Sport consumers and markets have traditionally been thought to exhibit unique behaviors from traditional consumer products, particularly in respect to perceptions of loyalty. Yet, despite sport landscapes becoming increasingly crowded, there has been scant research measuring consumers’ repeat behavior in the context of the dense sports market. Through this research, we address this gap by applying Dirichlet modeling against the behaviors of 1,500 Australian sport consumers. Two questions are explored: First, do sport attendance markets exhibit purchase characteristics distinct from typical consumer markets? Second, do consumers treat sport leagues as complimentary or substitutable goods? The results provide evidence that consumer patterns within the sport attendance market are consistent to other repeat-purchase consumer markets. This finding further diminishes the long-held notion that sport requires unique methods of management. Furthermore, it was found that fans consume sport teams as complimentary products. As sport teams largely share their fans with other teams, practitioners must reorient their expectations around fan loyalty.
Hunter Fujak, Stephen Frawley, Heath McDonald and Stephen Bush
Job Fransen, Stephen Bush, Stephen Woodcock, Andrew Novak, Dieter Deprez, Adam D.G. Baxter-Jones, Roel Vaeyens and Matthieu Lenoir
Purpose: This study aimed to improve the prediction accuracy of age at peak height velocity (APHV) from anthropometric assessment using nonlinear models and a maturity ratio rather than a maturity offset. Methods: The dataset used to develop the original prediction equations was used to test a new prediction model, utilizing the maturity ratio and a polynomial prediction equation. This model was then applied to a sample of male youth academy soccer players (n = 1330) to validate the new model in youth athletes. Results: A new equation was developed to estimate APHV more accurately than the original model (new model: Akaike information criterion: −6062.1, R 2 = 90.82%; original model: Akaike information criterion = 3048.7, R 2 = 88.88%) within a general population of boys, particularly with relatively high/low APHVs. This study has also highlighted the successful application of the new model to estimate APHV using anthropometric variables in youth athletes, thereby supporting the use of this model in sports talent identification and development. Conclusion: This study argues that this newly developed equation should become standard practice for the estimation of maturity from anthropometric variables in boys from both a general and an athletic population.