Profiling of Team Performances based on the Official Data in SOCCER
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Purpose: The performance analysis of sport has utilized to distinguish level of performances in past decade. Especially, the concept of identification on important factors relevant to winning and losing performances was always considered in the field of performance analysis in sports. This study was to compare different performanc-es between groups separated by frequencies of participant to soccer World Cup 2002, 2006, 2010, 2014, and 2018. This study was also intended to identify factor of distinguishing levels of performances instead of regional factor. Method: In this study, the official data from FIFA official website was collected by Microsoft Excel version 16.0 with Visual Basic Application scripts that totally 20 variables relevant to goals and features of performances were considered. After data collection has done, all data were separated by groups basing on frequencies of partici-pant to soccer World Cup. In addition, descriptive statistics and one-way ANOVA test with Turkey’s test as post hoc comparisons were utilized to compare different performances between groups. Results: As results of this study, there were significant differences found on variables relevant to goals, such as Goals, Shot attempt. Also, there were significant differences found between groups on Passes, Passes completed, Short passes, Foul sustained, % of Passes completed, % of Short passes completed and Ball possession. Those find-ings indicated different levels of performances between experiences on soccer World Cup that those variables also indicated different features of performances depending on the experiences. Conclusion: According to results of this study, the experiences on soccer World Cup are important factors to distinguish different levels of performances considering with the official data. The variables relevant to goals and different features of performances in soccer would be utilized to identify characteristics of team performances or nations regarding to the results of this study. Further researches are required that variables relating to the levels of performances distinguished in this study would be a factor of prediction models for identification of outcome of performances in soccer.
Abstract
Purpose: The performance analysis of sport has utilized to distinguish level of performances in past decade. Especially, the concept of identification on important factors relevant to winning and losing performances was always considered in the field of performance analysis in sports. This study was to compare different performanc-es between groups separated by frequencies of participant to soccer World Cup 2002, 2006, 2010, 2014, and 2018. This study was also intended to identify factor of distinguishing levels of performances instead of regional factor. Method: In this study, the official data from FIFA official website was collected by Microsoft Excel version 16.0 with Visual Basic Application scripts that totally 20 variables relevant to goals and features of performances were considered. After data collection has done, all data were separated by groups basing on frequencies of partici-pant to soccer World Cup. In addition, descriptive statistics and one-way ANOVA test with Turkey’s test as post hoc comparisons were utilized to compare different performances between groups. Results: As results of this study, there were significant differences found on variables relevant to goals, such as Goals, Shot attempt. Also, there were significant differences found between groups on Passes, Passes completed, Short passes, Foul sustained, % of Passes completed, % of Short passes completed and Ball possession. Those find-ings indicated different levels of performances between experiences on soccer World Cup that those variables also indicated different features of performances depending on the experiences. Conclusion: According to results of this study, the experiences on soccer World Cup are important factors to distinguish different levels of performances considering with the official data. The variables relevant to goals and different features of performances in soccer would be utilized to identify characteristics of team performances or nations regarding to the results of this study. Further researches are required that variables relating to the levels of performances distinguished in this study would be a factor of prediction models for identification of outcome of performances in soccer.
참고문헌 (20)
- Becker AJ, "An Investigation into the Coaching Approach of a Successful World Class Soccer Coach: Anson Dorrance", International Journal of Sports Science & Coaching, 7(3), pp.431~447 (2012)
- Hughes M, "The Use of Performance Indicators in Performance Analysis", Journal of Sports Sciences, 20, pp.739~754 (2002)
- Xuefeng Bai, "The Impacts of the Winter Olympic Games on SPORT Tourism: A Systematic Review", Kinesiology, 6(1), pp.39~47 (2021), J-INSTITUTE
- Kwack Hyun-tae, "A Narrative Study on the Preparation Period for the Performance Improvement of the Winner of TAEKWONDO Demonstration Competitions", Kinesiology, 5(1), pp.33~47 (2020), J-INSTITUTE
- 박주식, "Application of FUNCTIONAL TRAINING to Improve the Performance of Elite Judo Athletes", Kinesiology, 6(1), pp.20~29 (2021), J-INSTITUTE
- Taehun Kim, "The Comparison of MUSCLE POWER Related Main Techniques and Exercise Ability according to the Athletic Capacity of Male Middle School Handball Player", Kinesiology, 5(2), pp.70~78 (2020), J-INSTITUTE
- Park Ju-sik, "The Effect of Functional Training on the Physical Strength Factor of Elite TAEKWONDO Athletes", Kinesiology, 4(1), pp.1~7 (2019), J-INSTITUTE
- Hughes M, "Analysis of Passing Sequences, Shots and Goals in Soccer", Journal of Sports Sciences, 23(5), pp.509~514 (2005)
- 최형준, "축구 월드컵 경기 공식기록을 통한 데이터의 시각화", 한국체육측정평가학회지, 18(1), pp.83~92 (2016), 한국체육측정평가학회[DOI]
- Choi H, "The Prediction of Game Results Using ANN(Artificial Neural Networks) within the Wimbledon Tennis Championship 2005", The Korean Journal of Measurement and Evaluation in Physical Education and Sport Science, 45(3), pp.459~467 (2006)
- 최형준, "축구경기의 경기력혼란상태(PiP: Perturbation in Performances)측정방법 개발", 한국체육측정평가학회지, 16(3), pp.65~76 (2014), 한국체육측정평가학회[DOI]
- 최형준, "국내 스포츠 빅데이터 분석 연구의 현황", 한국체육측정평가학회지, 22(2), pp.63~69 (2020), 한국체육측정평가학회[DOI]
- Cottrell M, "How to Use the Kohonen Algorithm to Simultaneously Analyze Individuals and Modalities in a Survey", Neurocomputing, 63, pp.193~207 (2005)
- Kohonen T, "How to Make Large Self-organizing Maps for Nonvectorial Data", Neural Networks, 15(8-9), pp.945~952 (2002)
- Csataljay G, "Performance Indicators that Distinguish Winning and Losing Teams in Basketball", eIJPAS, 9(1), pp.60~66 (2009)
- Choi HJ, "Regional Comparisons of Teams’ Performances in the World Cup 2002 and 2006", Journal of Sports Science and Medicine, 6(10), pp.206~206 (2007)
- 최형준, "2002, 2006년 축구 월드컵 대회를 통한 경기력 분석에 관한 연구", 한국체육측정평가학회지, 11(2), pp.41~51 (2009), 한국체육측정평가학회[DOI]
- Katz L, "A Preliminary Analysis of Coaches’ Attitudes to the Use of Technology and Science in Sport" (2001), UWIC
- Kohonen T, "Self-organization and Associative Memory" (1989), Springerverlag
- Hughes M, "Establishing Normative Profiles in Performance Analysis" (2001), Routledge