## 1 Introduction  
Understanding precise human mobility is essential for the study of economic sciences, as it provides real-time data and shows small- and large-scale movement trends. This makes it helpful in examining the movements of people in relation to sporting events to gain knowledge about travel patterns and business effects. The combination of cell-based GPS data and business-level economic data allows for an understanding of meta-scale business trends and human movement based on whether it is a gameday or not. These insights are important in fields such as urban planning, transportation, and emergency preparedness [1, 2, 3]. Sports events uplift the local economy of host cities through enhanced city branching, economic benefits, non-infrastructure benefits, and revenue from event ticket sales and tourism [4]. In the past, stadiums were financed by private entities, but nowadays they are funded publicly, which means that the costs of constructing a new stadium fall on citizens through taxes [5]. Over the past two decades, virtually every one of the 100 professional stadiums that have been inaugurated has been provided with financial support, either directly or indirectly, by government entities at the local, state, or federal levels [6]. The Saint Louis Cardinals are a professional baseball team that was founded in 1882 and have won 11 World Series championships, making them one of the most successful franchises in Major League Baseball history. Since 2006, the Saint Louis region has benefited from an estimated economic impact of over USD 4.5 billion in output as a result of the Cardinals' 16 regular seasons, with around 40% of annual fan attendance being made up of out-of-town visitors [7]. As part of their agreement with the city, the owners of the Cardinals and their private equity partners invested over USD 270 million, which included at least USD 65 million in public subsidies, into the Ballpark Village, a sports-themed entertainment district [8; 9]. Given the significant investment involved, it is crucial to understand the potential impact that Cardinals games may have on the mobility and spending patterns of people in the area. The use of geospatial technologies and location-based data has been instrumental in studying various aspects of human behavior [10; 11]. However, the application of modern geospatial technology in investigating the economic effects of sports events on regional economies has been limited. One possible reason could be the insufficiency of relevant data or the lack of available infrastructure capable of handling big data. Nevertheless, recent advances in cloud computing infrastructure and the availability of Safe Graph data have made it possible to explore the tangible economic impact of sports events. Therefore, this study investigates the hypothesis that baseball games contribute to the local economy. This study seeks to bridge the gap between mobility patterns and economic impact by posing the following clear research questions: How do Major League Baseball (MLB) games affect local economic activity, and how can mobility data enhance our understanding of this impact? Additionally, how can we exploit mobility data to predict local spending, aiding in future planning, such as optimizing revenue generation, determining preferred game times or days, and selecting teams that maximize economic benefits? While it is well established that large events disrupt mobility patterns, our analysis goes beyond descriptive insights to explore how these changes translate into economic benefits. By integrating mobility data into machine learning models, we provide a more holistic view of the spillover effects of baseball games. This integration allows us to capture not only the spatial dynamics of visitor movements, but also their financial impact on local businesses. This analysis focuses on spatial patterns and the predictive power of features beyond business location, offering insights into how mobility data can inform revenue predictions.