Meta Insights: Analyzing Hero Performance in Mobile Legends with K-Nearest Neighbors

Abstract

This research presents a thorough statistical analysis of hero performance in the latest Mobile Legends meta, employing the K-Nearest Neighbor (KNN) algorithm. Utilizing diverse data sources, the study explores factors influencing hero success, leveraging KNN's ability to identify intricate patterns in complex datasets. Through meticulous data collection, preprocessing, and application of the KNN algorithm, the research classifies and predicts hero performance based on similarities with neighboring heroes. Critical determinants such as win rates, popularity, and hero ban rates emerge, providing profound insights into gameplay strategies. The study emphasizes the importance of understanding meta dynamics, hero attributes, and player expertise for informed decision-making in hero selection within the dynamic landscape of Mobile Legends.