ࡱ> 5@+bjbj22XX'%>>>8v<$:"9999999$;R=9]S@9OK: 9 9  23 8F>T2l4\a:0:2> d>(34">3( E<x99$> >MATCH PERFORMANCE EVALUATION MODEL OF A FOOTBALL TEAM DURING A FOOTBALL MATCH Kreaimir `oa1, Romeo Jozak1 and Vlatko Vu eti2 1Goal Academy, Munich, Germany; 2Faculty of Kinesiology, University of Zagreb, Croatia Abstract This paper presents the evaluation model for the match performance of the players and preparatory effects. Examinees were 4 promising midfield players of the football team NK Dinamo's B team, all 18(1 years of age. Parameters of match performance have been described as quantities of run distances (low, moderate and high speed, and overall) and as time spent in each of the 4 energy zones measured by heart rate monitors. The examinees were observed during two football matches, in the preparatory and competitive part of the season. The analysis data have pointed to significant differences in run distances, whereas there were no significant differences in durations of energy zones. This points to an improvement of the players' competitive fitness. The model proved to be simple and efficient for evaluating match performance and as such is used in the football practice. Key words: football, match analysis, match fitness, preparatory effects Introduction The demands that a football match makes on the players are a combination of energy and information component, i.e. they are mostly physiological and psychological in nature. (Bompa, 2000). The energy component is predominantly a part of all technical and tactic elements of the game (e.g. running at different speeds, contact play, jumps, groundings and liftings etc.). A good competitive effect is often the result of carefully planned and conducted trainings, especially in the preparatory part of the season. The aim of each preparation is to bring about adaptation processes, by which fitness reaches its peak in the competitive part of the season by supercompensation. (Bompa, 2000). The primary goal of the research is to present the model as one of the possibilities of match performance evaluation, and the secondary goal is to give insight into the preparatory effects. The indicators of the states used in order to evaluate match performance are: distances run at different intensities and the strain that running represented to the players, presented as heart rates (Vu eti et al., 2002). Methods Examinee sample Examinee samples are 4 promising players of the NK Dinamo's B team. The players have played in the 4:4:2 system, on the positions of midfield players, which were mostly under greatest energy strain, in the sense of sprinting during a match (Bangsbo, 1994). Descriptive parameters of the basic morphological characteristics are shown in table 1. Table 1. Average values of examinees' morphological characteristics Descriptive StatisticsN=4MeanSDAGE181,0HEIGHT175,88,8WEIGHT65,96,1%BF8,23,2Body Fat was measured by the method of bioelectric impendancy (Omron BF302) and is expressed as a percentage of the overall body fat (%BF), Mean and Standard Deviation (SD). Variables sample Indicators of the match performance are shown as parameters of quantity of running at different intensities i.e. different speeds: L1,2 = running at low speeds (m) S1,2 = running at moderate speeds (m) B1,2 = fast and maximally fast running (m) UK1,2 = overall quantity of running (m) Parameters of physiological strain, distances run during a match, have been estimated by heart rates. Based on obtained data, durations of each energy zone have been calculated, and the result in variables has been expressed as percentage of time spent in each energy zone in comparison to the overall time. The zones described by heart rates have been determined by a spiroergometric testing in the Sports diagnostic centre within the Faculty of Kinesiology, University of Zagreb. Z11,2 = aerobe regeneration zone (%) Z21,2 = aerobe extensive zone (%) Z31,2 = aerobe intensive zone (%) Z41,2 = anaerobe zone maximal oxygen intake zone (%) Experiment realization procedure The same players were monitored and their performance measured during two matches. The first match was played at the beginning of the preparation period of the autumn season 2003/2004, and the other at the beginning of the competitive period of the season, i.e. after 2 months. Graph 2. Graphic representation of the heart frequency movement of one player during the match  Graph 3. Graphic representation of the heart frequency distribution according to zones of one of the examinees  Legend in the text Heart frequencies of the football players during the match were monitored by Polar Team System heart rate monitors (Graph 2.) and analysed by the programme Polar PPP 4.0 (Graph 3.). The data on distances run by players were obtained through observations done by the students of the Faculty of Kinesiology, specially