This study aimed (i) to explore the relationship between vertical (jumping) and horizontal (sprinting) force–velocity–power (FVP) mechanical profiles in a large range of sports and levels of practice, and (ii) to provide a large database to serve as a reference of the FVP profile for all sports and levels tested. A total of 553 participants (333 men, 220 women) from 14 sport disciplines and all levels of practice participated in this study. Participants performed squat jumps (SJ) against multiple external loads (vertical) and linear 30–40 m sprints (horizontal). The vertical and horizontal FVP profile (i.e., theoretical maximal values of force (F0), velocity (v0), and power (Pmax)) as well as main performance variables (unloaded SJ height in jumping and 20-m sprint time) were measured. Correlations coefficient between the same mechanical variables obtained from the vertical and horizontal modalities ranged from −0.12 to 0.58 for F0, −0.31 to 0.71 for v0, −0.10 to 0.67 for Pmax, and −0.92 to −0.23 for the performance variables (i.e, SJ height and sprint time). Overall, results showed a decrease in the magnitude of the correlations for higher-level athletes. The low correlations generally observed between jumping and sprinting mechanical outputs suggest that both tasks provide distinctive information regarding the FVP profile of lower-body muscles. Therefore, we recommend the assessment of the FVP profile both in jumping and sprinting to gain a deeper insight into the maximal mechanical capacities of lower-body muscles, especially at high and elite levels.

The purpose of this study was to assess validity and reliability of sprint performance outcomes measured with an iPhone application (named: MySprint) and existing field methods (i.e. timing photocells and radar gun). To do this, 12 highly trained male sprinters performed 6 maximal 40-m sprints during a single session which were simultaneously timed using 7 pairs of timing photocells, a radar gun and a newly developed iPhone app based on high-speed video recording. Several split times as well as mechanical outputs computed from the model proposed by Samozino et al. [(2015). A simple method for measuring power, force, velocity properties, and mechanical effectiveness in sprint running. Scandinavian Journal of Medicine & Science in Sports. https://doi.org/10.1111/sms.12490] were then measured by each system, and values were compared for validity and reliability purposes. First, there was an almost perfect correlation between the values of time for each split of the 40-m sprint measured with MySprint and the timing photocells (r = 0.989-0.999, standard error of estimate = 0.007-0.015 s, intraclass correlation coefficient (ICC) = 1.0). Second, almost perfect associations were observed for the maximal theoretical horizontal force (F), the maximal theoretical velocity (V), the maximal power (P) and the mechanical effectiveness (DRF - decrease in the ratio of force over acceleration) measured with the app and the radar gun (r = 0.974-0.999, ICC = 0.987-1.00). Finally, when analysing the performance outputs of the six different sprints of each athlete, almost identical levels of reliability were observed as revealed by the coefficient of variation (MySprint: CV = 0.027-0.14%; reference systems: CV = 0.028-0.11%). Results on the present study showed that sprint performance can be evaluated in a valid and reliable way using a novel iPhone app.

These results suggest that the simple method presented here is valid and reliable for computing CMJ force, velocity, power, and F-v profiles in athletes and could be used in practice under field conditions when body mass, push-off distance, and jump height are known.

Compared to SJ, F-v relationships were shifted to the right in CMJ, with higher P max, maximal theoretical force and velocity (+35.8, 20.6 and 13.3%, respectively). As in SJ, CMJ performance depends on Fv IMB, independently from the effect of P max, with the existence of an individual optimal F-v profile (Fv IMB having an even larger influence in CMJ).

No abstract

Ortega-Becerra, M, Pareja-Blanco, F, Jiménez-Reyes, P, Cuadrado-Peñafiel, V, and González-Badillo, JJ. Determinant factors of physical performance and specific throwing in handball players of different ages. J Strength Cond Res 32(6): 1778-1786, 2018-This study aimed to analyze various fitness qualities in handball players of different ages and to determine the relationships between these parameters and throwing velocity. A total of 44 handball players participated, pooled by age groups: professional (ELITE, n = 13); under-18 (U18, n = 16); under-16 (U16, n = 15). The following tests were completed: 20-m running sprints; countermovement jumps (CMJs); jump squat to determine the load that elicited ∼20 cm jump height (JSLOAD-20 cm); a progressive loading test in full squat and bench press to determine the load that elicited ∼1 m·s (SQ-V1-LOAD and BP-V1-LOAD); and handball throwing (jump throw and 3-step throw). ELITE showed greater performance in almost all sprint distances, CMJ, JSLOAD-20 cm, and bench press strength than U18 and U16. The differences between U18 and U16 were unclear for these variables. ELITE also showed greater (p < 0.001) performance for squat strength and throwing than U18 and U16, and U18 attained greater performance (p ≤ 0.05) for these variables than U16. Throwing performance correlated (p ≤ 0.05) with sprint times (r = -0.31; -0.51) and jump ability (CMJ: r = 0.39; 0.56 and JSLOAD-20 cm: r = 0.57; 0.60). Muscle strength was also associated (p < 0.001) with both types of throw (SQ-V1-LOAD: r = 0.66; 0.76; and BP-V1-LOAD: r = 0.33; 0.70). These results indicate that handball throwing velocity is strongly associated with lower-limb strength, although upper-limb strength, jumping and sprint capacities also play a relevant role in throwing performance, suggesting the need for coaches to include proper strength programs to improve handball players' throwing velocity.

The absence of significant correlations between some of the FV relationship parameters suggests that for an individualized training prescription based on the FV profile both jumping and sprinting testing procedures should be performed with elite female soccer players.

Purpose: To compare the sprint mechanical force–velocity (F–V) profile between soccer and futsal players. A secondary aim was, within each sport, to study the differences in sprint mechanical F–V profile between sexes and players of different levels. Methods: A total of 102 soccer players (63 men) and 77 futsal players (49 men) who were competing from the elite to amateur levels in the Spanish league participated in this investigation. The testing procedure consisted of 3 unloaded maximal 40-m sprints. The velocity–time data recorded by a radar device were used to calculate the variables of the sprint acceleration F–V profile (maximal theoretical force [F0], maximal theoretical velocity [V0], maximal power [Pmax], decrease in the ratio of horizontal to resultant force [DRF], and maximal ratio of horizontal to resultant force [RFpeak]). Results: Futsal players showed a higher F0 than soccer players (effect size [ES] range: 0.11–0.74), while V0 (ES range: −0.48 to −1.15) and DRF (ES range: −0.75 to −1.45) was higher for soccer players. No significant differences were observed between soccer and futsal players for Pmax (ES range: −0.43 to 0.19) and RFpeak (ES range: −0.49 to 0.30). Men and high-level players presented an overall enhanced F–V profile compared with women and their lower-level counterparts, respectively. Conclusions: The higher F0 and lower V0 of futsal players could be caused by the game’s specific demands (larger number of accelerations but over shorter distances than in soccer). These results show that the sprint mechanical F–V profile is able to distinguish between soccer and futsal players.