Creating Probabilistic Idiographic Performance Profiles from Discrete Feelings: Combining the IZOF and IAPZ models

Abstract The purpose of the study was to determine if probabilistic profiling could be used to develop probabilistic individual zones of optimal functioning (pIZOF) profiles comprised from discrete feelings aggregated into valence-function categories (Hanin, 2000a). Ten male college tennis players developed individualized profiles, and then assessed their personal profile’s items during changeovers of intrasquad matches. Support for the viability of using ordinal logistic regression (OLR; a foundation of the IAPZ method) to develop idiographic discrete performance-feeling profiles (common to the IZOF framework) is provided. Evidence of the idiosyncratic nature of the profiles and for the effectiveness of the IZOF-IAPZ integration is provided through visual assessments of figures, qualitative comparisons of feeling-items selected by each player, and statistical analyses of differences in the size (variance) and location (means) of zones - which revealed that 62 to 76 percent of zones were individually unique. The results of this study augment the IZOF model by (1) establishing that OLR can be used to develop discrete probabilistic (pIZOF) profiles, and (2) providing a variety of qualitative and quantitative methods of assessing idiosyncrasy.