This article addresses the issue of contestant heterogeneity (CH) in team efforts in National Basketball Association games for the three seasons from 2013/14 to 2015/16. The results show that two teams’ total efforts regarding rebounds and fouls increase as CH becomes smaller. The evidence thus indicates that the two teams play harder the smaller that CH is. In the analysis of the effects of heterogeneity on the favorite’s and the underdog’s efforts, the results show that each tries harder when CH is reduced and makes less effort as it becomes larger. These results support the contamination hypothesis. The checks for robustness in the panel regressions and results of Hack-a-Shaq strategy reinforce these conclusions. The evidence also shows that the appearance of the previous year’s champion in a game decreases the two teams’ total number of rebounds and fouls. Overwhelming CH makes both favorites and underdogs exert less effort.
Organizers of major sports events regularly report impressive multibillion TV audiences to emphasize the success of their competitions, yet such claims are seldom substantiated with hard evidence, nor is it usually made clear what the numbers actually stand for. The aim of this paper is to provide a better insight into the ambiguity of reported audience sizes for sports events and to beg the question: What is the TV audience size for a live sports broadcast? By detailing seven pitfalls, we critically discuss the problems associated with a correct understanding of TV audiences for live sports broadcasts. We substantiate our findings with specific examples for various sports events. The paper demonstrates the relevance of a correct understanding of how TV audiences for sports broadcasts are determined and communicated, and the analysis of the pitfalls uncovers misunderstandings about reported TV audiences that have been largely ignored before. We also discuss the relevance of our insights for the growing body of academic literature in this field.
There is considerable discussion regarding interest in women’s basketball, with critics often comparing the Women’s National Basketball Association (WNBA) and the National Basketball Association (NBA). This comparison is problematic because the WNBA is in an early growth phase while the NBA organizational life cycle position is far more mature. We investigate whether the demand features of early growth leagues are similar by comparing attendance data from the 8th‒21st seasons of the WNBA with attendance from the same point in NBA history and the current NBA. We find the factors that affect demand in the WNBA are uniquely different than the NBA in both size and significance in either period; thus, it is inappropriate to compare the two leagues.
Jesyca Salgado-Barandela, Ángel Barajas and Patricio Sanchez-Fernandez
There are limitations in determining the economic impact of sporting events that need to be considered. One of these is represented by first-round leakages. This work focuses on explaining first-round leakages in the economic impact of sporting events on small cities. Seeking to identify this type of leakage, we estimated the spatial distribution of the economic impact of two small-sized events organized in a town with a population of 24,248 inhabitants. The results showed a first-round leakage exceeding €300,000 and identified higher average attendee expenditure in a more developed city adjacent to the host city. Moreover, an exploratory analysis concerning the influence of leakage in final spending was performed. Finally, the elements that would increase the probability of leakage were studied. Overall, the current case study highlighted the importance of considering the existence of leakage.
Jason P. Berkowitz, Craig A. Depken II and John M. Gandar
In this note, we comment on a recent paper in the journal that proposes a new normalization procedure when converting tennis betting odds to the implied probabilities of each player winning. The new procedure is especially germane for matches in which there is a heavy favorite and where there is concern that traditional conversion methods understate the true probability of the favorite winning. However, in this comment, we argue that the new adjustment, while an interesting contribution, suffers from at least three limitations that make the procedure relatively costly while not materially improving predictions of match outcomes.
