## 4 Discussion
Thus, the RSI RUN may be used to predict the 100 m sprint time in athletes with different anthropometric characteristics. In the present study, indeed, athletes with similar RSI RUN values were characterized by similar best seasonal performances in 100 m sprint. Therefore, since previous studies reported that acceleration up to 60 m explains only 64% of the time in the 100 m (32), a more predictive index of performance such as the RSI RUN may be useful. On the other hand, it is well known that many athletes show great performances in the 60 m sprint but are not competitive in the 100 m.  
Compared with the RSI RUN and the NRSI RUN, the RSI VDJ calculated for the athletes participating in this study shows very large negative correlations with all sprint times (r = \(-\)0.77 with all sprint times) and SB 100 m (r = \(-\)0.72) and a positive large correlation with max speed (r = 0.76). Although these data are consistent with other studies [27, 31, 34], the correlations are slightly superior to those in other studies involving track and field sprinters (r = \(-\)0.49) [14]. A recent review [15] also reported moderate correlations between the RSI calculated in the drop jump and both sprint acceleration and maximum running speed (r = 0.42 and 0.39, respectively). This study confirmed previous research [14, 35] and suggests that data obtained by vertical jumps are mainly correlated with the first acceleration phase, while leg stiffness is more important for the achievement of the maximum velocity. In this study, however, the RSI RUN and the NRSI RUN are highly correlated with sprint performances over different distances. This is likely determined by the fact that the athletes participating in this study run the 60 m sprint starting from a standing position and not from the blocks. This starting position may favor the use of reactive strength rather than explosive strength. The other indices analyzed in this study (RSI HDJ, NRSI HDJ, RSI SLR and NRSI SLR) did not show significant correlations with sprint performance. Thus, the present investigation confirms that the horizontal-based RSI represents a more specific parameter for running speed compared to the vertical-based RSI. This is consistent with the findings of [PERSON] and [PERSON] [31] and [PERSON] et al. [14], who supported the need for large horizontal, rather than vertical, forces to achieve high running speeds [28, 36]. However, observing the correlations between the different indices, the very large correlation between RSI RUN and RSI VDJ (r = 0.85) indicates that these two parameters may represent the strongest predictors of performance for the athletes involved in the present investigation. The second aim of this study was to correlate the RSI with the muscle architecture of lower body muscles. According to [PERSON] et al. [24], no significant correlations were detected between muscle thickness of the VL and sprint performances. The present study also shows that no relationships exist between muscle thickness and any kind of RSI. Muscle thickness, indeed, represents a key factor for maximal strength [37] but is not a good predictor of dynamic performances such as sprinting or jumping. Conversely, the echo intensity of the VL shows a very large correlation with sprint performance (from 30 to 100 m), the RSI RUN and the NRSI RUN. Curiously, no relationships between echo intensity and vertical-based RSI indices were detected. Echo intensity is considered a strong predictor of muscle quality that is affected by the individual body fat, the presence of fibrous tissue, age and training status [38]. The study by [PERSON] et al. [38] suggests that sprint performance is particularly sensitive to this parameter of muscle quality. The correlation between this parameter and the RSI RUN indicates that contact time and stride length may be both influenced by echo intensity.