Longitudinal Analysis of Tactical Strategy in the Men's Division of the Ultimate Fighting Championship

• Published in: Frontiers in artificial intelligence Vol. 2; p. 29
• Main Authors: James, Lachlan P, Sweeting, Alice J, Kelly, Vincent G, Robertson, Samuel
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 17.12.2019
• Subjects: Artificial Intelligence; combat sport; data mining; mixed martial arts; notational analysis; sports analytics; notational analysis; mixed martial arts; combat sport; sports analytics; data mining
• ISSN: 2624-8212; 2624-8212
• DOI: 10.3389/frai.2019.00029

This study explored longitudinal changes in contemporary mixed martial arts (MMA) combat within the Ultimate Fighting Championship (UFC). A secondary aim was to investigate how bout duration influences the contribution of performance indicators on outcome. Data were acquired via the official analytics provider to the UFC (FightMetric). Male fights with a winner from between 2000 and 2015 ( = 2,831) were examined, with 13 common performance indicators attained during each round for each participant along with duration (min) and year of fight. Non-metric dimensional scaling (nMDS) was used to examine bout characteristics by year. The Repeated Incremental Pruning to Produce Error Reduction (RIPPER) algorithm was run to determine a set of rules to explain bout outcome. The nMDS displayed that winning bout performance indicator attributes were dissimilar across the years. Eight rules were generated from the RIPPER, with fight duration featuring in three of eight rules. Distinct shifts occurred (albeit without linear trend) in performance indicator characteristics during the observed period. This was characterized by a more diverse combat style in the years following 2008. However, offensive grappling has remained a key factor regardless of year, and is influenced by bout duration.