Purpose Resent research has suggested that loaded multi-joint movements could reveal a linear force-velocity (F-V) relationship. The aim of the present study was to evaluate the F-V relationship both across different types of vertical jumps and across different F and V variables. Methods Ten healthy subjects performed maximum various vertical jumps that were either loaded or unloaded by constant external forces of up to 30% of their body weight. Both the maximum and averaged F and V data were recorded. Results The observed F-V relationships proved to be strong (median correlation coefficients ranged .78-.93) and quasi-linear. Their F- and V-intercepts and the calculated maximum power (P) were highly reliable (.85

The findings add to the evidence that the linear F-V and, consequently, parabolic P-V models could be used to study the mechanical properties of muscular systems, as well as to design a relatively simple, reliable, and ecologically valid routine test of the muscle ability of force, power, and velocity production.

The purpose of this study was to evaluate the standard field tests of flexibility of the lower extremity through their (a) intratrial and test-retest reliability, (b) concurrent validity with respect to a high-precision 3D system for kinematic recording, and (c) factorial validity. Physically active men (n = 84) were tested over 2 separate sessions by means of standard simple devices (kinanthropometry, ruler, and protractor) on the following flexibility tests: leg raise in a supine position, hip abduction test, single-legged knee bend (SLKB), sideward leg splits (SdLS), sit and reach (SR), sideways leg splits, and lengthwise leg splits. Additionally, 17 participants were simultaneously tested by means of a laboratory 3D kinematic analysis system. Most of the tests demonstrated high intratrial and test-retest reliability and concurrent validity. The exceptions were SLKB and SR tests that revealed not only a somewhat lower reliability but also a lower concurrent validity. For estimation of factorial validity, we applied a principal component analysis of the intercorrelations among the evaluated flexibility tests that revealed a single extracted principal component. Strong mutual relationships among them also suggest that very few of them, if not a single one, should be applied within the standard batteries of physical performance tests. We particularly recommend using SdLS over the most frequently used SR not only because of its relatively high reliability and validity but also because of its postural properties. Finally, we conclude that most of the standard field tests of flexibility of the lower extremity based on using inexpensive field equipment could be both reliable and valid and, therefore, justified for use in routine testing.

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A range of force (F) and velocity (V) data obtained from functional movement tasks (e.g., running, jumping, throwing, lifting, cycling) performed under variety of external loads have typically revealed strong and approximately linear F-V relationships. The regression model parameters reveal the maximum F (F-intercept), V (V-intercept), and power (P) producing capacities of the tested muscles. The aim of the present study was to evaluate the level of agreement between the routinely used "multiple-load model" and a simple "two-load model" based on direct assessment of the F-V relationship from only 2 external loads applied. Twelve participants were tested on the maximum performance vertical jumps, cycling, bench press throws, and bench pull performed against a variety of different loads. All 4 tested tasks revealed both exceptionally strong relationships between the parameters of the 2 models (median R = 0.98) and a lack of meaningful differences between their magnitudes (fixed bias below 3.4%). Therefore, addition of another load to the standard tests of various functional tasks typically conducted under a single set of mechanical conditions could allow for the assessment of the muscle mechanical properties such as the muscle F, V, and P producing capacities.

The inertia training load is more effective than weight in increasing P and weight and inertia may be applied for selective gains in F and V, respectively, whereas the linear F-V model obtained from loaded trials could be used for discerning among muscle F, V, and P.

The main aim of the present study was to examine differences in pacing between half-marathon and marathon in men and women. A total of 17,525 finishers in the marathon (n = 4807 men; n = 1278 women) and half-marathon race (n = 7624 men; n = 3816 women) in Vienna 2017 were considered. Their pacing was assessed through five race segments (0-23.7%, 23.7-47.4%, 47.4-71.1%, 71.1-94.8% and 94.8-100%) of the race. Compared to marathon (where absolute average change of speed [ACS] was 5.46% and 4.12% in men and women, respectively), a more even pacing was observed in half-marathon in both sexes (ACS = 3.60% and 3.36% in men and women, respectively). The more even pacing in women previously observed in marathon races was verified in half-marathon, too. However, the sex difference in pacing was smaller in half-marathon than in marathon. Since men and women endurance runners participate in both races, sport practitioners would have great benefit from these results since they could establish sex-based personalized race strategies and training programmes.

The aim of the present study was to examine the age-related differences in performance and pacing in a half-marathon compared to a marathon. All finishers (n = 9137) in the Ljubljana 2017 half-marathon (n = 7258) and marathon (n = 1853) with available data on split times during the races, were analysed for pacing. Half-marathoners were slower than marathoners among women, (2.77 ± 0.35 versus 2.86 ± 0.39 m·s−1 respectively, p < 0.001), but faster among men (3.14 ± 0.45 versus 3.08 ± 0.46 m·s−1 respectively, p < 0.001). In both race distances, the <25 age group was the fastest and the >54 age group the slowest (p < 0.001). All age groups presented a positive pacing in both race distances and genders, with each segment being slower than the previous one. However, an end spurt was observed in the marathon, but not in the half-marathon. A more even pace in the half-marathon than in the marathon was shown for most age groups. In summary, age-group finishers in the half-marathon decreased running speed across the race, presented a more even pacing than marathoners, and did not show an end spurt.