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on Sports and Economics |
| By: | Neville Welch (Capitol Technology University, USA); Darrell Norman (Capitol Technology University, USA) |
| Abstract: | The relentless pursuit of competitive excellence in sports has long paralleled technological innovation, and in recent years, artificial intelligence has emerged as a transformative force reshaping the athletic landscape. This perspective paper critically examines the multifaceted implications of AI-powered technologies, with a particular focus on image recognition systems that enable unprecedented precision in player performance analysis, tactical strategy, and fan engagement. Against the backdrop of escalating financial pressures, from Name, Image, and Likeness agreements in collegiate sports to soaring professional contracts and media rights, the imperative for efficiency and effectiveness in leadership decision-making has never been more pronounced. However, despite AI’s potential to revolutionize sports management and analytics, significant technical and ethical challenges persist, including concerns about model accuracy across varied sports contexts, data biases, and privacy issues related to biometric information. This paper synthesizes insights from technology management, human-computer interaction, and organizational behavior to explore how AI adoption reshapes organizational cultures, decision-making processes, and the social dynamics within sports ecosystems. Drawing upon examples from basketball and football, the analysis highlights both the transformative promise and the cautionary complexities of integrating AI technologies at scale. Ultimately, this inquiry argues that the sports community must navigate these technological frontiers judiciously, ensuring that organizational culture, change management dynamics, ethics, and leadership dynamics are at the core of how these AI technologies and tools are developed, deployed, and managed. |
| Keywords: | Artificial Intelligence, Sports Analytics, Image Recognition, Sports Management, Organizational Change, Leadership Decision-Making, Human-Computer Interaction, Technology Adoption, Technology Management |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:smo:raiswp:0530 |
| By: | David Winkelmann; Rouven Michels; Christian Deutscher |
| Abstract: | In the 2024/25 season, UEFA introduced the incomplete round-robin format in the Champions League and Europa League, replacing the traditional group stage with a single league phase table of all 36 teams. Now, the top eight qualify directly for the round of 16, while teams ranked 9th-24th enter a play-off round. Existing simulation-based analyses, such as those by Opta, provide guidance on points presumably needed for qualification but show discrepancies when compared to actual outcomes in the first season. We address this gap using a bivariate Dixon and Coles model to address lower draw frequencies, with team strengths proxied by Elo ratings. This framework allows us to simulate matches and derive qualification thresholds for direct and play-off advancement. Our results offer scientific guidance for clubs and managers, improving strategic decision-making under the new UEFA club competition formats. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.20075 |
| By: | El Fatmaoui, Ahmed (University of Wisconsin, La Crosse); Ransom, Tyler (University of Oklahoma) |
| Abstract: | This study investigates the extent to which U.S. universities strategically use athletic admissions to shape the socioeconomic status (SES) of their student bodies. Using a novel dataset linking NCAA roster data to neighborhood characteristics, we document substantial SES segregation across sports and universities. More selective institutions, particularly elite private universities, allocate up to 30% of enrollment to athletes who typically come from higher-SES backgrounds than their non-athlete peers. However, contrary to popular belief, we find that elite institutions enroll similarly wealthy athletes across all sports. Estimates of our structural model of sports bundle choice reveal that this SES homogeneity across sports limits universities' ability to systematically choose sports offerings to target higher-SES students. Counterfactual analyses demonstrate that athletic enrollment caps would create additional seats for non-athletes but require complementary policies to meaningfully impact socioeconomic mobility. |
| Keywords: | university admissions, income segregation, college athletics, higher education |
| JEL: | C35 I23 I24 L83 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18071 |
| By: | Mikhail Drugov; Dmitry Ryvkin |
| Abstract: | We characterize robust tournament design -- the prize scheme that maximizes the lowest effort in a rank-order tournament where the distribution of noise is unknown, except for an upper bound, $\bar{H}$, on its Shannon entropy. The robust tournament scheme awards positive prizes to all ranks except the last, with a distinct top prize. Asymptotically, the prizes follow the harmonic number sequence and induce an exponential distribution of noise with rate parameter $e^{-\bar{H}}$. The robust prize scheme is highly unequal, especially in small tournaments, but becomes more equitable as the number of participants grows, with the Gini coefficient approaching $1/2$. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.16348 |
| By: | Heikkilä, Enja; Danso, Andrew; Luck, Geoff |
| Abstract: | Video game sound and music have previously been found to influence player engagement and affective responses during gameplay. However, a systematic investigation into the full extent of these effects has not been conducted. This review and meta-analysis examined the influence of music and sound on player emotional (e.g., affective responses) engagement during video game play. 14 studies met the inclusion criteria, with six providing data for meta-analysis on affective valence. Results show that sound and music were able to elevate player engagement during gameplay by positively influencing engagement related domains such as enjoyment, flow, immersion and motivation. Sound and music had a significant positive effect on affective valence (g = 0.409, 95% CI [0.109, 0.709]; p = 0.007). Sensitivity analysis showed a consistent significant effect, with low heterogeneity (g = 0.287, 95% CI [0.113, 0.462]; p = 0.001; I² = 0%). Study quality was generally high, with 11 out of the 14 studies rated for a low risk of bias. There is promising evidence for video game sound and music to improve player engagement and affective responses during gameplay, yet further research as well as standardization of methodology is required to better understand the underlying mechanisms in this emerging area. |
| Date: | 2025–08–30 |
| URL: | https://d.repec.org/n?u=RePEc:osf:mediar:mxrgh_v1 |