 Detecting individual preferences and erroneous verdicts in mixed martial arts judging using Bayesian hierarchical modelsBenjamin Holmes, Ian G. McHale and Kamila Żychaluk European Journal of Operational Research, 2024, vol. 312, issue 2, 733-745 Abstract: In this paper, we use Bayesian hierarchical models to investigate the decision-making of judges of mixed martial arts (MMA) contests. Whilst there has been research into the judging of various sports in the past, none have explicitly modelled the judges’ behaviours at an individual level. We progress the literature by demonstrating that judges have personal preferences towards the different actions that they must assess during a fight. The preferences themselves may be the deciding factor in a bout, as demonstrated using a historical case study. We apply the concept of variable significance to the predictions of scores, to assess whether a judge’s verdict was within reason. Finally, we develop a model that predicts a bout’s fair outcome, which could be used in various ways in MMA. Keywords: OR in sports; Biases; Mixed martial arts; Bayesian statistics; Hierarchical model (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:312:y:2024:i:2:p:733-745 DOI: 10.1016/j.ejor.2023.07.004 Access Statistics for this article European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati More articles in European Journal of Operational Research from Elsevier |
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