Our research is closely related to ontological studies in mathematics. It provides crucial insights into the nature of decisions and strategies characterized by Markov moments. In a stopping game, a holistic decision-maker would evaluate comprehensive information by assessing the probabilities of various outcomes and their associated payoffs. This involves understanding the current state, historical data, and potential future scenarios. Such a decision-maker must also consider strategic interactions by anticipating and accounting for the strategies of other players. They must be flexible in adapting their strategy as the game evolves and able to integrate uncertainty by incorporating risk preferences and tolerances. They would perform scenario analysis to evaluate the impact of different stopping times under varying conditions. The goal of this modeling and its implementation in psychological practice is to introduce a novel method for assessing the state of players, leveraging deviations from rational strategies as diagnostic indicators of their psychological and decision-making profiles. The details of other models will be subject to contributed papers. The article presents the theoretical basis for combining various factors when modeling decision-making processes. The original title is "Rationality, Deviation, and Diagnosis: A Holistic Approach to Stopping Games" and will be used when it is possible to describe and interpret the results of the experiments we write about in the last section of the paper.