Sports Data Mining

• Main Authors: Schumaker, Robert P. (Author), Solieman, Osama K. (Author), Chen, Hsinchun (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Boston, MA : Springer US : Imprint: Springer, 2010.
• Series: Integrated Series in Information Systems, 26
• Subjects: Computer science.; Operations research.; Decision making.; Information technology.; Business > Data processing.; Business mathematics.; Data mining.; Statistics.; Computer Science.; Data Mining and Knowledge Discovery.; Business Mathematics.; IT in Business.; Operation Research/Decision Theory.; Statistics for Business/Economics/Mathematical Finance/Insurance.

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 intrin...

Table of Contents:

• Sports Data Mining: The Field
• Sports Data Mining Methodology
• Data Sources for Sports
• Research in Sports Statistics
• Tools and Systems for Sports Data Analysis
• Predictive Modeling for Sports and Gaming
• Multimedia and Video Analysis for Sports
• Web Sports Data Extraction and Visualization
• Open Source Data Mining Tools for Sports
• Greyhound Racing Using Neural Networks: A Case Study
• Greyhound Racing Using Support Vector Machines: A Case Study
• Betting and Gaming
• Conclusions.