The aim of the research was to analyze the goals scored in Russia World Cup 2018.The sample of this research was composed of 64 games played and 169 goals scored in the 2018 Russia World Cup. No goals were scored only in one competition. Because of 12 goals scored were own goals, 157 goals scored were analyzed on eleven different ways. The research data were collected e-analysis soccer programme. Frequency, average, standard deviation which were descriptive statistics were used for analysis of the research data.Consequently it was observed that 61,14% of goals were scored in the 2nd half of the matches and most of goals in the last 15 minutes of the matches, 63,69% of goals were scored after organized attack (open play), 38,59% of goals were scored from penalty, 78,98% of goals were scored with foot shot, 72,61% of goals were scored with one touch, 84,71% of the goals were scored through the penalty zone and 60,50% of the goals were scored in 3rd zone which was determined in the penalty zone. Moreover, of the teams that scored first results showed that they won 71,42% of the matches. Scorer’s playing position was 32,48% striker. Asist player’s playing position was 44,03% midfielder. 11,92% of asist were passed from 9th zone which was determined outside the penalty zone.The work guided the coaches to design real competition-like trainings and tailor the game style to the match situation. Coaches can also use this information to set goals for players and teams that specifically refer to offense and defense games. It is advisable to coach to use the 3rd zone set in the penalty zone for more goals and to use the 3rd zone in the penalty zone for more effective defense for fewer goals.
Complex networks often display network motifs and these can be described as subgraphs. Methods for analyzing complex networks promise to be of great benefit to almost all scientific disciplines including sports. In football if we want to disrupt the opponent's game format, we must first be aware of the pass motifs that the team often uses. Determining how to break these motifs will make an important contribution to the success of a team. In this study, 3-nodes and 4-nodes pass motifs of the teams were examined within the frame of a data set of ten games and the most frequent repetitions of these motifs were determined. In addition, we suggest that in a match, the balance can be measured by the correlation between the frequencies of the motif types and there may be an inverse relationship between this correlation and the difference in the goals of the match.
Background and Study Aim. The aim of this research is to (i) examine the COVID-19 fear scales according to the contact rate of the sports branch of the athletes and (ii) examine the COVID-19 fear scales according to some demographic variables of the athletes. Material and Methods. Sport Sciences Faculty students athletes (n=176) in sports with different levels of contact voluntarily participated in the current study. The fear of COVID-19 scale consisting of a total of 7 items and demographic information form and a single sub-dimension were applied online via Google® forms to individuals who participated in the study voluntarily. The data obtained from the study were analyzed using IBM SPSS 25.0 statistics package program. Due to the normal distribution of the data, sample t-test independent of parametric tests and one-way analysis of variance tests were used in the statistical analysis of the data. Bonferroni test, one of the multiple comparison tests, was used in order to determine which groups had significance according to the results of the one-way analysis of variance test. The results were tested at a significance level of p <0.05. The Cronbach Alpha reliability coefficient for the COVID-19 fear scale was found to be 0.88. Results. Statistically significant difference was found between the fears of catching COVID-19 according to the gender of athletes in different branches (p = 0.01). No statistically significant difference was found between the fears of catching COVID-19 according to the educational status of the athletes (p = 0.31). No statistically significant difference found between the fears of catching COVID-19 according to the contact included in the specialty sports of the athletes in different branches (p = 0.56). Statistically significant difference was found between the highest level (professional) and intermediate level (amateur) groups ) in terms of fear of catching COVID-19 (p = 0.02). No statistically significant difference found between the fears of catching COVID-19 (p = 0.08) of the athletes in different branches according to their sports experience. Statistically significant difference was found in terms of fear of catching COVID-19 between the 4-6 years and 7-9 years groups with sports experience (p = 0.02). In addition, it has been revealed that the average scores of COVID-19 fear scales (20.05 ± 4.79) of female athletes are higher than the average scores of male athletes (17.67 ± 6.75).Conclusions. As a result, this research has revealed that the fear of COVID-19 does not differ relative to the contact levels of a specific sports branch. In addition, it has shown that the fear of COVID-19 is greater in female athletes compared to male athletes and lower performance levels and less competition experiences are in fact causing an increase in fear of COVID-19.
Economics is a science that examines how people use scarce
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.