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.
This book explores emerging research and pedagogy in analytics and data science that have become core to many businesses as they work to derive value from data. The chapters examine the role of analytics and data science to create, spread, develop and utilize analytics applications for practice. Selected chapters provide a good balance between discussing research advances and pedagogical tools in key topic areas in analytics and data science in a systematic manner. This book also focuses on several business applications of these emerging technologies in decision making, i.e., business analytics. The chapters in Analytics and Data Science: Advances in Research and Pedagogy are written by leading academics and practitioners that participated at the Business Analytics Congress 2015. Applications of analytics and data science technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination of the impact of these technologies and applications on business and society. As organizations in various sectors formulate their IT strategies and investments, it is imperative to understand how various analytics and data science approaches contribute to the improvements in organizational information processing and decision making. Recent advances in computational capacities coupled by improvements in areas such as data warehousing, big data, analytics, semantics, predictive and descriptive analytics, visualization, and real-time analytics have particularly strong implications on the growth of analytics and data science.
Analysis, Visualisation and Decision Making in Sports Performance
Author: Ambikesh Jayal
Category: Sports & Recreation
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.
The Science of Assessing Performance, Predicting Future Outcomes, Interpreting Statistical Models, and Evaluating the Market Value of Athletes
Author: Lorena Martin
Publisher: FT Press
A PRACTICAL, REAL-WORLD GUIDE TO ANALYTICS FOR THE 5 MAJOR SPORTS: FOOTBALL, BASKETBALL, BASEBALL, SOCCER, AND TENNIS GAIN A COMPETITIVE EDGE! This is the first real-world guide to building and using analytical models for measuring and assessing performance in the five major sports: football, basketball, baseball, soccer, and tennis. Unlike books that focus strictly on theory, this book brings together sports measurement and statistical analyses, demonstrating how to examine differences across sports as well as between player positions. This book will provide you with the tools for cutting-edge approaches you can extend to the sport of your choice. Expert Northwestern University data scientist, UC San Diego researcher, and competitive athlete, Lorena Martin shows how to use measures and apply statistical models to evaluate players, reduce injuries, and improve sports performance. You’ll learn how to leverage a deep understanding of each sport’s principles, rules, attributes, measures, and performance outcomes. Sports Performance Measurement and Analytics will be an indispensable resource for anyone who wants to bring analytical rigor to athletic competition: students, professors, analysts, fans, physiologists, coaches, managers, and sports executives alike. All data sets, extensive code, and additional examples are available for download at http://www.ftpress.com/martin/ What are the qualities a person must have to become a world-class athlete? This question and many more can be answered through research, measurement, statistics, and analytics. This book gives athletes, trainers, coaches, and managers a better understanding of measurement and analytics as they relate to sports performance. To develop accurate measures, we need to know what we want to measure and why. There is great power in accurate measures and statistics. Research findings can show us how to prevent injuries, evaluate strengths and weaknesses, improve team cohesion, and optimize sports performance. This book serves many readers. People involved with sports will gain an appreciation for performance measures and analytics. People involved with analytics will gain new insights into quantified values representing physical, physiological, and psychological components of sports performance. And students eager to learn about sports analytics will have a practical introduction to the field. This is a thorough introduction to performance measurement and analytics for five of the world’s leading sports. The only book of its kind, it offers a complete overview of the most important concepts, rules, measurements, and statistics for each sport, while demonstrating applications of real-world analytics. You’ll find practical, state-of-the-art guidance on predicting future outcomes, evaluating an athlete’s market value, and more.
This book is the first to combine principles from analytics, complex systems theory, multi-disciplinary diagnostics and sport performance analysis. It considers athletes, teams, and sport organizations in individual and team games as complex systems, and demonstrates how complexity studies can enrich analytics and give us a more sophisticated understanding of the causalities of winning and losing in sports. Part I introduces the basic categories of analytics and their uses in elite sport. Part II presents an original conception of sport analytics both as a complex of different kinds of processes and as a complexity-adapted view of human systems acting in sport performance and management. Part III considers the main principles of complex sport analytics, expanding the prism of complexity to include all levels of a sport organization from athletes, coaches and trainers to top decision makers, and suggests practical applications and simulations for cases of both individual and team sports. This is illuminating reading for any advanced student, researcher or practitioner working in sport analytics, performance analysis, coaching science or sport management.
Modeling Techniques in Predictive Analytics with R and Python
Author: Thomas W. Miller
Publisher: FT Press
Category: Business & Economics
Now , a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications. Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where Miller's widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes: The role of analytics in delivering effective messages on the web Understanding the web by understanding its hidden structures Being recognized on the web – and watching your own competitors Visualizing networks and understanding communities within them Measuring sentiment and making recommendations Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.
Performance Analysis Based on Spatiotemporal Tracking Data
Author: Daniel Link
Daniel Link explores how data analytics can be used for studying performance in soccer. Based on spatiotemporal data from the German Bundesliga, the six individual studies in this book present innovative mathematical approaches for game analysis and player assessment. The findings can support coaches and analysts to improve performance of their athletes and inspire other researchers to advance the research field of sports analytics.
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.
Data visualization is increasingly central to predictive analytics and data science. The book focuses on all three application areas of data visualization: exploratory data analysis, model diagnostics, and presentation graphics. Built on the same structure and approach as other books in Thomas W. Miller's popular Modeling Techniques series, it has been carefully designed to serve multiple audiences: business managers, analysts, programmers, and students. Miller begins with core principles, revealing why some data visualizations effectively present information and others don't. He reviews the science of human perception and cognition, proven principles of graphic design, and the growing role of visualization throughout data science -- including examples such as the visualization of time, networks, and maps. Drawing on his pioneering experience teaching data visualization, Miller begins each chapter by stating a real business problem. He explains why the problem is important, describes a relevant dataset, and guides you through solving it with leading open-source tools such as R, Python, D3, and Gephi. (All R and Python code is set apart, so managers or analysts who aren't interested in programming can easily skip it.) Like other books in this series, Data Visualization Principles and Practices draws realistic examples from key application areas, including marketing, finance, sports analytics, web and network data science, text analytics, and social network analysis. Examples include cross-sectional data, time series, network, and spatial data. Readers will discover advanced methods for constructing static and interactive graphics, building web-browser-based presentations, and even creating "information art.""
5th International Workshop, MLSA 2018, Co-located with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings
Author: Ulf Brefeld
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.