Critical Reviews of NBA Official Data based on Sport Analytics
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Purpose: This study was to identify and to recognize the critical moment of NBA official data using sport analytics techniques. Previous studies have already had the research area on the basketball that the sport science was to be applied into enhancing of performance in the practice. The official data was recently considered in many researchers that the official data has been gathered by scientific methods such as advanced technologies. Current trend of performance analysis of sport intends to extent the data range that the official data could be gathered from the official website and it would be a massive dataset. Method: The sport analytics techniques using big data analysis were utilized that the NBA official data from 2015-2016 to 2020-2021 seasons contained more than 3,040,000 events. The Python scripts to gather the NBA official data were utilized and the gathered data as csv format. All analysis of data was executed within R studio with R programming that the changes of numbers of events between seasons and successful rate of each events were compared in this study. Statistically, the frequency analysis was used for the determination of data. Results: This study was to recognize the critical moment among the NBA official data that there were two find-ings mainly. First of all, frequencies of events on 2-pt jump shots have been decreasing and frequencies of events on 3-pt jump shots have been increasing between season. Particularly, the short-distance shots such as 2-pt tip-in, 2-pt layup, 2-pt jump shots were more presented in each season than the long-distance shots. Secondly, the successful rate of shots and outcomes between season have not been differently presented. Conclusion: Consequently, this study has found the displacement of critical changes within the official NBA data that it could indicate the originality of basketball match rather than characteristics of playing. It is also important that the playing trend would be differently observed when the skill or players’ style was able to be consid-ered. Further research is also required that the critical point of recording change on the sequencies of time line would need to be concerned.
Abstract
Purpose: This study was to identify and to recognize the critical moment of NBA official data using sport analytics techniques. Previous studies have already had the research area on the basketball that the sport science was to be applied into enhancing of performance in the practice. The official data was recently considered in many researchers that the official data has been gathered by scientific methods such as advanced technologies. Current trend of performance analysis of sport intends to extent the data range that the official data could be gathered from the official website and it would be a massive dataset. Method: The sport analytics techniques using big data analysis were utilized that the NBA official data from 2015-2016 to 2020-2021 seasons contained more than 3,040,000 events. The Python scripts to gather the NBA official data were utilized and the gathered data as csv format. All analysis of data was executed within R studio with R programming that the changes of numbers of events between seasons and successful rate of each events were compared in this study. Statistically, the frequency analysis was used for the determination of data. Results: This study was to recognize the critical moment among the NBA official data that there were two find-ings mainly. First of all, frequencies of events on 2-pt jump shots have been decreasing and frequencies of events on 3-pt jump shots have been increasing between season. Particularly, the short-distance shots such as 2-pt tip-in, 2-pt layup, 2-pt jump shots were more presented in each season than the long-distance shots. Secondly, the successful rate of shots and outcomes between season have not been differently presented. Conclusion: Consequently, this study has found the displacement of critical changes within the official NBA data that it could indicate the originality of basketball match rather than characteristics of playing. It is also important that the playing trend would be differently observed when the skill or players’ style was able to be consid-ered. Further research is also required that the critical point of recording change on the sequencies of time line would need to be concerned.
참고문헌 (23)
- Novak I, "Evidence to Practice Commentary New Evidence in Coaching Interventions", Physical and Occupational Therapy in Pediatrics, 34(2), pp.132~137 (2014)
- Xuefeng Bai, "The Impacts of the Winter Olympic Games on SPORT Tourism: A Systematic Review", Kinesiology, 6(1), pp.39~47 (2021), J-INSTITUTE
- 박주식, "Application of FUNCTIONAL TRAINING to Improve the Performance of Elite Judo Athletes", Kinesiology, 6(1), pp.20~29 (2021), J-INSTITUTE
- Chiyoung Lee, "An Analysis of the Utilization of Offensive and Defensive Techniques According to the JUDO Athlete's Career", Kinesiology, 6(3), pp.60~71 (2021), J-INSTITUTE
- Rein R, "Future Challenges and Opportunities for Sports Science", Springer Plus, 5, pp.n1410~ (2016)
- Franks I, "Soccer Analytics" (2016), Meyer & Meyer Sport
- Eaves S. J, "A History of Sports Notational Analysis : A Journey into the Nineteenth Century", International Journal of Performance Analysis of Sport, 15(3), pp.1160~1176 (2015)
- Winter C, "Tactical Metrics that Discriminate Winning, Drawing and Losing Teams in UEFA Euro 2012", Journal of Sports Science, 34(6), pp.486~492 (2016)
- Korte F, "Passing Network Analysis of Positional Attack Formations in Handball", Journal of Human Kinetics, 70(1), pp.209~221 (2019)
- Forsman H, "Identifying Technical, Physiological, Tactical and Psychological Characteristics that Contribute to Career Progression in Soccer", International Journal of Sport Science in Coaching, 11(4), pp.505~513 (2016)
- 최형준, "자기구성지도를 이용한 테니스 ATP 공식기록 기반 연도, 그랜드슬램 여부, 토너먼트의 분류: 1991-2017년 자료를 중심으로", 한국체육학회지, 58(5), pp.263~272 (2019), 한국체육학회[DOI]
- 최형준, "2002, 2006년 축구 월드컵 대회를 통한 경기력 분석에 관한 연구", 한국체육측정평가학회지, 11(2), pp.41~51 (2009), 한국체육측정평가학회[DOI]
- 최형준, "축구 월드컵 경기 공식기록을 통한 데이터의 시각화", 한국체육측정평가학회지, 18(1), pp.83~92 (2016), 한국체육측정평가학회[DOI]
- Havard C, "Basketball at the Most Magical Place on Earth: A Case Study of the NBA’s Season Conclusion at Walt Disney World Amid the Covid-19 Pandemic" (2021), Sage Business Cases Originals
- Raiola G, "Physical and Sports Activity during the Covid-19 pandemic", Journal of Physical Education and Sport, 21(1), pp.477~482 (2021)
- Sarlis V, "Sports Analytics-Evaluation of Basketball Players and Team Performance", Information System, 93, pp.1~19 (2020)
- Courel-Ibáñez J, "Inside Game Effectiveness in NBA Basketball : Analysis of Collective Interactions", Kinesiology, 50(2), pp.1~10 (2018)
- Richardson CA, "Evolution of a Player: Transitions in NBA Player Classifications", SSRN Electronic Journal, pp.n3515711~ (2020)
- 저우차우, "2019 세계 남자 농구 월드컵 경기대회의 공식기록에 기반한 경기내용에 관한 군집 분석", 한국체육학회지, 59(3), pp.397~411 (2020), 한국체육학회[DOI]
- Bhandari I, "Advanced Scout : Data Mining and Knowledge Discovery in NBA Data", Data Mining and Knowledge Discovery, 1(1), pp.121~125 (1997)
- McFarlane P, "Evaluating NBA End-of-game Decision-making", Journal of Sports Analytics, 5(1), pp.17~22 (2018)
- Process P, "Report Information from Proquest", European Physical Education Review, 8(3), pp.191~204 (2014)
- Sheng L, "Application Status and Development Prospect of Big Data in Chinese Sports Field", International Conference on Communications, Information System, and Computer Engineering (2019)