ECSS Paris 2023: OP-AP18
INTRODUCTION: Resistance running(RS) is widely recognized as the most commonly used and effective method to enhance speed performance and overcome speed barriers in sprint training. Some studies have employed body mass (bm) as a benchmark, revealing that varying percentages of body mass as resistance yield different training effects. For instance, 12.5%bm RS enhances high-speed acceleration phases. Another study utilized 10%bm, 30%bm, and 50%bm for resistance running training, suggesting that faster and stronger athletes may require relatively heavier resistance to attain their training goals. This study investigates resistance ranging from 1% to 10%bm, aiming to determine if athletes with different physical characteristics benefit from personalized resistance for achieving specific training goals within this range. METHODS: Twenty-nine elite track and field athletes participated in this study, comprising 18 male and 11 female athletes. All athletes underwent the same warm-up procedure, followed by a squat 1RM test and a 30m sprint test without resistance （T-133 timing system，eliga，china）on the same day. Within one week of the initial test, the athletes engaged in resistance running training（T120-sprint training device，eliga，china）. The resistance was set between 1%-10% of the athletes body weight(bw), and the 30m times were recorded, above test excluding reaction time. Linear regression analysis was conducted using SPSS software to assess the impact of gender, weight, and relative strength (squat 1RM/body weight) on the rate of speed decline. RESULTS: The average time for the 30m sprint without resistance was recorded at 3.835 seconds, with a standard deviation of 0.123 seconds. The average relative strength was measured at 2.100, with a standard deviation of 0.251, and the average rate of speed decline was found to be 15.37%, with a standard deviation of 3.613%. For female athletes, the average 30m sprint time was 4.087 seconds, with a standard deviation of 0.133 seconds; the average relative strength was 1.818, with a standard deviation of 0.217; and the average rate of speed decline was 21.281%, with a standard deviation of 6.679%.Linear regression analysis revealed that resistance as a percentage of body weight, within the range of 1%-10% (B=1.635, p<0.01), and gender (B=0.079, p<0.01) significantly influenced the rate of speed decline. However, relative strength (B=-0.048, p=0.144) and the finish time for the sprint without resistance (B=-0.110, p=0.074) did not show a significant effect on the rate of speed decline. CONCLUSION: The findings of this study indicate that in resistance running training, when the load is below 10% of body weight (bw), the trend of speed decline is roughly similar across athletes of different strength levels as resistance increases. However, gender and the amount of load are significant factors affecting the rate of speed decline, with female athletes experiencing a slightly higher rate of decline compared to male athletes. This suggests that when des
Read CV Qingshou GuoECSS Paris 2023: OP-AP18
INTRODUCTION: The development of acceleration and maximum velocity (MV) sprint performance are key goals for field-based invasion team sport (FITS) coaches. Resisted sprint training (RST) has been shown to be an effective method for improving acceleration performance when using a broad range of loading magnitudes [1], yet there are concerns regarding the potential of ‘very heavy’ loaded RST to negatively impact MV performance [2]. Alternatively, flying sprints are used by coaches when targeting MV improvements [3]. However, no research has investigated the efficacy of a concurrent RST and maximum velocity sprint training (MVST) protocol. This study aimed to determine the effectiveness of a combined RST and MVST approach on the in-season acceleration and maximum velocity performance of FITS players. METHODS: Elite level, male hurling players were assigned to an experimental group (EG) (n=21) or a control group (n=19). In addition to their regular training, the EG performed two sessions (1 x RST, 1 x MVST) per week for 8 weeks, while the control group performed unresisted sprinting (5-20m repetition distance range). RST was performed with a 50% Vdec load and a constant repetition distance of 15m, while MVST consisted of 8-12m flying sprints with a 25m build-up phase. Sprint, strength, and jump performance were measured at 1-week pre and post intervention. RESULTS: The EG displayed significant small within-group (pre to post) improvements in 5m (d = 0.57) and 10m (d = 0.44) split times, and MV (d = 0.35), while a significant moderate increase in SLJ performance (d = 0.89) was also found. A significant decrease in reactive strength (d = 0.42) and increase in relative strength (d = 0.53) were detected for the CG. Finally, there were significant time effects for first step flight time (FT) (p = 0.004) last step FT (p = 0.035), and the 10-20 m split time (p = 0.018). CONCLUSION: Performing a weekly combination of very-heavy RST and MVST across an 8-week in-season training block can yield improvements in both early acceleration and MV sprint performance. Additionally, study findings dampen previous concerns regarding the potentially negative impact of heavy-loaded RST on MV. Our study highlights the utility of this RST (using 8 sleds) and MVST approach within FITS settings, integrated prior to collective in-season sports training using a short 20-minute time slot.
