Analysis of the start to the first hurdle in 110 m hurdles at the IAAF World Athletics Championships Beijing 2015

Amo, José Luis López del; Rodríguez, Maria Carmen Afaro; Hill, David W.; González, Julián Ernesto

doi:10.14198/jhse.2018.133.03

Cited by 7 publications

(8 citation statements)

References 4 publications

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“…Elite-level athletes had shorter split times in all race phases than high-level athletes (men: δ 5–11%; women: δ 7–14%). These results suggest that elite-level participants do not only perform a faster approach run (as also reported by López del Amo et al, 2018) and hurdle unit phases, but are significantly faster during the run-in phase.…”

Section: Discussionsupporting

confidence: 70%

“…The split times in the approach run phase of elite-level hurdlers (Table 2) were slightly greater than those reported in previous studies carried out with this standard of athletes (Muller and Hommel, 1997; Graubner and Nixdorf, 2011; Tsiokanos et al, 2017; López del Amo et al, 2018; Pollitt et al, 2018a,b; Walker et al, 2019a,b). These differences could be explained by the greater sample size employed in the present research (30 men and 27 women athletes) in comparison to the seven or eight finalists studied during the above-mentioned studies.…”

Section: Discussionmentioning

confidence: 52%

“…The most common analysis of the hurdle’s races has been carried out through an evaluation of the hurdle split times (from touchdown to touchdown behind the hurdle), using video recordings with a fixed or panned video-camera both in 110 and 100 m (Muller and Hommel, 1997; Graubner and Nixdorf, 2011; Tsiokanos et al, 2017; Pollitt et al, 2018a,b) as of 60 m hurdles (Walker et al, 2019a,b). López del Amo et al (2018) found that the reaction time and the approach run time were predictors of race performance, however, Tsiokanos et al (2017) did not observed a significant relationship between reaction time and the race performance. Similarly, Tsiokanos et al (2017) determined that the correlation between the intermediate times and final performance was decisive from the fifth hurdle onwards in the 110 m hurdles event ( r = 0.77 – 0.98).…”

Section: Introductionmentioning

confidence: 79%

“…Findings from these kinematical analyses suggest that efficient hurdle clearance technique is associated to the take-off contact time, take-off to landing point ratio in relation to the hurdle and to the hurdle flight time. In addition to the hurdle unit phase, the approach run phase (Rash et al, 1990; López del Amo et al, 2018; Walker et al, 2019a,b) has been subjected to kinematic analysis. To our knowledge, the run-in phase has been excluded from all the investigations carried so far, except for the research carried out by Pollitt et al (2018a,b).…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal Comparisons Between Elite and High-Level 60 m Hurdlers

et al. 2019

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Despite the existence of literature on the athletics hurdles event, no previous studies have examined the kinematic behavior of athletes during the race. The aims of the present research were (1) to compare the spatiotemporal parameters of elite and high-level hurdlers (men and women) in the approach run, hurdles-unit and run-in phases and (2) to relate these parameters to the 60 m end race results. Split times, step lengths, step widths, step times, contact times and flight times were calculated for the 60 m hurdlers (n = 110) who participated in the 44th Spanish Indoor Championship and in the 12th IAAF World Indoor Championship. Both men and women elite-level hurdlers obtained shorter split times than high-level hurdlers in the approach run (δ 0.14 ± 0.01 and 0.18 ± 0.02 s, respectively), the hurdles-unit (δ 0.11 ± 0.01 and 0.13 ± 0.01 s, respectively) and the run-in (δ 0.10 ± 0.01 and 0.20 ± 0.02 s, respectively) race phases. Elite-level men athletes also presented lower step lengths in the approach run phase (δ 0.01 ± 0.00 m), greater take-off distances (δ 0.10 ± 0.03 m) and shorter landing distances (δ 0.17 ± 0.05 m) than high-level athletes, although elite-level women hurdlers only showed longer landing step length (δ 0.07 ± 0.02 m) than high-level athletes. Finally, in the run-in phase, elite-level hurdlers had longer step lengths than high-level hurdlers (men: δ 0.09 ± 0.03 m; women: δ 0.11 ± 0.03 m). Step times, contact times and flight times were also different between both levels of performance in most of the race phases. Correlational analysis with the race result showed large (r > 0.5), very large (r > 0.7), or nearly perfect (r > 0.9) relationships for most of the mentioned kinematic parameters. These results indicate that elite-level athletes were faster than high-level in the three phases of the 60 m hurdles event, specifically in some new spatiotemporal parameters (e.g. step length in the run-in phase) as well as others already studied. Accordingly, coaches and athletes should implement their training programs to have an impact on these key variables.

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Section: Discussionsupporting

confidence: 70%

Section: Discussionmentioning

confidence: 52%

Section: Introductionmentioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal Comparisons Between Elite and High-Level 60 m Hurdlers

et al. 2019

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“…In this study, the kinematic parameters were referred to pervious research [Čoh and Iskra, 2012;López et al, 2018]. For the purposes of the study, ten high-speed Casio Ex F1 camera (Casio Electronics, Japan) was placed 6m to the side (the right side, from the runner's perspective) of each of the 10 hurdles at a height of 1.07m.…”

Section: Methodsmentioning

confidence: 99%

The wearable devices application for evaluation of 110 meter high hurdle race

Ho¹,

Chang²,

Lin³

2019

jhse

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Purpose: This study was intended to explore the continuous changes in the kinematic parameters of hurdlers in a 110 meter (110m) high hurdle race from hurdles 1 through 10. Method: Ten excellent college athletes who specialized in the 110m high hurdle race volunteered for this study. Inertial measurement units (IMUs) strapped to the back of the athlete's feet and 10 high-speed cameras were used to document the movements of the hurdlers as they were hurdling along the entire track. Kwon3D and MATLAB computer programs were employed for the analysis of kinematic parameters (take-off distance, landing distance, takeoff distance percentage, landing distance percentage, flight time, time between hurdles, hurdle cycle time, hurdle cycle velocity, height of centre gravity above the hurdle and takeoff angles). The trend analysis was introduced to test the changes of the parameters between hurdles. The level of significance was set to α =.05. Results: The results showed that the subjects averaged 14.31±0.29 seconds in their 110m high hurdle tests. Regarding the trend analysis, all kinematic parameters except landing distance displayed quadratic linear patterns along the 110m race. Conclusion: The athletes rapidly gained speed as they sprinted from the starting line and reached their maximum speeds between hurdles 5 and 6, after which their speed declined. In addition, the kinematic parameters changed as the running velocity varied.

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