1 free read left. Create a free account for unlimited reading + AI research.
Create free accountWhitepaper
DiGRA
Ludic Cultivation builds trust through fair, learnable difficulty. Aspirational Deferment reads present frustration as investment in future competence, and Communal Mythopoesis amplifies the experience through shared stories.
This paper introduces the Ordeal Pleasure Framework (OPF), a model explaining why repeated failure in Souls-like games such as Dark Souls, Elden Ring, and Hollow Knight can become satisfying rather than merely frustrating. The framework rests on three interacting mechanisms: Ludic Cultivation, in which mastery through fair and learnable difficulty establishes a foundation of trust; Aspirational Deferment, in which players read present frustration as investment in future competence, a reading that depends on that trust; and Communal Mythopoesis, a social amplifier through which shared ordeal stories and interpretation intensify the experience without causing it. The author positions OPF against flow theory, Self-Determination Theory, learning theory, and fan studies.
The evidence base is deliberately modest. The paper's central claims are framed as hypotheses requiring causal and empirical testing, and the quantitative support is limited to a 95-participant survey of Dark Souls III players (Petralito et al., 2017), a study of a 2,363-comment Elden Ring Reddit thread (Czauderna et al., 2024), and Elden Ring's shipment of over 30 million units. Much of the comparative analysis is design-based, drawing on close readings of titles rather than systematic data collection.
The comparative cases are used diagnostically. Hollow Knight appears as a boundary case, showing strong cultivation and deferment without difficulty-coupled communal mythmaking, while Lords of the Fallen and The Surge serve as probes where weakened trust or thinner mythopoetic material may disrupt ordeal pleasure. Coarse Metacritic reception scores are used only to generate hypotheses, not to establish outcomes. The paper's most practical contribution is its claim that the framework can help identify which mechanism is failing in a given difficult game, whether untrusted difficulty, unclear temporal growth, or insufficient material for shared meaning, and it proposes two falsifiable hypotheses to guide future testing.
DiGRA · 2026
DiGRA · 2026