Clayton Graham is an adjunct professor of Statistics and Economics at DePaul University. He holds senior positions with the Chaos Group, Inc. and Analytical Advantages, LLC where he functions as a management consultant specializing in analytical and graphic econometrics.
He will present a case study at the 2009 the 2009 Palisade Conference: Risk Analysis, Applications, & Training. The conference is set to take place on 21 – 22 October at the Hyatt Regency in Jersey City, 10 minutes by PATH from Manhattan’s Financial District.
See the abstract for Clay Graham’s case study below, and see the full schedule for the Conference here.
Capitalizing Upon Market Inequities:
A Game Plan for Successful Sports Wagering
Sports wagering brings two separate "markets" together. First is the production market or the game itself. The second is the wagering or betting market. As a matter of practicality, the wagering market is itself in balance, i.e., bet clearing is covered through the process of adjusting the cost-payout ratio (the line). Betting lines are translated into an expected probability of winning. This resultant probability is frequently inconsistent with the probability of the team actually winning.
Hence, the opportunity to capitalize upon the dichotomy between the inequities of the production and gaming markets will be detailed and quantified. The presentation will include:
- Fundamentals of gambling lines and odds,
- Identification of key metrics,
- Methods of production modeling baseball and basketball
(similarities and differences),
- Integration of economics (investment) with production,
- Economics of decision making.
Principal Palisade software utilized includes: StatTools (statistical analysis toolkit for Microsoft Excel), @RISK (risk analysis software using Monte Carlo techniques in Excel) and Evolver (genetic algorithm optimization in Excel). The presentation will have a heavy graphic and visualization emphasis. Theoretical statistics will be tightly tied with pragmatic realities of game modeling and economically based decision making.
Specific quantification will consist of:
- Probabilities of winning a game,
- Measurement bias of officials,
- Quantification of player performance,
- Expected values of return on investment,
- Sports gambling optimizing algorithm.
Examples of actual results for current and past seasons along with predictions will be provided.
In short, it’s "Card Counting" for sports!
More information about this project can be seen at Baseballwon.com.