What can Possibly Go Wrong? A Generic Classification System for Human Error in Sports

To win in sports, athletes must perform complex motor tasks while avoiding errors. Such errors relate to deviations from successful performance or decision-making that negatively impact performance. Categorizing errors can help practitioners understand the sources of those errors and implement targeted training protocols to address them. While error classification models can be found in many human factors-related domains, sports lack a similar framework for error classification. This article introduces the Generic Error Modelling System for Sport (GEMS-S), an adaptation of Reason's Generic Error Modelling System (GEMS), used in human factors research. GEMS-S distinguishes between six types of errors: planning mistakes, spontaneous mistakes, slips, lapses, implementation failures, and reaction failures. Some of these categories are drawn from the original GEMS, some are added to adapt the framework to the types of errors that occur in sports. We present a systematic approach to classifying errors according to the six categories and demonstrate how GEMS-S can be applied using simple example scenarios from golf, motor racing, and football – sports representing a broad variety of temporal, motor, and perceptual-cognitive demands. GEMS-S enables researchers and practitioners to identify errors, develop error-specific interventions, and establish a common vocabulary across different sports.