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on Sports and Economics |
| By: | J. James Reade (Department of Economics, University of Reading); Carl Singleton (Department of Economics, University of Reading); Alasdair Brown (School of Economics, University of East Anglia) |
| Abstract: | This study analyses point forecasts for a common set of events. These forecasts were made for distinct competitions and originally judged differently. The event outcomes were low-probability but had more predictable sub-outcomes upon which they were also judged. Hence, the forecasts were multi-dimensional, complicating any evaluation. The events were football matches in the English Premier League. The forecasts were of exact scoreline outcomes. We compare these with implied probability forecasts using bookmaker odds and a crowd of tipsters, as well as point and probabilistic forecasts generated from a statistical model suited to predicting football match scorelines. By evaluating these sources and types of forecast using various methods, we decide that forecasts of this type are strange, which we define. We argue that regression encompassing is the most appropriate way to compare point and probabilistic forecasts, and find that both types of forecasts for football match scorelines generally add information to one another. |
| Keywords: | Forecasting, Statistical modelling, Regression models, Prediction markets |
| JEL: | C53 L83 G14 G17 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:rdg:emxxdp:em-dp2019-18&r=all |
| By: | Smith, Gary (Pomona College); Hawkins, Jordan (Pomona College); Storrs, Jack (Pomona College) |
| Abstract: | There is a substantial and highly significant correlation between the performance of widely followed college football teams and the pre-college recruiting scores received by their players. This correlation implies a regression toward the mean that should be taken into account in the identification of under-performing and over-performing teams and can also be used to improve pre-season predictions of the performance of teams with highly rated and lowly rated recruits. |
| Keywords: | football recruting, regression to mean |
| Date: | 2019–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:clm:pomwps:1008&r=all |
| By: | Matt Andrews (Center for International Development at Harvard University) |
| Abstract: | Globalization has fed significant economic gains across the world. The gains lead some policymakers in developing countries to believe in the potential of ‘catch up’—where they leverage the gains of an open world economy to foster rapid progress and compete with more developed nations. This belief is particularly evident in countries like Rwanda, where policymakers aspire to turn the country into ‘Africa’s Singapore’. This paper asks if such aspiration is realistic: Do developing countries really gain enough from globalization to catch up to more developed countries? The paper examines the world economy as a league in which countries compete for winnings (manifest in higher income and production). Wealthier countries are in the top tiers of this league and poorer countries are in the lower tiers. The paper asks if gains from the last generation of growth have been distributed in such a way to foster ‘catch up’ by lower tier countries, and if we see these countries ‘catching up’ by moving into higher tiers. This analysis of the world economy is compared with a study of English football, where over 90 clubs play in an multi-tier league system. Prominent examples of ‘catch up’ in this system include Leicester City’s rise from the third tier in 2008 to become first tier champion in 2015. The paper asks if such ‘catch up’ is common in English football, given the way winnings are distributed, and if ‘catch up’ is more common in this context than in the world economy more generally. |
| Keywords: | Globalization |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:cid:wpfacu:345&r=all |