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EN
Background: The purpose of this study was to obtain knowledge on tactics of long distance swimming at the highest women professional level.Material/Methods: Eight swimmers, finalists of 800 m distance of freestyle of the Beijing 2008 Olympic Games were examined. The distribution of velocity of swimming for the entire distance based on 50 m segments was analyzed. Partial, halves and quarters velocity, speed indexes and linear and nonlinear regression equations were calculated.Results: It was revealed that better swimmers (placed 1-3) had their distribution of swimming as an ascending line and with very small difference between segmental velocity and that of the entire distance, while the rest of swimmers had a descending velocity line and a higher dispersion of partial values.Conclusions: High performance swimmers have to hold uniform velocity of movement with small dispersion along the entire distance of swimming.
EN
Background: Tactics in endurance disciplines is often considered by a analysis of distribution of velocity at a distance. Long-distance swimming (800m, 1500m) is a discipline perfectly located in the above definition. Thus the purpose of the paper is to deepen knowledge on sport tactics based on the distribution of velocity by athletes training swimming at the highest level.Material/Methods: The research material comprised finalists of the swimming race on the 800 meters at the Olympic Games in Beijing (2008) and the World Championships in Rome (2009). Data on the average speed for the entire distance and average speed for the 50-meter segments were analyzed. The average speed for the "halves" (350m and 400m) and "quarters" (150m, 200m, 200m, 200m) was calculated, and the specific "velocity differences index" was also identified (VDI). To illustrate the results better, a linear and non-linear regression equation was used.Results: The results show that the top athletes both of the Beijing Olympics and the World Championships in Rome maintain consistency of the pace; deviations from the average velocity are low, and increasing speed happens at the finish. The analysis of non-linear regression equation confirms this observation. The second "half" of the distance is covered by the best swimmer at higher speeds compared to the first part of the distance; the analysis of "quarters" indicates that the middle one is the slowest. The values of VDI for "halves" have the lowest values in both races for the best swimmers.Conclusions: The analysis of results justifies the conclusion that primarily it is the constant pace of the race that gives a chance to obtain a high result. The ultimate way in which the race is to be executed depends on athlete's individual predispositions; however, maintaining a constant high speed without speeding up at the finish proved to be an effective tactic in the case of one of the top athletes in both races.
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The Efficiency Model of Goalkeeper's Actions in Soccer

51%
EN
Background: The purpose of this paper was to present cognitive models illustrating efficiency of the goalkeeper's actions in soccer based on observation of play in selected matches of the Euro 2008 finals.Material/Methods: The observation method was used in the study. The play of both goalkeepers was analysed in 7 soccer matches in a cup phase of the European Championships which took place in Portugal in 2008. The data was recorded on the authors' observation forms. Activity, effectiveness and reliability during both offensive and defensive actions were subject to this examination.Results: It was revealed that most actions of the goalkeeper are aimed at taking control of the field of play or keeping possession of the ball; creating goal scoring opportunity represents only a small percentage of offensive actions. Defensive actions are generally performed individually and the highest reliability is reported while catching the ball.Conclusions: Efficiency models of goalkeepers' actions should be used to create models of play for players representing a lower level of sports competence in order to improve the effectiveness of their game play. One should continue further study to improve a research tool so as to evaluate other, important from the point of view of the game's objectives, actions definitely dependent on team mates' behavior.
EN
Background: The aim of this study was to identify and compare the efficiency of action-effective football players in one against one situations (1×1).Material/Methods: The game of winning teams' players was observed in four matches and two semi-final meetings of the European Championships tournament in 2004 and 2008. Visual recording was monitored using a freeze-frame function and data about the players' game were recorded on observation sheet by Szwarc. The activity, effectiveness and reliability of individual offensive and defensive actions were estimated.Results: It was found that on average players of the best teams in Europe participated in 216 1×1 battles (from 184 to 273) in one game, with an average reliability of 52%.Conclusions: Furthermore, it was proved that players-champions engaged equally often and with the same effectiveness in both individual defensive measures and offensive actions.
EN
Background: In this work an original computer program for the video analysis of players on a large area by using a single camera is presented. Video analysis is one of the basic research techniques of human movement applied in sport. A set of cameras and special computer software is used for this purpose. Many companies provide hardware and software, but, unfortunately, their high cost and difficulty in usage are their major drawbacks. In order to simplify and reduce the costs of data analysis (obtained from a single camera), AS-4 program was developed. Material/Methods: The program includes an original algorithm which enables positioning of the camera in any place. Specifying dimensions of the playing field and an object, the program automatically calculates a scale and transfers the data to the 3D matrix. Then, using flat transformation, 3D coordinates can be determined. Results: The algorithm was tested in the field. The accuracy of determining coordinates was studied in 3 areas and errors of the method were within an acceptable range. Conclusions: With the present program, it was possible to determine the kinematic parameters at any time during the movement. The accuracy of the program was sufficient to determine the 3D position. It can be used to determine the movement path over a large area and then to calculate velocity and acceleration
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