Mixed Membership Martial Arts: Data-Driven Analysis of Winning Martial Arts Styles

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Authors

Sean R. Hackett
John D. Storey

Abstract

Abstract: A major analytics challenge in Mixed Martial Arts (MMA) is understanding the differences between fighters that are essential for both establishing matchups and facilitating fan understanding. Here, we model ~18,000 fighters as mixtures of 10 data-defined prototypical martial arts styles, each with characteristic ways of winning. By balancing fighter-level data with broader trends in MMA, fighter behavior can be predicted even for inexperienced fighters. Beyond providing an informative summary of a fighter's style, it is also the case that style is a major determinant of success in MMA. This is reflected by the fact that champions of the sport conform to a narrow subset of successful styles.