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This brief highlights the application of performance analysis tools in data acquisition, and various machine learning algorithms for evaluating team performance as well as talent identification in beach soccer and sepak takraw. Numerous performance indicators and human performance parameters are considered based on their relevance to each sport. The findings presented here demonstrate that the key performance indicators as well as human performance parameters can be used in the future evaluation of team performance as well as talent identification in these sports. Accordingly, they offer a valuable resource for coaches, club managers, talent identification experts, performance analysts and other relevant stakeholders involved in performance assessments.
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.
To understand the dynamic patterns of behaviours and interactions between athletes that characterize successful performance in different sports is an important challenge for all sport practitioners. This book guides the reader in understanding how an ecological dynamics framework for use of artificial intelligence (AI) can be implemented to interpret sport performance and the design of practice contexts. By examining how AI methodologies are utilized in team games, such as football, as well as in individual sports, such as golf and climbing, this book provides a better understanding of the kinematic and physiological indicators that might better capture athletic performance by looking at the current state-of-the-art AI approaches. Artificial Intelligence in Sport Performance Analysis provides an all-encompassing perspective in an innovative approach that signals practical applications for both academics and practitioners in the fields of coaching, sports analysis, and sport science, as well as related subjects such as engineering, computer and data science, and statistics.
Data mining is the process of extracting hidden patterns from data, and it’s commonly used in business, bioinformatics, counter-terrorism, and, increasingly, in professional sports. First popularized in Michael Lewis’ best-selling Moneyball: The Art of Winning An Unfair Game, it is has become an intrinsic part of all professional sports the world over, from baseball to cricket to soccer. While an industry has developed based on statistical analysis services for any given sport, or even for betting behavior analysis on these sports, no research-level book has considered the subject in any detail until now. Sports Data Mining brings together in one place the state of the art as it concerns an international array of sports: baseball, football, basketball, soccer, greyhound racing are all covered, and the authors (including Hsinchun Chen, one of the most esteemed and well-known experts in data mining in the world) present the latest research, developments, software available, and applications for each sport. They even examine the hidden patterns in gaming and wagering, along with the most common systems for wager analysis.
It seems that artificial intelligence (AI) is always just five years away, but it never arrives. Recently, however. developments have made the practical utility of game theory a genuine reality. Will sport provide the petri dish in which AI will prove itself? What do domain specialists like managers and coaches want to know that they can’t currently find out, and can AI provide the answer? What competitive advantages might AI provide for recruitment, performance and tactics, health and fitness, pedagogy, broadcasting, eSports, gambling and stadium design in the future? Written by leading experts in both sports management and AI, AI for Sports begins to answer these and many other questions on the future of AI for sports.
Moneyball meets Freakonomics in this myth-busting guide to understanding—and winning—the most popular sport on the planet. Innovation is coming to soccer, and at the center of it all are the numbers—a way of thinking about the game that ignores the obvious in favor of how things actually are. In The Numbers Game, Chris Anderson, a former professional goalkeeper turned soccer statistics guru, teams up with behavioral analyst David Sally to uncover the numbers that really matter when it comes to predicting a winner. Investigating basic but profound questions—How valuable are corners? Which goal matters most? Is possession really nine-tenths of the law? How should a player’s value be judged?—they deliver an incisive, revolutionary new way of watching and understanding soccer.
The first book of its kind devoted to this topic, this comprehensive text/reference presents state-of-the-art research and reviews current challenges in the application of computer vision to problems in sports. Opening with a detailed introduction to the use of computer vision across the entire life-cycle of a sports event, the text then progresses to examine cutting-edge techniques for tracking the ball, obtaining the whereabouts and pose of the players, and identifying the sport being played from video footage. The work concludes by investigating a selection of systems for the automatic analysis and classification of sports play. The insights provided by this pioneering collection will be of great interest to researchers and practitioners involved in computer vision, sports analysis and media production.
This book highlights the recent research on soft computing and pattern recognition and their various practical applications. It presents 62 selected papers from the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020) and 35 papers from the 16th International Conference on Information Assurance and Security (IAS 2020), which was held online, from December 15 to 18, 2020. A premier conference in the field of artificial intelligence, SoCPaR-IAS 2020 brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from 40 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
We seem to be living in the age of A.I. Everywhere you look, companies are touting their most recent A.I., machine learning, and deep learning breakthroughs, even when they are far short of anything that could be dubbed a "breakthrough." "A.I." has eclipsed "Blockchain" and "Crypto" as the buzzword of today. The A.I. Sports Book breaks down A.I., machine learning, and deep learning into five unique business use cases-sound, time series, text, image, and video-and reveals how sports book marketing executives can utilize this powerful technology to help them more finely tune their marketing campaigns, better segment their customers, increase lead generation, and foster strong customer loyalty. Today, "Personalization"-the process of utilizing mobile, social, geo-location data, web morphing, context and even affective computing to tailor messages and experiences to an individual interacting with them-is becoming the optimum word in a radically new customer intelligence environment. The A.I. Sports Book explains this complex technology in simple to understand terms and then shows how sports book marketers can utilize the psychology of personalization with A.I. to both create more effective marketing campaigns as well as increase customer loyalty. Pearson shows companies how to avoid Adobe's warning of not using industrial-age technology in the digital era. Pearson also reveals how to create a platform of technology that seamlessly integrates EDW and real-time streaming data with social media content. Analytical models and neural nets can then be built on both commercial and open source technology to better understand the customer, thereby strengthening the brand and, just as importantly, increasing ROI.The A.I. Sports Book reveals how these and other technologies can help shape the customer journey. The book details how the five types of analytics-descriptive, diagnostic, predictive, prescriptive, and edge analytics-affect not only the customer journey, but also just about every operating function in a sports book. An IoT-connected sports book can make its operations smart. Connected devices can help with inventory optimization, labor management, marketing, and customer experience, as well as keep its data centers green and its energy use smart. Social media is no longer a vanity platform, but rather it is a place to both connect with current customers as well as court new ones. The A.I. Sports Book knows that social media can produce a healthy ROI, if done properly. Social media can also be utilized as a place to gauge a customer's psychological profile; it's amazing how much information there is in a Facebook like, a Twitter Tweet, or a YouTube comment. The A.I. Sports Book breaks down social media into its six different categories -- collaborative projects, blogs and micros blogs, content communities, social networks, virtual game worlds and virtual social worlds -- and shows sports books how to utilize each one to both market to individuals as well as to attain real-time competitive intel. This book will help sports betting executives break through the technological clutter so that they can deliver an unrivaled customer experience to each and every one of their patrons to ensure that they keep coming through those front doors, as well as onto their websites.
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.