Read CV Cormac WardECSS Paris 2023: OP-AP18
INTRODUCTION: High-speed running is fundamental to perform in various sports. Muscle morphological (volume) and functional characteristics (strength) are recognized to be associated with sprint performance [1,2] and seem to influence sprint force-power-velocity (FPV) relationship [3]. This study aimed to identify the relationships between sprint maximal velocity (Vmax), theoretical maximal power (Pmax) and force (F0) derived from the sprint FVP profiles, and lower limb muscle characteristics including volume inferred from automatized MRI scans segmentation in elite athletes. METHODS: Seventy-two athletes (33 women, 39 men, age: 24.3 ± 3.3 years, height: 1.77 ± 0.09 m, mass: 74.2 ± 12.9 kg) of rugby 7, track and field, and bobsleigh performed two 40-m sprints. Vmax and FVP relationship were assessed using radar-based velocity measurements. F0 and Pmax were calculated from the FPV relationship. Maximal isometric (MVC) and eccentric (ECC) torque, and rate of torque development (RTD) were assessed during hip, knee and ankle extension and flexion (except for ankle). The volume of 18 lower limb muscles including gluteus, quadriceps, hamstrings and adductors groups was automatically extracted from Magnetic Resonance imaging (MRI) using Deep Learning method [4] for 24 athletes (14 women and 10 men). Multiple linear regressions (Forward method) were conducted to identify significant predictors of Pmax, F0 and Vmax (dependant variables) from the functional characteristics and then the 18 muscle volumes (independent variables). RESULTS: Vmax exhibited significant correlations with the volume of the vastus intermedius (VI), gluteus minimus (Gmin), biceps femoris short head (BFsh) and semitendinosus (ST) muscles (r2 = 0.62, P < 0.05). Pmax showed significant correlations with VI, BFsh, gluteus maximus (Gmax) and ST volumes (r2 = 0.70, P < 0.05) whereas F0 showed significant correlations with VI and Gmax volume (r2 = 0.58, P < 0.05). Furthermore, Vmax was significantly correlated with plantar flexor RTD and hip flexor MVC (r2 = 0.20, P < 0.05) whereas Pmax and F0 were both significantly correlated with plantar flexor RTD and knee flexor MVC (r2 = 0.18 and r2 = 0.13, respectively, P < 0.05). CONCLUSION: This study shows that a significant part of sprint performance variability could be explained by hip flexors and knee extensors muscle volume. Joint strength testing seems also to partly explain sprint performance. Hip extensor and knee flexor muscles could be targeted in training programs to maximize sprint performance. While these findings are consistent with previous studies [1,5,6], they suggest to further explore the relationship between muscle morphology, functional capacity and sprint performance, particularly for thigh muscles. REFERENCES: 1.Miller et al., 2021, MSSE 2.Bellinger et al., 2020, MSSE 3.Rabita et al., 2015, Scand J Med Sci Sports 4.Piecuch et al., 2023, in Shape in Medical Imaging 5.Takahashi et al., 2021, PlosOne 6.Takahashi et al., 2024, Sport Biomech
Read CV Caroline GIROUXECSS Paris 2023: OP-AP18