## 4 Discussion
athletes but question its utility with the population of professional athletes as its accuracy seems to decrease with higher values of JH [52]. Our results provide an important insight into testing with this type of equipment. We suggest that in order to maximize accuracy of the measurements and its utility for subsequent NMF monitoring, the practitioners need to implement more rigorous testing procedures as in S2. A 4% decrease in JH was a statistically significant decrease, and it is important in the context of testing CMJ as its approximate between-day coefficient of variation was described as 3.5% [28]. Therefore, if we select an execution of the test that does not maximize the probability of receiving as accurate results as possible, we potentially increase the risk of unreliable testing procedures. CMJ is used not only to track NMF [20] but also as a hint to identify potential talent in youth athletes [53] and ranking the players within the group [28]. The results of our investigation promote high-quality, standardized procedures as they often influence subsequent decision-making within sport institutions. The approximately 4% decrease in JH was statistically significant, but the approximately 30% decrease in standard deviation may be more relevant for strength and conditioning coaches. To track NMF, it is a common practice to introduce basic statistical analysis such as z-score, coefficient of variation or smallest worthwhile change [28]. In all of these statistical calculations, one of the variables is a standard deviation. Results presented in Tables 4 and 5 demonstrated a large decrease in standard deviation after introducing more rigorous testing procedures in S2 for all the players (Tables 4 and 5). Analyzing players' individual changes in standard deviation between S1 and S2, some results need special attention as such changes as demonstrated by athletes n1 (45 and 37.5%), n3 (58.2 and 54.8%) and n8 (47.1 and 38.6%) should persuade practitioners to implement execution of the CMJ test of S2. A large decrease in the standard deviation means that the results of the measurement are oriented much closer to the mean, and it directly influences the use of highlighted statistical tools as they become much more sensitive to changes in JH. If a strength and conditioning coach uses z-score to compare individual results of a given session to overall data collected during an extended period, such changes in standard deviation may alter the decision-making process within the team. Usually, an integrated approach of subjective and objective monitoring is implemented [8; 15], but in the case of using only CMJ measurements to assess NMF, the practitioners could decide incorrectly about a player's contribution during technical sessions. To put it into perspective, a result of JH that is lower than an athlete's mean by 3 cm for players n1, n3 or n8 could lead to a completely different intervention regarding these players. In relation to standard deviations from S1, a coach could potentially keep athletes within their normal training regimen, but with the results from S2, he could also potentially modify their participation in a technical session or even withdraw them from the session. In our opinion, this example appropriately illustrates how the decrease in standard deviation in S2 can be even more important than the decrease in JH. An argument that could be raised against the results of our study is that apart from execution of the jump, a number of other factors can influence their performance in the test. The players could simply be introduced to more physically demanding sessions or participate in a higher number of the games and had insufficient recovery. However, the role of the players between the seasons became unchanged, the starters in S1 were also the starters in S2, the bench players in S1 were also the bench players in S2.