Modelling mood states in athletic performance.

Abstract

Because moods are transitory emotional states that can be influenced by a range of personality and environmental factors, the notion that elite athletes will always tend to produce a so-called iceberg profile of mood, and that less successful performers will not, is open to question. Evidence for such a claim is based principally upon descriptive studies. The present experiment used the POMS inventory as a predictor of cross-country running performance among a group of experienced male athletes. Race times from two competitive events were plotted against each of six mood factors. Using data from race 1, a multiple-regression model--incorporating the interdependence of tension, anger and depression--was able to predict rank order of finishing positions for race 2 with acceptable accuracy (rs = 0.74, P less than 0.01). The present approach differs from the traditional model of mood research in sport in that it provides a prescriptive, rather than a descriptive, focus. Although the model that has been developed appears promising, it is likely that in sports where demands on athletes are very different from those made upon cross-country runners, an alternative model may be required.