Performance diagnostics in sports is employed to obtain the current status of an athlete, for longitudinal as well as cross comparisons and for adjusting the subsequent training phase. A diagnostic set-up consists of certain tests that yield specific quantitative parameters. In this paper, we show how to analyze large amount of test data and possibilities to reduce the complexity of a diagnostic set-up. For the data collected from about 200 German elite ski jumpers and Nordic combined athletes between 2004 and 2008, we performed a factor analysis in order to find latent factors that would reduce the number of parameters measured and interpreted so far. Our calculations resulted in three latent factors: 1. general jump ability and relative maximum strength, 2. general maximum strength and dynamic strength, and 3. force rate development. We propose to reduce the number of measured parameters to a) one of the variables that load high on the three factors and b) those that do not measure any factors at all. This way, we come up with ten instead of the initial 23 parameters, while a high proportion of variance can be explained. These findings need to be checked in actual testing settings for practical relevance.
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