Revenue sharing in a sports league with an open market in playing talent

In this paper we develop an economic model of a professional sports league, in which the teams acquire playing talent in an external market. There have been several earlier formulations of this open model and all rely upon an inappropriately specified revenue function. Team revenues should depend upon the absolute quality of the teams, as well as their relative quality measured by win-percent. An inference that has been cited widely in this literature is that revenue sharing increases competitive inequality. We show that this analysis is flawed. If the revenue function is specified appropriately, gate revenue sharing always reduces competitive inequality

Strategic Behaviour and Risk Taking in Football

This article develops a dynamic game-theoretic model of optimizing strategic behaviour by football teams. Teams choose continuously between defensive and attacking formations and between a non-violent and a violent playing style. Starting from the end of the match and working backwards, the teams' optimal strategies conditional on the current state of the match are determined by solving a series of two-person non-cooperative subgames. Numerical simulations are used to explore the sensitivity of strategic behaviour to variations in the structural parameters. The model is tested empirically, using English football league data. Teams that are trailing are willing to bear an increased risk of a player dismissal in order to increase the probability of scoring. Teams that are leading or level in scores play cautiously. The scoring rates of teams that are trailing are higher than those of teams that are ahead or level. Stochastic simulations are used to obtain probabilities for match results, conditional upon the state of the match at any stage. The article's main theoretical and empirical results constitute novel, non-experimental evidence that the strategic behaviour of football teams can be rationalized in accordance with game-theoretic principles of optimizing strategic behaviour by agents when payoffs are uncertain and interdependent.

Strategic behaviour and risk taking in football

This article develops a dynamic game-theoretic model of optimizing strategic behaviour by football teams. Teams choose continuously between defensive and attacking formations and between a non-violent and a violent playing style. Starting from the end of the match and working backwards, the teams’ optimal strategies conditional on the current state of the match are determined by solving a series of two-person non-cooperative subgames. Numerical simulations are used to explore the sensitivity of strategic behaviour to variations in the structural parameters. The model is tested empirically, using English football league data. Teams that are trailing are willing to bear an increased risk of a player dismissal in order to increase the probability of scoring. Teams that are leading or level in scores play cautiously. The scoring rates of teams that are trailing are higher than those of teams that are ahead or level. Stochastic simulations are used to obtain probabilities for match results, conditional upon the state of the match at any stage. The article’s main theoretical and empirical results constitute novel, non-experimental evidence that the strategic behaviour of football teams can be rationalized in accordance with game-theoretic principles of optimizing strategic behaviour by agents when payoffs are uncertain and interdependent.

LSTM Deep Neural Networks Postfiltering for Improving the Quality of Synthetic Voices

Recent developments in speech synthesis have produced systems capable of outcome intelligible speech, but now researchers strive to create models that more accurately mimic human voices. One such development is the incorporation of multiple linguistic styles in various languages and accents. HMM-based Speech Synthesis is of great interest to many researchers, due to its ability to produce sophisticated features with small footprint. Despite such progress, its quality has not yet reached the level of the predominant unit-selection approaches that choose and concatenate recordings of real speech. Recent efforts have been made in the direction of improving these systems. In this paper we present the application of Long-Short Term Memory Deep Neural Networks as a Postfiltering step of HMM-based speech synthesis, in order to obtain closer spectral characteristics to those of natural speech. The results show how HMM-voices could be improved using this approach.Comment: 5 pages, 5 figure

How do Public Laboratories Collaborate with Industry? New Survey Evidence from France.

This paper uses a survey of 130 public laboratories in France to investigate collaborative activities of laboratories with industry. Our statistical analysis shows that knowledge and technology development and transfer occurs most frequently through collaborative and contract research, informal exchanges, conferences, and consortia. The main benefits from the perspective of laboratories are the tangible and intangible inputs received –funds, materials, research suggestions and data. The outputs of collaboration are most often theses and publications along with technological artefacts (new products & processes, software) while patents, licenses and copyrights are less frequent. Collaboration with industry leads laboratories to conduct research in a more timely and reliable way, as well as focused in more applied areas.Economics of Science; Public-Private Research Partnerships; Knowledge and Technology Transfer; University-Industry Collaborations; France;

Addressing societal challenges: Joined-up research funding could facilitate innovation and engagement.

With changes looming for research councils and research funding as a whole, John Goddard looks at what a more joined-up research council driven by societal challenges would mean for the social sciences. Universities are going to have to increase their capacity to support engagement with society. The social science community therefore needs to actively enter into the fray locally and nationally and demonstrate that they are working alongside colleagues in science, engineering, medicine and the humanities particularly to address societal challenges

The importance of thermal neutron scattering laws in reactor calculations

Imperial Users onl

Effort levels in contests: an empirical application of the Tullock model

Empirical applications of the Tullock contest model are rare, due in part to the non-observability of effort. This paper presents an application of the standard Tullock model in a setting where effort can be observed and explained. A simple contest model is used to predict levels of effort in English soccer, with data on fouls and yellow and red cards used to reflect the effort of teams. Effort levels are found to be higher in matches between evenly balanced teams, and in matches with implications for end-of-season outcomes. The results suggest that the teams’ effort levels are strategic complements.Tullock contest, team sport, strategic complements.

The cationic region of Rhes mediates its interactions with specific Gβ subunits

Ras homologue enriched in striatum (Rhes) is a small monomeric G protein which functions in a variety of cellular processes, including attenuation of G protein-coupled receptor (GPCR)signalling. There have been many studies into the effects of Rhes, but there is no molecular information about how Rhes might bring about these effects. Rhes shares striking sequence homology to AGS1 (activator of G protein signalling 1) and we considered whether the two proteins function in similar ways. AGS1 binds to the Gβ1 subunit of heterotrimeric G proteins and we have used yeast two-hybrid studies to show that Rhes binds selectively to Gβ1, Gβ2 and Gβ3 subunits. Binding to the Gβ subunits involves the cationic regions of AGS1 and Rhes, and we used Rhes-AGS1 chimeras to show that their different cationic regions determine the Gβ-specificity of the interactions. Possible implications of this interaction for the activity of Rhes are discussed