Background: Repeated vertical jump tests are widely used to assess neuromuscular function and lower limb performance. However, inconsistent formulas for average power output produce large discrepancies, limiting comparability across studies and limiting practical applications. This study aimed to compare three different models for the calculation of average power output, Bosco, Miron Georgescu (MG), and Modified Miron Georgescu-15s (MGM-15), applied to identical jump test data, in order to evaluate their computational behavior and practical relevance in athlete performance profiling. Methods: A single-group quasi-experimental study was conducted with 25 physically active male university students (mean age: 21.4 ± 2.7 years), who performed a 15 s repeated vertical jump test on the OptoJump Next system. Raw parameters including flight time, contact time, and jump height were recorded and exported. Average power output (W/kg) was subsequently calculated using three distinct computational models, each applied to the same dataset of flight and contact times. A repeated-measures ANOVA was used to compare outputs across models, with Bonferroni-adjusted pairwise comparisons for post hoc analysis (α = 0.05). Results: Significant differences were observed (p < 0.001). The Bosco model produced the highest values of average power (40.13 ± 8.56 W/kg), followed by MG (21.07 ± 5.92 W/kg), while MGM-15 yielded the lowest and most consistent outputs (4.08 ± 0.61 W/kg). Effect sizes were very large (η²_p = 0.952), confirming that calculation models strongly influenced the outcomes. Conclusions: The findings demonstrate that average power output differed markedly across formulas, despite identical performance data. Bosco and MG models tended to overestimate values due to simplified assumptions, whereas the MGM-15 method produced lower and more consistent outputs that may better capture repeated jump demands. The standardization of computational models is fundamental to ensure comparability and to improve athlete performance profiling in research and practice.

The study aims to highlight the impact of practicing recreational figure skating by evaluating the relationship between the perceptions of motor, mental and social benefits of practicing figure skating and the frequency and duration allocated for this recreational activity. The study included 143 students of physical education and sport specialization. The questionnaire was designed to evaluate the students’ perception about the benefits of practicing recreational figure skating; it included 30 items divided in three parts: motor, mental and social benefits. Each of them contained 10 items to be assessed by students using the Likert scale, with 2 items related to the duration and frequency of practicing figure skating during recreational time. The results were processed using SPPS 24. The results were statistically significant at p < 0.05. The Cronbach’s Alpha coefficient of the questionnaire was α = 0.965, suggesting that the items had high internal consistency. Using the Likert scale, we found the following: concerning the high score 5 points—the motor capacity 62.9%, the mental capacity 49.7%, the social capacity 49.7%; and for a low score of 1 point—mental and social capacity 1.4%, motor capacity 0.7%. The effect size was medium for almost all items. No statistically significant correlations were found between the result of the questionnaire and the frequency and duration of practicing figure skating during free time. Figure skating is considered by students to be one of the activities through which a series of parameters of physical development and level of physical fitness can be improved through the expansion of motor skills. Also, the practice of figure skating contributes to the formation of proactive behaviors by improving the mental and social abilities of practitioners.

Background: Average power in repeated vertical jump tests is commonly estimated rather than directly measured, and the equation chosen may substantially affect interpretation. This quasi-experimental within-subject study compared Bosco, MG, and MGM-15 estimates from identical 15 s repeated-jump kinematic data and, as a supplementary exploratory component, quantified their differences relative to power from a separate 20 s Concept2 BikeErg trial. Methods: Fifty-one physically active male participants performed a 15 s repeated vertical jump test with arm swing on OptoJump. Raw kinematic data were converted to average power using the Bosco, MG, and MGM-15 equations. Average power was also recorded during a 20 s maximal BikeErg trial. Repeated-measures ANOVA, Pearson correlations, linear regression, and Bland–Altman analyses quantified between-method and cross-task differences. Results: Mean power differed markedly across models: 40.79 ± 7.65 W/kg (Bosco), 21.60 ± 5.13 W/kg (MG), and 4.20 ± 0.54 W/kg (MGM-15), versus 7.83 ± 0.94 W/kg for BikeErg (F(1.03, 51.29) = 1082.05, p < 0.001, η²p = 0.956). MGM-15 correlated strongly with Bosco (r = 0.977) but produced substantially lower estimates. Bland–Altman mean differences relative to BikeErg were +32.96 W/kg (95% LoA: 18.69 to 47.22) for Bosco, +13.77 W/kg (4.34 to 23.20) for MG, and −3.63 W/kg (−5.27 to −2.00) for MGM-15; proportional bias was confirmed for all three models (all p < 0.001). Conclusions: Average power values from this test are strongly model dependent. Bosco, MG, and MGM-15 values are not interchangeable, even if they come from the same kinematic dataset. MGM-15 yielded estimates nearer to BikeErg power than either Bosco or MG. However, since cycling and jumping are biomechanically different activities performed over different time spans, this indicates only exploratory numerical convergence, not criterion validity.