Sprint performance and mechanical outputs computed with an iPhone app: Comparison with existing reference methods

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 (F0), the maximal theoretical velocity (V0), the maximal power (Pmax) 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.Actividad Física y Deport

Differences between adjusted vs. non- adjusted loads in velocity-based training: consequences for strength training control and programming

Strength and conditioning specialists commonly deal with the quantification and selection the setting of protocols regarding resistance training intensities. Although the one repetition maximum (1RM) method has been widely used to prescribe exercise intensity, the velocity-based training (VBT) method may enable a more optimal tool for better monitoring and planning of resistance training (RT) programs. The aim of this study was to compare the effects of two RT programs only differing in the training load prescription strategy (adjusting or not daily via VBT) with loads from 50 to 80% 1RM on 1RM, countermovement (CMJ) and sprint. Twenty-four male students with previous experience in RT were randomly assigned to two groups: adjusted loads (AL) (nD13) and non-adjusted loads (NAL) (nD11) and carried out an 8-week (16 sessions) RT program. The performance assessment pre- and post-training program included estimated 1RM and full load-velocity profile in the squat exercise; countermovement jump (CMJ); and 20-m sprint (T20). Relative intensity (RI) and mean propulsive velocity attained during each training session (Vsession) was monitored. Subjects in the NAL group trained at a significantly faster Vsession than those in AL (p < 0.001) (0.88 - 0.91 vs. 0.67- 0.68 m/s, with a 15% RM gap between groups for the last sessions), and did not achieve the maximum programmed intensity (80% RM). Significant differences were detected in sessions 3- 4, showing differences between programmed and performed Vsession and lower RI and velocity loss (VL) for the NAL compared to the AL group (p < 0.05). Although both groups improved 1RM, CMJ and T20, NAL experienced greater and significant changes than AL (28.90 vs.12.70%, 16.10 vs. 7.90% and -1.99 vs. - 0.95%, respectively). Load adjustment based on movement velocity is a useful way to control for highly individualised responses to training and improve the implementation of RT programs

Do you Play or Do you Train? Insights From Individual Sports for Training Load and Injury Risk Management in Team Sports Based on Individualization

[EN] The understanding of the potential causes of musculoskeletal injuries in any competitive sport needs to address their multifactorial nature, which results from complex associations among different external conditions and modifiable and non-modifiable intrinsic risk factors (Drew and Purdam, 2016; Kalkhoven et al., 2020a). In this context, the cause of any non-contact injury merely results from a sum of loads generating a force that exceeds the limit supported by the respective biological tissue (Zernicke and Whiting, 2008). Consequently, it has been suggested that a poor load management is a major risk factor for injury in sport settings (Gabbett, 2016). One novel monitoring tool for injury risk management is the acute: chronic workload ratio (ACWR). The ACWR is currently in the spot light of sport sciences (Griffin et al., 2020; Maupin et al., 2020). While some emerging evidence suggests that it is a valid method to identify an increased injury risk (Andrade et al., 2020), other authors have pointed out its methodological limitations and even questioned its validity (Impellizzeri et al., 2020; Wang et al., 2020). Proponents of the ACWR approach argue that athletes are at greater risk of sustaining a time-loss injury when the ACWR is higher relative to a lower or moderate ACWR (Andrade et al., 2020). In other words, the ACWR helps to identify critical windows in terms of elevated injury risk based on imbalanced training loading as for example sudden spike loads (Bowen et al., 2020)

Performance and ranking position evolution during 20 competitive seasons in elite 100 meter sprinters

The literature contains several researches seeking to analyse and predict the behaviour of 100-meter dash performance through different mathematical models. Although when analysing the historical records in their entirety these simple models fit largely to their behaviour of the historical series, these approximations are not valid when the focus is on the analysis of accumulated times over the past 2 decades. For this reason, this work proposes new alternatives such as polynomial gradient or smooth models capable of explaining with greater accuracy what has happened during the last 20 years for this modality. Therefore, in order to analyse the distribution of competitive marks relative to the top five and bottom five in the ranking over a period of 20 seasons, a total amount of 428 records corresponding to the marks obtained by international level male athletes who conformed the IAAF world ranking in the 100 m race during the 20 indicated seasons were considered for this goal. The main findings of this research conclude with the lack of fitting between the simple approaches (linear or exponential models) and the reported decline in the records -therefore better performance- throughout the analysed period. In return, this work reveals the existence of a tendency towards overall reduction of time records, denoting a positive evolution of the "competitive health" of the discipline. These evolutions, however, seem to be influenced by the position in which athletes qualify, thus showing greater reductions for athletes classified in the bottom five than for those classified in the top five

Effects of Fatigue Induced by Repeated Sprints on Sprint Biomechanics in Football Players: Should We Look at the Group or the Individual?