trained for this purpose. Each student monitored 1 player and entered the estimated length of section and the running speed into the list. After that, the values were added up for each of the three intensities and overall. Methods of data analysis Based on the obtained data, basic descriptive parameters (mean) and standard deviations (SD) have been calculated, and the analysis of differences between the first and the second match in the monitored variables has been done by Student's t-test for dependant samples. The data have been statistically processed by the programme package Statistics for Windows 5.0 at the Faculty of Kinesiology of the University in Zagreb. Results The parameters used to evaluate match performance (quantity of running) have yielded statistically significant differences (p<0,05, Table 4.) between the first and the second match. Table 4. Results of t-test analysis for dependant samples based on variables from two matches (index 1 and 2) T-test for Dependent Samples*Marked differences are significant at p < 0,05N=4MeanSDtdfpL1206573L22469277-3,398*30,0425S183555S21306218-4,366*30,0222B143579B2611156-4,278*30,0235UK13335121UK24386513-5,103*30,0146Z111,92,3Z121,01,62,11130,1251Z2116,99,8Z2212,17,32,12030,1241Z3147,725,1Z3243,823,61,23130,3059Z4133,836,0Z4243,230,8-1,92830,1495Mean, Standard Deviation (SD), t-test results (t), degrees of freedom (df), error size (p) The differences in indicators of strain (percentage of time spent in the zones) aren't statistically significant (p>0,05). The players on average ran more during the second than the first match, in all three intensities (L, S, B) and overall (UK). The greatest differences have been noted in the quantities of running at moderate intensity and overall. The players have, on average, spent more time in the maximal oxygen intake zone (Z4) during the second game. Correspondingly, they spent on average a smaller percentage of time in the zones Z3, Z2 and Z1. Despite the differences in average values of percentage of time spent in each zone, they are statistically insignificant (p>0,05) although it can be said that there is a tendency towards it (Table 4.). Discussion Four midfield players of the young NK Dinamo team ran, on average, more at the three intensities (L, S and B) and overall (UK) during the second match in the autumn part of the season 2003/2004. As this difference is statistically significant, we can assume that the same is true for the team. Larger amount of running requires higher energy consumption, and therefore the data that the players have spent more time in the maximal oxygen intake zone (Z4), and less in the zones Z3, Z2 and Z1, is not surprising. Nevertheless, although these differences are statistically insignificant (p>0,05) they show a tendency. We can assume that the young players of the NK Dinamo team played more effectively in the second match in the autumn part of the season 2003/2004. In other words, the players ran considerably more during the second match (during the competitive part of the season) with insignificantly higher energy consumption than in the first match (during preparatory part of the season). The conclusion points to an improvement of competitive fitness, which confirms that the aim of condition part of preparations has been achieved. This model of evaluation of energy effects and demands during a match has proven to be very useful and relatively simple for practical use. By testing particular functional abilities of the players it is also possible to evaluate the effects of trainings conducted during preparatory part of the season. However, the presented model includes an integration of the ultimate energy and technical-tactical aim, with the prerequisite that they offer a bigger possibility of success during a football match. We believe that this or similar approach to monitoring players' match performance can considerably contribute to the raising of the footballs' quality. References 1. Billows, D., T. Reilly and K. George (2003). Physiological demands of matchplay on elite adolescent footballers. World Congress on Science and Football-5 (p. 159). Lisbon: Faculty of Human Kinetics, Technical University of Lisbon, Portugal 2. Bangsbo, J. (1994). Fitness Training in Football a Scientific Approach. DBU. Copenhagen: August Krogh Institute, University of Copenhagen, Denmark 3. Bompa, T. (2000). Periodization: Theory and Methodology of Training. Human Kinetics. Illinois: York University, USA 4. Miyagi, O. and J. Ohashi (2003). Energy expenditure and movement distance during a game of U-15 soccer players in Japan.World Congress on Science and Football-5 (p.305). Lisbon: Faculty of Human Kinetics, Technical University of Lisbon, Portugal 5. Vu eti, V., D. `entija and B. Matkovi (2002). 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