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The rapid advancement of artificial intelligence (AI), augmented (AR) and virtual reality (VR), and the associated evolving social behavior could likely catalyze a remarkable transformation in the consumption of top-tier sports. Nonetheless, existing research efforts have neglected to explore whether and how the sports management practice might need to adapt their most valuable asset, that is, the media product, to cater to future consumer needs effectively. As such, in this study, we add to the still-emerging literature by synthesizing experts' opinions to project the future of the top-tier sports media product. Based on the assessment of 71 industry experts, our results indicate how we consume top-tier sports will significantly transform by 2030. Moreover, our research extends beyond sport-specific features, elucidating the imperative for content customization and personalization and the capacity for consumers to enhance the product, thereby creating an increasingly immersive experience. These findings bear great relevance to the sports industry and across diverse sectors. • We explore whether (and how) the top-tier sports media product might need to adapt in the future. • We synthesize 71 experts' opinions to project the future of the top-tier sports media product. • We find that the way we consume top-tier sports is currently undergoing a significant transformation. [ABSTRACT FROM AUTHOR]

• We apply machine learning to forecast the Olympic medal distribution. • We are first to consistently outperform the more traditional naïve forecast. • We also improve the forecasting accuracy presented in more recent work. Forecasting the number of Olympic medals for each nation is highly relevant for different stakeholders: Ex ante, sports betting companies can determine the odds while sponsors and media companies can allocate their resources to promising teams. Ex post, sports politicians and managers can benchmark the performance of their teams and evaluate the drivers of success. We apply machine learning, more specifically a two-staged Random Forest, to a dataset containing socioeconomic variables of 206 countries (1991–2020). For the first time, we outperform the more traditional naïve forecast for four consecutive Olympics between 2008 and 2020. [ABSTRACT FROM AUTHOR]

• Population-representative survey data from 11 European countries and the USA. • Context-specific orientations play a decisive role for individuals' affective feelings. • Affective feelings exert a strong influence on the support for public mega projects. • Effortful processing filters the influence of affective feelings on decisions. • The filtering mechanism, however, is rather ineffective. When facing complex decisions, individuals often employ heuristics, relying on affective feelings rather than systematically evaluating decisional pros and cons. If this heuristic misguides the personal decisions, the consequences may be unfortunate for the individuals but not harmful to the wider society. This is not the case, however, for decisions with a public policy impact, such as the approval of public mega projects, which can result in inefficient government spending. This study thus examines the formation and interplay of cognitive versus affective decision components in the context of these projects. More specifically, using population-representative survey data from 11 European countries and the US, the authors provide evidence for three major findings: First, context-specific orientations play a more decisive role for individuals' affective feelings than their general orientations. Second, affective feelings exert a strong influence on their support for public mega projects. Third, although effortful processing filters the influence of affective feelings on decisions, the filtering mechanism is rather ineffective. [ABSTRACT FROM AUTHOR]