## 4 Discussion  
This study introduces a custom Excel/VBA spreadsheet designed specifically for the analysis of dual platform countermovement bipodal jumps, offering a cost-effective and accessible alternative to high-end software solutions. The manual identification of key events during the jump, which can be completed in less than five minutes, allows for the extraction of a wide range of biomechanical variables. These variables are summarized in a printable format, integrating data from both force platforms while also allowing for the individual analysis of each leg's function during the jump. The comparison between the ad hoc Excel/VBA spreadsheet and the prestigious software (MARS 4.0), recognized  
Figure 6: Bland–Altman plot of the height computed from flight time. Figure 7: Bland–Altman plot of the propulsive impulse. as a benchmark in biomechanics laboratories, revealed small differences. The difference in jump height estimated using flight time was less than one centimeter, and less than two centimeters when estimated using take-off velocity, corresponding to relative errors of approximately 2% and 4%, respectively. The propulsive impulse showed a difference of approximately 5 N \(\cdot\) s, with a relative error of about 2.5%. These findings suggested that the custom spreadsheet provided accurate results, making it a viable option for laboratories and researchers with limited resources. When assessing the magnitude of these errors, it is essential to consider the typical between-group and within-subject differences reported in the literature. In other words, coaches and scientists must avoid measurement errors larger than the differences they intend to measure [31,32]. For example, a researcher intending to use the ad hoc Excel/VBA spreadsheet for a specific aim should carefully consider the magnitude of error relative to the differences found in similar studies. Regarding jump height, a difference of approximately 1.8 cm was observed when using take-off velocity for estimation and of 0.7 cm when using flight time. Some scientific literature results are discussed below, in which the use of the ad hoc Excel/VBA spreadsheet would be recommended or not. In a study by [PERSON] and [PERSON] [11] comparing jump performance between throwers and sprinters, the sprinters exhibited a jump height approximately 10 cm greater (35 cm vs. 45 cm). Similarly, in a study by [PERSON] et al. [13], a four-week training program incorporating resistance and pyometric exercises, with a frequency of two days per week, demonstrated improvements in jump height ranging from 3 to 5 cm after three weeks. Both examples show differences larger than the spreadsheet errors of 1.8 cm when using take-off speed to estimate jump height and 0.7 cm when using flight time, indicating that it is sensitive enough to accurately detect these variations. In addition, a shoe with higher bending stiffness improved jump height by an average of 1.7 cm [14]. While this improvement exceeds the 0.7 cm error associated with the Excel/VBA spreadsheet using flight time, it is very close to the 1.8 cm error observed when using take-off speed, suggesting that the latter method may not be suitable for such studies. Moreover, [PERSON] [33] assessed the effects of pyometric and concentric exercise programs lasting between 6 and 12 weeks, finding jump height improvements of approximately 5% to 10% (equating to 2-6 cm). These percentage increases are substantially higher than the percentage error for jump height obtained with the Excel/VBA spreadsheet using flight time, confirming its adequacy for such assessments. However, when take-off speed is used, the percentage error (\(\approx\)4%) is lower than that reported in most studies included in the meta-analysis but is comparable to those with the smallest improvements. In these latter cases, the use of take-off speed for estimation is not recommended. In a study examining within-subjects jump height changes across sessions, systematic biases of 1.3 cm were found [12].