Kinematic Analysis of Sprinting Pickup Acceleration versus Maximum Sprinting Speed.

Manzer, Stefanie; Mattes, Klaus; Hollander, Karsten

doi:10.4127/jbe.2016.0109

Cited by 7 publications

(4 citation statements)

References 7 publications

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“…The average sprint speed achieved by junior football players in the variables M10SS and M10LSS was 5.77 m/s and 7.04 m/s, respectively, while the cadet age football players achieved a speed of 5.57 m/s and 6.82 m/s, respectively. Similar results were obtained by Manzer et al (2016) on a sample of n = 8 athletes aged 17 years and in = 8 athletes aged 19 years, where they recorded an average sprint speed time of 9.2 m / s and 8.0 m/s for 10m running. Also, Vescovi et al (2011) recorded a running speed of 6.84 m / s for U15 football players, while they recorded a running speed of 7.01 m/s for U16 football players.…”

Section: Discussionsupporting

confidence: 81%

Motor-functional profile of footballers of junior and cadet age

Anđelić

Vasić

Karišik

et al. 2021

Turkish Journal of Kinesiology

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Football is probably the most popular game around the world, having taken over the globe with 256 million registered players in 208 countries. The aim of the study was to determine the differences in motor and functional abilities between football players of junior and cadet age. The research included a sample of 39 football players of the Kicker Football Club from Kraljevo, divided into two subsamples: 20 football players of junior age of chronological age of 17 ± 0.6 years and 19 football players of cadet age of chronological age of 15 ± 0.6 years. The following tests were used to assess motor skills: Starting acceleration at 10 m, Starting acceleration at 10 m flying start, maximum running speed during the test at 10 m, maximum running speed during the test at 10 m flying start, Illinois Agility test, while the following tests were used to assess functional abilities: Maximum oxygen consumption and maximum heart rates. The results of the study indicate that statistically significant differences were recorded only in motor abilities. The emphasis on working with younger categories should be placed on the long-term development process, to enable better success in senior age.

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Section: Discussionsupporting

confidence: 81%

Motor-functional profile of footballers of junior and cadet age

Anđelić

Vasić

Karišik

et al. 2021

Turkish Journal of Kinesiology

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“…Numerous studies Journal of Human Kinetics, volume 93, July 2024 http://www.johk.pl have shown a lack of consensus on some variables, e.g. step length, specific speed, and anthropometric variables (Bezodis, 2012;Coh et al, 2010;Debaere et al, 2013;Manzer et al, 2016;Mates et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Kinematics of Two Special Endurance Trials: A Methodological Contribution to 400-m Performance

Mackala,

Omelko,

Mroczek

et al. 2024

Journal of Human Kinetics

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This study aimed to determine changes in the kinematics of sprint steps based on progressive muscular fatigue during high-intensity 350-m and 500-m trials. Twelve elite healthy male 400-m sprinters with a minimum of six years of regular sprint training experience were recruited. They were divided into two groups for the experiment: a 350-m and a 500-m trial group. Time and kinematics of sprinting step motion for specific segments, i.e., starting to final stages of each trial, were obtained using the Opto Jump-Microgate optical measurement system. The starting phase of each sprint was defined as the section without muscular fatigue (noF), and the final phase was the sprint under muscular fatigue (onF). Each last 25 m of the 50-m evaluated section containing ten complete running steps was selected for detailed statistical analysis. Various patterns of temporal and spatial variables of sprinting efforts were observed between 350-m and 500-m trials. Each trial result was influenced by significant individual changes (p < 0.05). All variables indicated that the two distances differed significantly in terms of running kinematics. This was confirmed by significant differences in the mean step frequency (p < 0.001), which presented a difference of 11.75%, and the mean step speed (p < 0.001). As a result of these changes, a hierarchical intermittent endurance training pattern was defined. The research concluded that special endurance (intermittent sprints) based on 350 m differed significantly in kinematics from sprints over 500 m. Therefore, it should be assumed that the distance of 350 m is more similar in its kinematics to the 400-m competition. This should encourage coaches and athletes to apply a 350-m distance in training developing special endurance, especially in the pre-competitive and competitive periods.

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“…Research has mostly investigated the first acceleration phase of the run (Nagahara et al, 2018a ; Bezodis et al, 2019 ) typically trying to understand the step-to-step relations during acceleration based on ground reaction forces (Hunter et al, 2005 ; Rabita et al, 2015 ; Colyer et al, 2018 ; Nagahara et al, 2018a ) and characteristic body angles by high-precision 3D kinematics (Manzer et al, 2016 ; Mattes et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Sprint Parameters in Top Speed Interval in 100 m Sprint—A Pilot Study Under Field Conditions

Seidl¹,

Russomanno²,

Stöckl³

et al. 2021

Front. Sports Act. Living

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Improving performances in sprinting requires feedback on sprint parameters such as step length and step time. However, these parameters from the top speed interval (TSI) are difficult to collect in a competition setting. Recent advances in tracking technology allows to provide positional data with high spatio-temporal resolution. This pilot study, therefore, aims to automatically obtain general sprint parameters, parameters characterizing, and derived from TSI from raw speed. In addition, we propose a method for obtaining the intra-cyclic speed amplitude in TSI. We analyzed 32 100 m-sprints of 7 male and 9 female athletes (18.9 ± 2.8 years; 100 m PB 10.55–12.41 s, respectively, 12.18–13.31 s). Spatio-temporal data was collected with a radio-based position detection system (RedFIR, Fraunhofer Institute, Germany). A general velocity curve was fitted to the overall speed curve (vbase), TSI (upper quintile of vbase values) was determined and a cosine term was added to vbase within TSI (vcycle) to capture the cyclic nature of speed. This allowed to derive TSI parameters including TSI amplitude from the fitted parameters of the cosine term. Results showed good approximation for vbase (error: 5.0 ± 1.0%) and for vcycle (2.0 ± 1.0%). For validation we compared spatio-temporal TSI parameters to criterion values from laser measurement (speed) and optoelectric systems (step time and step length) showing acceptable RMSEs for mean speed (0.08 m/s), for step time (0.004 s), and for step length (0.03 m). Top speed interval amplitude showed a significant difference between males (mean: 1.41 m/s) and females (mean: 0.71 m/s) and correlations showed its independence from other sprint parameters. Gender comparisons for validation revealed the expected differences. This pilot study investigated the feasibility of estimating sprint parameters from high-quality tracking data. The proposed method is independent of the data source and allows to automatically obtain general sprint parameters and TSI parameters, including TSI amplitude assessed here for the first time in a competition-like setting.

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Kinematic Analysis of Sprinting Pickup Acceleration versus Maximum Sprinting Speed.

Cited by 7 publications

References 7 publications

Motor-functional profile of footballers of junior and cadet age

Motor-functional profile of footballers of junior and cadet age

Kinematics of Two Special Endurance Trials: A Methodological Contribution to 400-m Performance

Assessment of Sprint Parameters in Top Speed Interval in 100 m Sprint—A Pilot Study Under Field Conditions

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