Navigating Between Human and Machine-Based Evaluation: Judgment and Objectivity in Economic Games Exemplified in the Analysis of MMA Fights

UFC (Ultimate Fighting Championship) video games aim to provide a realistic virtual experience of MMA (Mixed Martial Arts) fights. However, despite the seeming simplicity of the point-based scoring system used during these fights, judges’ holistic verdicts of identifying the winner often fail to accurately reflect the performances because, we find, they do not rely on the point-awarding system used during the fights. We investigate the extent to which judges employ holistic approaches in their scoring decisions, even though they are consistent in applying them. To overcome the shortcomings of the holistic approach, we propose a merit-based set of rules (based on the Bayesian statistical approach that is driven by the points accrued in each round of the fight) for identifying the winners of matches and tournaments. Merit-based sets of rules are commonplace in economic games, in which strategic decision-making and performance evaluation are common, and such rules infer that quantified measures do objectify the assessment of player/fighter performance in a far more satisfactory (and non-controversial) manner. We thereby emphasize the importance of significant strikes being a key component of scoring. Our analysis of data from 3039 UFC decision fights demonstrates that the potential of objective scoring methods will make tournaments more attractive for not only gamers but also spectators. Likewise, such objective evaluation methods are useful in economic games.