## 4 Discussion
The higher variability can be explained by independent differences in the _GRF_ and \(v\) variables between sets (especially at low inertias) that determine the x-intercept (V0 variable) and consequently the inclination of the regression line (_Slope_ variable). It is worth noting that the peak _GRF_ and \(v\) variables fitted the linear regression line poorly (mean rmcorr R\({}^{2}\) was 0.28 (0.41; 0.16) for criterion and 0.52 (0.40; 0.63) for direct measure), so we decided to exclude the peak variables from further _F-v-P_ analysis due to lack of credibility. Based on this finding, we believe that peak parameters should not be used in further calculation of _F-v-P_ output variables in FW squats, regardless of thesensory system used. Interestingly, these results are in contrast to the results of [PERSON] and coauthors [49], who suggest using peak over mean variables due to both a stronger linearity of the _F-v_ relationship and a higher reliability of the _F-v-P_ variables in squat jumps with additional weights. Moreover, FW inertial resistance training has often been used with the aim of achieving an eccentric overload [33; 50]. Interestingly, we found a very high goodness of fit of the mean eccentric _GRF_ and \(v\). The eccentric portion of the closed-kinetic chain _F-v_ relationship has not been studied as extensively as the concentric part. Controversial results have been previously reported regarding the eccentric part of the muscles' _F-v_ relationship in the open chain exercises [51]. Our study therefore raises some new questions regarding the evaluation of lower-extremity eccentric closed-chain characteristics across the spectrum of different inertias that are beyond the scope of our study. While the variables of the eccentric phase of the FW squat have shown moderate external validity in assessing lower extremity performance (change of direction, squat jump, countermovement jump, and isokinetic strength) [9] and therefore provide valuable information about athletes' lower extremity characteristics, they should be considered in future research. The concurrent validity results from our study are in line with the previous research on comparing _GRF_, \(v\), \(P\), or _F-v-P_ outcome variables between force plates and linear velocity encoder during jumps [52]. It was found that despite high inter-methods correlations, linear velocity encoder overestimated the mechanical output as compared to the force plates in counter-movement jumps [53] and squat jumps with additional weights [54], especially under light loading conditions [53; 54; 55]. Consequently, the _F-v_ slope obtained by the linear encoder differed with respect to the other methods due to a larger V0 (for 72.3%), providing a more velocity-oriented _F-v_ profile [53]. Custom-made rotary encoder sensor used in our study generally works similarly to a linear encoder; however, it measures the rotational position, rather than in a straight line [38]. This could be one of the important system disadvantages because the successive manipulation of the raw data magnifies the measurement error. Consequently, inter-measure differences found in our study could be a consequence of several factors involving data collection, the calculation of the variables, and also the technique of the squat execution described in further detail in the next sections. The overestimation of the \(v\) (mean and peak) of a direct measure was more prominent under light inertias. Regarding the calculation of the variables in the concentric phase of the squat, the \"active phase\" and the \"relaxed phase\" must be highlighted. It is clear that in order to prevent the push-off in FW squats, the athlete must accelerate rapidly from the bottom of the squat (active phase) and then start decelerating before full leg extension (relaxed phase). Both the linear encoder and rotary encoder sensor can detect the drop in velocity during the relaxed portion of the concentric phase.