The aim of this study was to analyse the influence of fatigue on sprint biomechanics. Fifty-one football players performed twelve maximal 30 m sprints with 20 s recovery between each sprint. Sprint kinetics were computed from running speed data and a high-frequency camera (240 Hz) was used to study kinematic data. A cluster analysis (K-mean clustering) was conducted to classify individual kinematic adaptations. A large decrease in maximal power output and less efficiency in horizontally orienting the ground reaction force were observed in fatigued participants. In addition, individual changes in kinematic components were observed, and, according to the cluster analysis, five clusters were identified. Changes in trunk, knee, and hip angles led to an overall theoretical increase in hamstring strain for some players (Cluster 5, 20/51) but to an overall decrease for some others (Cluster 1, 11/51). This study showed that the repeated sprint ability (RSA) protocol had an impact on both kinetics and kinematics. Moreover, fatigue affected the kinematics in a different way for each player, and these individual changes were associated with either higher or lower hamstring length and thus strain

Mechanical, metabolic, and perceptual acute responses to different set configurations in full squat

This study aimed to compare mechanical, metabolic, and perceptual responses between 2 traditional (TR) and 4 cluster (CL) set configurations. In a counterbalanced randomized order, 11 men were tested with the following protocols in separate sessions (sets x repetitions [interrepetition rest]): TR1: 3 x 10 [0 seconds]; TR2: 6 x 5 [0 seconds]; CL1: 3 x 10 [10 seconds]; CL2: 3 x 10 [15 seconds]; CL3: 3 x 10 [30 seconds]; CL4: 1 x 30 [15 seconds]. The exercise (full squat), number of repetitions (30), interset rest (5 minutes), and resistance applied (10 repetition maximum) was the same for all set configurations. Mechanical fatigue was quantified by measuring the mean propulsive velocity during each repetition and the change in countermovement jump height observed after each set and after the whole training session. Metabolic and perceptual fatigue were assessed via the blood lactate concentration and the OMNI perceived exertion scale measured after each training set, respectively. The mechanical, metabolic, and perceptual measures of fatigue were always significantly higher for the TR1 set configuration. The 2 set configurations that most minimized the mechanical measures of fatigue were CL2 and CL3. Perceived fatigue did not differ between the TR2, CL1, CL2, and CL3 set configurations. The lowest lactate concentration was observed in the CL3 set configuration. Therefore, both the CL2 and CL3 set configurations can be recommended because they maximize mechanical performance. However, the CL2 set configuration presents 2 main advantages with respect to CL3 (a): it reduces training session duration, and (b) it promotes higher metabolic stress, which, to some extent, may be beneficial for inducing muscle strength and hypertrophy gains

Microdosing Sprint Distribution as an Alternative to Achieve Better Sprint Performance in Field Hockey Players

Introduction: The implementation of optimal sprint training volume is a relevant component of team sport performance. This study aimed to compare the efficiency and effectiveness of two different configurations of within-season training load distribution on sprint performance over 6 weeks. Methods: Twenty male professional FH players participated in the study. Players were conveniently assigned to two groups: the experimental group (MG; n = 11; applying the microdosing training methodology) and the control group (TG; n = 9; traditional training, with players being selected by the national team). Sprint performance was evaluated through 20 m sprint time (T20) m and horizontal force–velocity profile (HFVP) tests before (Pre) and after (Post) intervention. Both measurements were separated by a period of 6 weeks. The specific sprint training program was performed for each group (for vs. two weekly sessions for MG and TG, respectively) attempting to influence the full spectrum of the F-V relationship. Results: Conditional demands analysis (matches and training sessions) showed no significant differences between the groups during the intervention period (p > 0.05). No significant between-group differences were found at Pre or Post for any sprint-related performance (p > 0.05). Nevertheless, intra-group analysis revealed significant differences in F0, Pmax, RFmean at 10 m and every achieved time for distances ranging from 5 to 25 m for MG (p p < 0.05). Conclusion: Implementing strategies such as microdosed training load distribution appears to be an effective and efficient alternative for sprint training in team sports such as hockey