## 3 Results  
Jump height from 84 valid trials performed by the participants using the five devices and different methods are shown in Figure 3. High dispersion of jump height was observed due to participant-specific variations. Values range from 250 mm to 650 mm, with the mean and the standard deviation of 381 \(\pm\) 76 mm, when considering the measurements from the QMS markers position. A direct comparison between jump height obtained through QMS markers position, FP double integration, and ABJ displacement is presented in Figure 3a. Many authors consider the first two as the gold standard techniques, and the third can provide an easy, low cost, and direct measurement of jump height. Jump height was also determined from flight-time (Figure 3b). The values obtained from QMS flight-time compared closely to the values of the QMS marker position. Flight-time determined from the maximum and minimum vertical velocity or from the contactless time with the EJ mat always led to an underestimation of jump height. For FP and MP, the vertical trajectory of the centre of mass was determined by double integration of the body's vertical acceleration, and jump height was obtained by taking the position at the highest point of this trajectory. The results from the FP and MP were compared with the QMS marker's position, as shown in Figure 3c. It can be observed that, except for a few cases, there is a good agreement between the results from the FP and the QMS; the same is not seen for the results from MP. According to the results in Table 1, ABJ presents the highest accuracy and precision with 1 mm and \(\pm\)15 mm, respectively. This is closely followed by FP using the double integration method and QMS using the flight-time method. However, one should mention that the results from FP could be better if we remove the outlier of trial 23 shown in Figure 3a,c, which would improve the accuracy to 1.5 mm and the precision to \(\pm\)13.9 mm. The flight-time method for all devices except QMS resulted in an underestimation of jump height. The difference was largest for EJ, followed by MP and FP devices. Figure 3: Comparison of jump height for 84 trials obtained by: (**a**) the QMS markers position, the FP double integration method, and ABJ displacement; (**b**) the QMS markers position, FP, EJ, and MP by using the flight-time method; (**c**) the QMS markers position and the FP and MP by double integration. To verify the degree of agreement between the jump height reference values (\(QMS_{Ref. }\)), obtained from QMS markers position, and the results from different devices and methods, the Bland-Altman plots are presented in Figure 4. For this analysis, the outlier of trial 23 was excluded from FP: double integration results. A positive bias is identified for the ABJ: displacement, QMS: flight-time and FP: double integration, and a negative bias for the other cases. High dispersion of the differences around the mean value is also observed. The linear regression line is also shown to investigate the presence of proportional bias. Except for the QMS: flight-time, we observed a significant slope. The Pearson correlation coefficient (\(\rho\)) and the p-value of the mean variable are also shown. The correlation coefficient revealed a negligible correlation for QMS: flight-time, a moderate correlation for MP: double integration, and a weak correlation for the other cases. The \(p\)-value lower than 0.05 was identified for the ABJ: displacement and MP: double integration, meaning the correlation coefficient was statistically significant and, therefore, it is assumed there is proportional bias. The ABJ: displacement presented a negative proportional bias, which would tend to underestimate the jump height for higher jumps. On the other hand, the MP