• Robert P. Schumaker
  • Osama K. Solieman
  • Hsinchun Chen
Part of the Integrated Series in Information Systems book series (ISIS, volume 26)


Over the next several years, sports data mining practices will be faced with several challenges and obstacles. The most obvious of which is to overcome the years of resistance by the members of sporting organizations that would rather stick with a traditional way of doing things. Aside from the challenges that are faced, sports data mining currently sits at a pivotal junction in history with many opportunities just waiting to be grabbed. Some avenues of opportunity will be pursued quickly, while others may take years or decades to become fruitful. In any event, sports data mining today is still in its infancy. While some first steps were made with pioneers such as Dean Oliver and Bill James, the next few years will become a transition period as the technology begins to mature within the sporting community and become more commonplace. New metrics, algorithms and ways of thinking will begin circulating themselves as the field enters puberty and begins to mature. The coming decades will be fascinating to watch.


Data Mining Technique Sport Organization Data Mining Approach Athletic Department Data Mining System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Lyons, K. 2005. Data Mining and Knowledge Discovery. Australian Sports Commission Journals 2(4).Google Scholar

Copyright information

© Springer US 2010

Authors and Affiliations

  • Robert P. Schumaker
    • 1
  • Osama K. Solieman
    • 2
  • Hsinchun Chen
    • 3
  1. 1.Cleveland State UniversityClevelandUSA
  2. 2.TucsonUSA
  3. 3.University of ArizonaTucsonUSA

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