answer lies in the mathematical models applied in biology, physics and economics. Soccermatics brings football and mathematics together in a mind-bending synthesis, using numbers to help reveal the inner workings of the beautiful game. This new and expanded edition analyses the current big-name players and teams using mathematics, and meets the professionals working inside football who use numbers and statistics to boost performance. Welcome to the world of mathematical modelling, expressed brilliantly by David Sumpter through the prism of football. No matter who you follow – from your local non-league side to the big boys of the Premiership, La Liga, the Bundesliga, Serie A or the MLS – you'll be amazed at what mathematics has to teach us about the world's favourite sport.

Text Analytics with Python

Dipanjan Sarkar

Author : Dipanjan Sarkar
Publisher : Apress
Page : 397 pages
File Size : 50,7 Mb
Release : 2016-11-30
Category : Computers
ISBN : 9781484223888

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Text Analytics with Python by Dipanjan Sarkar Pdf

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 Build a 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

Analyzing Baseball Data with R, Second Edition

Max Marchi,Jim Albert,Benjamin S. Baumer

Author : Max Marchi,Jim Albert,Benjamin S. Baumer
Publisher : CRC Press
Page : 318 pages
File Size : 41,5 Mb
Release : 2018-11-19
Category : Mathematics
ISBN : 9781351107075

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Analyzing Baseball Data with R, Second Edition by Max Marchi,Jim Albert,Benjamin S. Baumer Pdf

Analyzing Baseball Data with R Second Edition introduces R to sabermetricians, baseball enthusiasts, and students interested in exploring the richness of baseball data. It equips you with the necessary skills and software tools to perform all the analysis steps, from importing the data to transforming them into an appropriate format to visualizing the data via graphs to performing a statistical analysis. The authors first present an overview of publicly available baseball datasets and a gentle introduction to the type of data structures and exploratory and data management capabilities of R. They also cover the ggplot2 graphics functions and employ a tidyverse-friendly workflow throughout. Much of the book illustrates the use of R through popular sabermetrics topics, including the Pythagorean formula, runs expectancy, catcher framing, career trajectories, simulation of games and seasons, patterns of streaky behavior of players, and launch angles and exit velocities. All the datasets and R code used in the text are available online. New to the second edition are a systematic adoption of the tidyverse and incorporation of Statcast player tracking data (made available by Baseball Savant). All code from the first edition has been revised according to the principles of the tidyverse. Tidyverse packages, including dplyr, ggplot2, tidyr, purrr, and broom are emphasized throughout the book. Two entirely new chapters are made possible by the availability of Statcast data: one explores the notion of catcher framing ability, and the other uses launch angle and exit velocity to estimate the probability of a home run. Through the book’s various examples, you will learn about modern sabermetrics and how to conduct your own baseball analyses. Max Marchi is a Baseball Analytics Analyst for the Cleveland Indians. He was a regular contributor to The Hardball Times and Baseball Prospectus websites and previously consulted for other MLB clubs. Jim Albert is a Distinguished University Professor of statistics at Bowling Green State University. He has authored or coauthored several books including Curve Ball and Visualizing Baseball and was the editor of the Journal of Quantitative Analysis of Sports. Ben Baumer is an assistant professor of statistical & data sciences at Smith College. Previously a statistical analyst for the New York Mets, he is a co-author of The Sabermetric Revolution and Modern Data Science with R.

See the First Steps: Football Analytics

Rodney Paul

Author : Rodney Paul
Publisher : Unknown
Page : 150 pages
File Size : 42,5 Mb
Release : 2020-08-15
Category : Electronic
ISBN : 173552400X

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See the First Steps: Football Analytics by Rodney Paul Pdf

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.

No Game for Boys to Play

Kathleen Bachynski

Author : Kathleen Bachynski
Publisher : Studies in Social Medicine
Page : 296 pages
File Size : 40,5 Mb
Release : 2019
Category : Health & Fitness
ISBN : 1469653702

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No Game for Boys to Play by Kathleen Bachynski Pdf

"In 2016, the NFL admitted a link between degenerative brain disease and injuries resulting from tackle football. This admission sparked a new safety debate in professional football. However, the concerns about players' health do not start at the professional level, but at the beginning and intermediate levels of play. In this book, Kathleen Bachynksi tells the story of youth tackle football and the debates over player safety in the United States. In the postwar United States, high school football was celebrated as a "moral" sport for young boys, one that promised the creation of the honorable male citizen. However, Bachynski shows that throughout the twentieth century, coaches, sports equipment manufacturers, and even doctors were more concerned with "saving the game" than young boys' safety. By connecting the study of sport, health, childhood, and masculinity, Bachynski shows the social and physical vulnerability of young football players and how commonly held ideas of masculinity shape sport"--

Football Analytics With Python R

Football Analytics with Python & R by Eric A. Eager,Richard A. Erickson Pdf

Data Analytics in Football by Daniel Memmert,Dominik Raabe Pdf

Sports Analytics and Data Science by Thomas W. Miller Pdf

Test-Driven Development with Python by Harry Percival Pdf

Python and R for the Modern Data Scientist by Rick J. Scavetta,Boyan Angelov Pdf

Behavioral Data Analysis with R and Python by Florent Buisson Pdf

Basketball Data Science by Paola Zuccolotto,Marica Manisera Pdf

Text Analytics with Python by Dipanjan Sarkar Pdf

Mathletics by Wayne L. Winston Pdf

Soccermatics by David Sumpter Pdf

Text Analytics with Python by Dipanjan Sarkar Pdf

Analyzing Baseball Data with R, Second Edition by Max Marchi,Jim Albert,Benjamin S. Baumer Pdf

See the First Steps: Football Analytics by Rodney Paul Pdf

No Game for Boys to Play by Kathleen Bachynski Pdf

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