Sports data mining / by Robert P. Schumaker, Osama K. Solieman, Hsinchun Chen
- 作者： Schumaker, Robert P.
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- 其他題名：
- Springer eBooks
- 出版： Boston, MA : Springer Science+Business Media, LLC 2010
- 叢書名： Integrated series in information systems ,v. 26
- 主題： Data mining. , Sports--Statistics. , Computer science , Data Mining and Knowledge Discovery. , Business Information Systems. , Operations Research/Decision Theory. , Statistics for Business/Economics/Mathematical Finance/Insurance.
- ISBN： 9781441967305 (electronic bk.) 、 9781441967299 (paper)
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電子書
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讀者標籤：
- 系統號： 005177009 | 機讀編目格式
館藏資訊
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.