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Success in long jump performance mainly
Success in long jump performance mainly depends on the ability of the athlete to transform his horizontal approach velocity into horizontal and vertical takeoff (TO) velocity during the support phase of the jump. Biomechanical analyses indicate that the TO is prepared by a lowering of the center of gravity (CG) during the last strides of the approach run (e.g., 1–4). It was stated by Hay/Nohara, that elite long jumpers lowered their CG during the flight phase of the second-last stride and stayed low until they raised it for the TO during the support phase of the jump itself (5). The same authors observed an inc rease of the touchdown (TD) distance for the last stride

Success in long jump performance mai
Success in long jump performance mainly depends on the ability of the athlete to transform his horizontal approach velocity into horizontal and vertical takeoff (TO) velocity during the support phase of the jump. Biomechanical analyses indicate that the TO is prepared by a lowering of the center of gravi ty (CG) during the last strides of the approach run (e.g., 1–4). It was stated by Hay/Nohara, that elite long jumpers lowered their CG during the flight phase of the second-las t stride and stayed low until they raised it for the TO during the support phase of the jump itself (5). The same authors observed an increase of the touchdown (TD) distance for the last stride

and the jump. Further, a lengthening of the second-last stride has been considered as a corresponding factor for the lowering of the CG (e.g., 4, 6, 7), but there are contradictory find ings as well (e.g., 2, 8, 9). While it is a com mon approach for biomechanical analyses, in all studies mentioned above, time discrete data such as heights or velocities of CG at TO and TD of each stride were analyzed. Therefore, the results can only serve as an indicator of what the athlete has done up to this point in his performance or of what he may be able to do from this point (see 5).

Relatively few investigations deal with the problem of how a long jumper should move his/her body segments to achieve the aspired positions. Relating to the movement technique, a backward sweeping or “active” landing of the supporting leg (that can be characterized by a negative touchdown velocity) has been recommended for the last strides as well as for the jump (10, 11). Koh/Hay (10) also stated in their study that elite long jumpers used a less “active” landing in the last stride than in the two preceding strides. Ramlow/Romanautzky concluded from a single case study that the lowering of the CG during the last stride was supported by the motion of the swinging leg that moved in a lower position than in the preceding strides (12). Those results are mainly based on mathematical simulation, the analysis of discrete parameters, or more qualitative considerations.

Methods

= baso de agua = More detailed knowledge about the movement processing is available if time continuous data are analyzed. Based on a pattern recognition approach, analyses of the time courses of kinematic and dynamic variables have been useful recently in identifying adaptations of ballistic sports movements following motor learning (13) or changes in the environment (14). Similar procedures were also used to investigate structural differences between slightly varying movements—for example, the long jump TO from various heights (15) or between following phases during a singular running movement (16). As a common result of those and several other studies, highly individual movement styles were stated for high performance level athletes as well as for subjects with quite inferior performances (e.g., students; 16–18).

The purpose of this investigation was to study long jump performance in the last strides of the approach run and the jump based on the analysis of time continuous data. Special interest was on two topics: (a) to identify differences and changes of movement patterns in the transition from approach to TO and (b) to investigate to what extent changes in the complex pattern may be explained by single variables that describe partial motions of body segments.