VisMLB: An Hybrid Data Visualization Model for Major League Baseball Matches Using Tableau

This manuscript provides an in-depth analysis of Major League Baseball (MLB) team performance from 2005 to 2023 using data visualization in Tableau and proposed an hybrid data visualization model (VisMLB) for Major League Baseball matches. The objective is to identify key metrics, such as batting, fielding, and pitching, that influence team success, including championship wins. The authors analyze the total number of championships won by each team, compare top-performing teams based on a variety of performance metrics, and explore the relationship between On-Base Percentage (OBP) and Slugging Percentage (SLG) for home and visitor teams in relation to home victories. Using Tableau, feature importance is visualized, and predictive models are evaluated for accuracy, precision, and recall. The findings offer a comprehensive overview of MLB performance trends over nearly two decades.