 Bio
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Research
Contact Information
CIS Department
Ahuja College of Business
Cleveland State University
2121 Euclid Ave
Cleveland, OH 44115
rob.schumaker@gmail.com
Phone: (216) 687-4760
Founder & President,
The Schumaker Foundation
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Sports Data Mining
Because many of the sports we watch and enjoy have human participation, there is a degree of predictability that can be uncovered. Recording events and running statistical tests is a good start, but that doesn't always paint the complete picture. This research area investigates taking sports to the next level by identifying the patterns, trends and tendencies that can exist within the data. This information can be formed into knowledge (observable rules) and provide an organization with a competitive advantage by identifying the weaknesses of their opponents and formulating strategies to exploit them. The techniques used are not isolated to only human participants, greyhounds and thoroughbreds also exhibit predictive behavior. It is the process of isolating the important variables and learning from prior events that makes Sports Data Mining possible.
AZGreyhound
Greyhound racing is an exciting sport that works well with Sports Data Mining and machine learning in particular. Leveraging advanced web mining and machine learning techniques, the AZGreyhound system was able to identify winners 45.35% of the time and furthermore would correctly identify Superfecta Box combination winners 6.35% of the time as compared to random chance at 2.79%. The results of this study are presented in An Investigation of SVM Regression to Predict Longshot Greyhound Races.
S&C Racing
Following upon the success of AZGreyhound, the program was expanded to include other racing sports such as Harness racing. This series of research papers investigate portability of greyhound machine learning techniques to harness racing, compares them against track experts, crowd wisdom and other successful predictive techniques such as the Dr. Z System and then investigates the proper amount of race history to optimize the machine learning algorithms. Further extensions of this work include investigating different machine learning techniques and adapting this to thoroughbred and Nascar prediction.
Books and Interviews
Dr. Schumaker has also written a book on Sports Data Mining, published by Springer.
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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. A full draft TOC is attached.
With combined (NFL; MLB; NBA; NHL) team values in the US running at more than $42 billion (NFL alone was at $33.3 billion in 2008!), and European soccer teams at over $10 billion, professional team sports worldwide is a massive business that is about to experience its first real contraction in over ten years. Combine that with the proven effectiveness -- and growing use -- of statistical analysis to produce winning teams (and thus higher revenues), and then consider the sharp growth in college programs in sports business: an eager market awaits this book in the sports business market alone. It will also appeal to researchers in data mining broadly; the sports statistics service industry that’s developed in the last ten years; and anyone studying any of the pari-mutuel wagering sports around the world.
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Dr. Schumaker's Sports Data Mining research was also featured in an interview in IEEE Intelligent Systems.
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