|
on Sports and Economics |
Issue of 2013‒05‒19
two papers chosen by Joao Carlos Correia Leitao University of Beira Interior and Technical University of Lisbon |
By: | Siem Jan Koopman (VU University Amsterdam); Rutger Lit (VU University Amsterdam) |
Abstract: | Attack and defense strengths of football teams vary over time due to changes in the teams of players or their managers. We develop a statistical model for the analysis and forecasting of football match results which are assumed to come from a bivariate Poisson distribution with intensity coefficients that change stochastically over time. This development presents a novelty in the statistical time series analysis of match results from football or other team sports. Our treatment is based on state space and importance sampling methods which are computationally efficient. The out-of-sample performance of our methodology is verified in a betting strategy that is applied to the match outcomes from the 2010/11 and 2011/12 seasons of the English Premier League. We show that our statistical modeling framework can produce a significant positive return over the bookmaker's odds. |
Keywords: | Betting, Importance sampling, Kalman filter smoother, Non-Gaussian multivariate time series models, Sport statistics |
JEL: | C32 C35 |
Date: | 2012–09–27 |
URL: | http://d.repec.org/n?u=RePEc:dgr:uvatin:2012099&r=spo |
By: | Humphreys, Brad (University of Alberta, Department of Economics); Zhou, Li (University of Alberta, Department of Economics) |
Abstract: | We develop a monopolistic competition model of urban service consumption and production that includes spatial structure and property values. The model shows that the introduction of a new professional sports facility and team generates agglomeration effects that change the mix of services and property values, and increases local welfare, part of which is transferred to the team as subsidies for the construction of the facility. The distributional consequences of the new facility and the implications of property tax based financing for the subsidy are analyzed. |
Keywords: | agglomeration effects; sports facilities; subsidies |
JEL: | H71 L83 R13 R58 |
Date: | 2013–04–19 |
URL: | http://d.repec.org/n?u=RePEc:ris:albaec:2013_004&r=spo |