Research Papers

Clayton Graham

Abstract: With over a trillion dollars1 being risked on worldwide sports gambling every year, the interest to modeling game performance in general and baseball in particular has gained growing popularity. Integrating baseball game modeling with analytically based gambling, allows for these two elements to be exploited with a single objective: profiting from the marketplace inequities between the game (production) and betting markets (price and lines). Two questions will be addressed: First, can an accurate baseball gaming model be derived and used to calculate the probability of winning and the economic consequence predicated upon the betting line? Second, what is the optimal bet size based upon the risk tolerances (operational constraints) of the investor? Included will be the derivation of a production function which can be used to calculate the probability of a winning team. Defining the implication of the betting line will address cost, payoffs, and the implied probabilities of winning. Expected Return on Investment and Betting Edge will provide an economics perspective.