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Sports Data Mining (Integrated Series in Information Systems) Hardcover – September 30, 2010

ISBN-13: 978-1441967299 ISBN-10: 144196729X Edition: 2010th

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Product Details

  • Series: Integrated Series in Information Systems (Book 26)
  • Hardcover: 138 pages
  • Publisher: Springer; 2010 edition (September 30, 2010)
  • Language: English
  • ISBN-10: 144196729X
  • ISBN-13: 978-1441967299
  • Product Dimensions: 6.1 x 0.4 x 9.2 inches
  • Shipping Weight: 12.8 ounces (View shipping rates and policies)
  • Average Customer Review: 1.3 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #3,764,038 in Books (See Top 100 in Books)

Editorial Reviews

From the Back Cover

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 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, and greyhound racing are all covered, and the authors (including Hsinchun Chen, one of the most respected 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. Integrated Series in Information Systems (IS2) strives to publish scholarly work in the technical as well as the organizational side of the field. This series contains three sub-series including: expository and research monographs, integrative handbooks, and edited volumes, focusing on the state-of-the-art of application domains and/or reference disciplines, as related to information systems. In a parallel effort - recognizing that some of the cutting edge research in IS comes from doctoral research - selected dissertations are also published in the monograph section of the series.

About the Author

Dr. Robert Schumaker is an Assistant Professor in Information Systems at Iona College. Rob's overall research interests involve the uses of technology to acquire, deliver and make predictions in a variety of Business-related environments. These interests further branch into computer mediated communications, design science, human computer interfaces, machine learning algorithms, natural language processing, technology acceptance models and textual data mining. His recent research has focused on Sports Knowledge Management and Data Mining of relevant data from Sports-related databases and producing accurate predictions that can provide an edge to sports organizations and gamblers alike. Using the Moneyball style philosophy, this project analyzes the use of different machine learning techniques to predict outcomes of sporting events.

He has authored or co-authored many journal articles, including ACM Transactions on Information Systems, Decision Support Systems, IEEE Systems, Man and Cybernetics – Part A and Communications of the ACM.

Osama K. Solieman attended the University of Arizona graduating with a BS in Computer Science in 2003. In 2006, he received a MS in Management Information Systems where he was also the lead researcher on a database project for the Department of Electrical & Computer Engineering. Currently, he is an IT Consultant regularly working with Fortune 500 companies and traveling extensively around the world. He remains an avid sports fan and is active in his community.

Hsinchun Chen is McClelland Professor of Management Information Systems (MIS) at the Eller College of the University of Arizona and Andersen Consulting Professor of the Year (1999). He is the author of 15 books and more than 200 articles covering knowledge management, digital library, homeland security, Web computing, and biomedical informatics in leading information technology publications. He serves on ten editorial boards, including: Journal of the American Society for Information Science and Technology, ACM Transactions on Information Systems, IEEE Transactions on Systems, Man, and Cybernetics, IEEE Transactions on Intelligent Transportation Systems, International Journal of Digital Library, and Decision Support Systems. He has served as a Scientific Advisor/Counselor of the National Library of Medicine (USA), Academia Sinica (Taiwan), and National Library of China (China). Dr. Chen founded The University of Arizona Artificial Intelligence Lab in 1990. The group is distinguished for its applied and high-impact AI research. Since 1990, Dr. Chen has received more than $20M in research funding from various government agencies and major corporations. He has been a PI of the NSF Digital Library Initiative Program and the NIH NLM’s Biomedical Informatics Program. His group has developed advanced medical digital library and data and text mining techniques for gene pathway and disease informatics analysis and visualization since 1995. Dr. Chen’s nanotechnology patent analysis works, funded by NSF, have been published in the Journal of Nanoparticle Research. His research findings were used in the President’s Council of Advisors in Science and Technology’s report on "The National Nanotechnology Initiative at Five Years: Assessment and Recommendations of the National Nanotechnology Advisory Panel." Dr. Chen’s work also has been recognized by major US corporations and been awarded numerous industry awards for his contribution to IT education and research, including: AT&T Foundation Award in Science and Engineering and SAP Award in Research/Applications. Dr. Chen has been heavily involved in fostering digital library, medical informatics, knowledge management, and intelligence informatics research and education in the US and internationally. He has been a PI for more than 20 NSF and NIH research grants since 1990. Dr. Chen is conference chair of ACM/IEEE Joint Conference on Digital Libraries (JCDL) 2004 and has served as the conference general chair or international program committee chair for the past six International Conferences of Asian Digital Libraries (ICADL), 1998-2005. He has been instrumental in fostering the ICADL activities in Asia. Dr. Chen is the founder and also conference co-chair of the IEEE International Conference on Intelligence and Security Informatics (ISI), 2003-2006. The ISI conference has become the premiere meeting for international, national, and homeland security IT research. Dr. Chen is an IEEE fellow.


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Customer Reviews

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8 of 10 people found the following review helpful By Stephen Slash on February 8, 2011
Format: Hardcover
I have spent a whole day reading this hundred dollar book, and I cant find anything more than some introductory or preliminary information about how others relate data mining techniques to sports. The author tried so hard to give a lot of appraisal to this subject, but there is nothing a reader can really benefit from beside trusting the author that data mining works and look somewhere else.

My conclusion is, mathematics works in almost any human or natural event and if you want to understand something or get an answer, study it seriously.
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4 of 5 people found the following review helpful By Dimitri Shvorob on March 28, 2012
Format: Hardcover
Despite having two academics among its authors, the book has the quality of a master's thesis (in more ways than one: witness a non-native English speaker soldier on without assistance from a proof-reader) and almost nothing to say about data mining methods, and fills its 100-plus small and generously whitespaced pages with soft stuff, including a helicopter tour of athlete-performance statistics, sports-data vendors, two data-mining software packages (a couple of pages on each), and other entertaining but peripheral information. Shame on Springer, for greenlighting this book and giving it a grandiose title, a misleading editorial description, and an $85 price tag.
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2 of 3 people found the following review helpful By Jesse on March 30, 2013
Format: Hardcover
Another reviewer compared this book to a masters thesis which is offensive to masters thesis. It is at the level of a final project for a college class. It goes through multiple topics in a single page by doing not much more than mentioning the name of a topic and that someone uses it. Youll learn more about sports data mining from wikipedia articles. I have no idea why the publisher believes this is worth $100+.
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