## 4 Discussion  
A main objective of this study was to investigate the suitability of using general jump types to assess sport-specific VSJ performance. Correlations were found between VSJ height and all measured general jump heights (i.e., SJ, CMJ, and CMJA). This suggests that general jump types may be suitable for training and testing to improve and assess VSJ jump height. However, regression analyses revealed that only 52% to 76% of the variance in VSJ height could be explained in models using general jump height as the only predictor. The observation that VSJ height differed from the height of all other jump types raises doubts regarding if general jump heights alone are sufficient to assess VSJ performance. Predictions with a precision of 52% in the weakest model are not recommended, and the VSJ performance should not be decided prematurely on the basis of general jump height alone. Differences in jump height were also found between sexes during all four jump types. Jump performance differences between sexes were previously reported in volleyball players during SJ [19], CMJ [19], and VSJ [6]. The reasons may include biological and power differences [20; 21], the ability to benefit from stretch-shortening-cycles [19; 22], and technical-coordinative variations [6]. These sex differences support sex-specific assessment of jump performances. Moreover, ANOVA results revealed an interaction (sex by jump type) for jump height, indicating that differences in height between jump types vary for females and males. Therefore, sex-specific analyses of jump performance are highly recommended, especially for predictions of VSJ height based on general jump type performances. Simple models with only one predictor (i.e., SJ, CMJ, or CMJA height) achieved \(R^{2}\) values between 0.52 and 0.76. Considering that these results are an equivalent of the explained variance in the criterion variable (i.e., VSJ height), it seems reasonable not to draw conclusions on sport-specific VSJ performance during the testing of general jump types. This should be considered especially when testing CMJA in males, where the least favorable result was achieved. General jump testing has several benefits (e.g., standardization, comparability, reliability) and is frequently used for performance testing in various sports [10]. The findings of the current study allowed improved association of general jump performance with VSJ favoring improved prediction. Improved regression models were derived from SJ performance in both sexes and CMJA performance in males. These models improved considerably the predictions of VSJ height from \(R^{2}\) = 0.76 to \(R^{2}\) = 0.92 in SJ for females, from \(R^{2}\) = 0.61 to \(R^{2}\) = 71% in SJ for males, and from \(R^{2}\) = 0.52 to \(R^{2}\) = 0.78 in CMJA for males. This suggests improvements for explaining the variance in the model by 26%, 10%, and 26%, respectively, and none of the improved models required more than two variables added to the respective general jump height. For practical application of the current findings, it is important to note the strength of all three improved models requiring only kinetic variables as additional predictors. No kinematic data were required except for the jump height of the respective general jump type. Since the jump height of all mentioned general jump types could be calculated via ground reaction forces, the measurement of kinetic data is sufficient for the application of the predication equations presented in this study and, thus, an advanced assessment of jump performance. A limitation of this study is that only three of six regression models could be improved. The other three analyses achieved statistical power ranging between \(1-\beta=0.22\) and \(1-\beta=0.53\). Considering the achieved power for correlation analyses (i.e., \(1-\beta=0.89\)) and the correlation effects of the added kinematic and kinetic variables, the power in failed model attempts was not caused by sample size.