## 4 Discussion  
This study aimed to explore the following: (1) to test the correlation of a new variable denominated integral reactive strength index (IRSI) with the RSI, and (2) to compare the flight time, ground contact time, jump height, RSI, reactive capacity, and IRSI between Olympic athletes in 100 m and 400 m events. In the experimental approach, no differences in reactive strength variables were shown between the groups. Nevertheless, there are some differences in the magnitude of the effect size that need to be discussed. We also found a trend of RC decrease, when HF increases, as expected [16]. Although we found an inversely proportional trend of RC behavior with respect to the RSI in this study, the correlation between these variables was of small magnitude. This low correlation, and their inversely proportional trend, helped to explain the influence of RC on HF. To our knowledge, this is the first study to compare reactive strength variables from different heights in 100 m and 400 m dash sprimters. Our data showed that it is possible to suggest the individualization of the most recommended drop heights to develop reactive strength in these sprimters, that is, those needed to maintain short ground contact times during sprinting [21]. Our results indicate that there are no differences between the groups (100 m vs. 400 m), so these sprimters could perform the same training strategies concerning reactive strength variables. This is explainable, as the current demands of a 400 m dash sprimter are not very different from those of a 100 m dash sprimter (Appendix A). By analyzing separately the metrics that make up the reactive strength calculation (GCT and FT), we can observe that regarding FT, we found no significant differences between the groups. Even so, we observed that between DJ30-50, there is a trend that 100 m group sprimters show trivially better FT (ES \(\leq\) 0.50) than 400 m sprimters (see Table 2). These effects tend to be slightly large between DJ50-60, where moderate effects are already observed (ES = 0.72). When examining the GCT, we also observed that between DJ30 and DJ50, the 100 m group tends to show an increment in this value relative to the 400 m group (ES DJ30 = 0.12; DJ40 = 0.33; DJ50 = 0.46, and DJ60 = 0.68). This may explain why the 100 m group improved their RSI during all HFs, while the 400 m group decreased their RSI in the DJ60. There are criticisms of the reactive strength based on errors of measurement [2] that occurred during FT conducting to the overestimation of JH, which suggests a possible threat to the use of this marker [2]. However, due to the inherent high costs of the pyometric assessment, the reactive strength could be considered the most accessible pyometric variable for the coach monitoring pyometric performance [16]. Therefore, the 2-3 cm margin of error in JH does not limit it from being a useful control training tool, provided that the measurement methods and instruments are correctly standardized. In the same vein, although one study [10] recommends that it is impractical when working with large  
Figure 2: The RSI (**left**) and IRSI (**right**) for each drop jump obtained in 100 m and 400 m sprimters. The \(y\)-axis represents either the mean RSI or IRSI, and the \(x\)-axis represents the different drop jumps (i.e., fall heights) for both groups. groups to individualize the HF and proposes a moderate HF (30 cm), this strategy may not be useful for high-level 100 m and 400 m sprimters. Accordingly, the aim of this training task variable is to show the maximum RSI associated with the highest HJ, to seek greater specificity [8] and magnitude of the adaptations [5]. The principle of specificity indicates that the way the athlete develops the pylemetric activity will be decisive to the results of the athlete's achievement [22]. Furthermore, higher HF increases neuromuscular pre-activation levels and the speed that can be generated in the eccentric phase, and thus increases the contractile potentiation mechanisms in muscles and tendons [9].