With every passing season, statistical analysis is playing an ever-increasing role in how hockey is played and covered. Knowledge of the underlying numbers can help fans stretch their enjoyment of the game. Acting as an invaluable supplement to traditional analysis, Stat Shot: A Fan’s Guide to Hockey Analytics can be used to test the validity of conventional wisdom and to gain insight into what teams are doing behind the scenes — or maybe what they should be doing! Inspired by Bill James’s Baseball Abstract, Rob Vollman has written a timeless reference of the mainstream applications and limitations of hockey analytics. With over 300 pages of fresh analysis, it includes a guide to the basics, how to place stats into context, how to translate data from one league to another, the most comprehensive glossary of hockey statistics, and more. Whether A Fan’s Guide to Hockey Analytics is used as a primer for today’s new statistics, as a reference for leading edge research and hard-to-find statistical data, or read for its passionate and engaging storytelling, it belongs on every serious fan’s bookshelf. A Fan’s Guide to Hockey Analytics makes advanced stats simple, practical, and fun.

Making advanced stats simple, practical, and fun for hockey fans Advanced stats give hockeyÍs powerbrokers an edge, and now fans can get in on the action. Stat Shot is a fun and informative guide hockey fans can use to understand and enjoy what analytics says about team building, a playerÍs junior numbers, measuring faceoff success, recording save percentage, the most one-sided trades in history, and everything you ever wanted to know about shot-based metrics. Acting as an invaluable supplement to traditional analysis, Stat Shot can be used to test the validity of conventional wisdom, and to gain insight into what teams are doing behind the scenes „ or maybe what they should be doing. Whether looking for a reference for leading-edge research and hard-to-find statistical data, or for passionate and engaging storytelling, Stat Shot belongs on every serious hockey fanÍs bookshelf.

Best known for Player Usage Charts and his record-breaking ESPN Insider contributions, Rob Vollman was first published in the fall 2001 issue of the Hockey Research Journal and has since co-authored 10 books in the Hockey Abstract, Hockey Prospectus, and McKeen's magazine series. He writes for NHL.com, and lives in Calgary, Alberta. Tom Awad is a Montreal-based electrical engineer who loves applying numbers to his job, hockey, and anything else he can get his hands on. He has co-authored six previous books on hockey analytics. Iain Fyffe created Hockeythink (originally Puckerings), the first dedicated hockey analytics site, in 2001. He has served as editor of the Hockey Research Journal and was a co-author of the books Hockey Prospectus 2011 and 2012 and Hockey Abstract 2014, as well as the author of On His Own Side of the Puck. He lives in Fredericton, New Brunswick

A fraction of a second can be the difference between a one-timer finding the back of the net and a blocked shot that starts transition the other way. In the fast and fluid game of hockey, time and space drive success. But hockey analytics hasn't appreciated these two most important factors. It hasn't respected the complexity of the game...until now. Backed by the findings of an original study never before released to the public, Hockey Analytics demonstrates that-whether it is a failed pinch in the offensive zone, a missed rotation in the defensive zone or other blunder-the vast majority of goals are scored when the defense's positioning is compromised. The authors identify the actions that give players the time and space to read, react and execute. Their findings will shock even the most experienced hockey minds and call into question strategies regularly employed by the game's best coaches. It is simple, actionable and nothing like you've seen before. Whether you're a fan, player or coach, Hockey Analytics will change how you experience hockey.

Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.

This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)

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.