Integrating the Izof and Iapz models to assess individual feeling states and performance during tennis matches

Abstract

For researchers and practitioners interested in optimal performance in sport, feeling states are one of the most important predictors of performance. In this study, the Individual Zones of Optimal Functioning (IZOF; Hanin, 2000) and Individual Affect Performance Zone (IAPZ; Kamata et al., 2002; Tenenbaum et al., 2008) idiographic models were combined by developing probabilistic estimates for discrete feelings (e.g., angry, relaxed, strong, focused, etc.). Ten male NCAA tennis players volunteered to participate in this study—providing 918 observations. Each participant developed individualized profiles with 12-13 feelings, identified four 'trigger-feelings' that each player felt were most important to his performance, and then monitored the intensity of each feeling in the profile during competitive intra-squad matches. Their discrete feelings were organized into four categories based on valence and functionality: positive-helpful, positive-harmful, negative-helpful, and negative-harmful. Ordinal logistic regressions were conducted to create probabilistic performance curves for poor, average, and good performances. Statistical analyses supported the validity of the combined IZOF-IAPZ method as well as the idiosyncratic nature of feeling-performance relationships: 76% of profiles were unique in either the size or the location of each performance zone. The four-category (valence-function) model predicted performance correctly 63.5% of the time—more than twice that of chance. The four trigger-feelings were even more accurate at 66.4%, and the top three trigger feelings were accurate 70.0% of the time. The results of this study provide alternative ways to apply the IZOF and IAPZ models, such as by establishing OLR-curves for discrete feelings, grouping feelings into function-valence categories, and developing simplified models that use only three or four feelings to predict performance.

Acknowledgments: The study was supported by Michigan State University's Dissertation Completion Fellowship.