Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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The identification of optimal data range for the discrimination between won and lost

  • Han, Doryung (Major of Security secretary Studies Continuing Education Center, Kyonggi University) ;
  • Choi, Hyongjun (Dept. of Physical Education (Performance Analysis in Sport), Dankook University)
  • Received : 2020.07.13
  • Accepted : 2020.07.29
  • Published : 2020.07.31
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Abstract

Performance indicators have often investigated and developed in order to identify foundational elements and factors for an enhancement of performance in sports. In order to identify the valid performance indicators it is important that the indicators used within a performance analysis system discriminate between the winning and losing performances within a match (Hughes and Bartlett, 2002). However, the performance indicators proposed in research studies on basketball performance have not been used for real-time analysis and feedback within a coaching context. Such real-time support for the coach and players has been described within research on other sports (Choi et al., 2004; O'Donoghue, 2001; Palmer et al., 1997). Within the process of real-time feedback, the identification of relevant performance indicators that distinguish winning and losing performances should be the first stage of the development of a real-time analysis system. Therefore, this study investigated the differences between winning and losing teams in terms of a set of performance indicators gathered during the analysis of 10 English National Basketball League matches. Winning and losing teams were compared using whole match data (N=10) as well as individual quarters (N=40). A series of Wilcoxon Signed Ranks tests was used to identify the relevant performance indicators that discriminate between winning and losing performers within whole matches and individual quarters. The tests found that 3 point shots made (p<0.05) and Assists (p<0.05) were significantly different between winning and losing teams within matches. However, 2 point shots made (p<0.05), 2 point shots attempted (P<0.05), percentages of 2 point shots scored (p<0.05), 3 point shots made (p<0.05), Defensive Rebounds (p<0.05) and Assists (p<0.05) were significantly different between winning and losing performance within quarters. The analysis task should be based on relevant performance indicators which explain the current performances to performance analysts and coaches. Within a real-time analysis and feedback scenario, this will have the additional benefit of supporting a decision based on immediate performance within the most recent quarter. Consequently, the real-time analysis system would use performance indicators which have the property of construct validity to support the decisions of the coach.

성과를 나타내는 지표는 스포츠 성과 향상을 나타내는 기본 요소를 식별하기 위해 개발되었다. 유효한 성과 지표를 식별하려면 성과 분석 시스템 내에서 사용 된 지표가 경기 내에서 성과의 승패를 구별하는 것이 매우 중요하다고 할 수 있다. (Hughes and Bartlett, 2002). 그러나 농구 성과에 관한 연구에서는 제안된 성과와 지표는 코치 및 선수의 상황에 따라 실시간 분석 및 피드백이 사용되지 않고 있다는 점이다. 코치 및 선수에 대한 이러한 실시간 지원은 다른 스포츠에 대한 연구에서도 설명되고 있다. (Choi et al., 2004; O'Donoghue, 2001; Palmer et al., 1997). 실시간 피드백 프로세스 내에서 성과와 손실을 구분하는 관련성과 지표를 식별하는 것이 실시간 분석 시스템 개발의 첫 단계가 되어야 한다. 따라서 이 연구는 10 개의 잉글랜드 내셔널 농구 리그 경기를 분석하는 동안 수집 된 성과 지표 세트 측면에서 팀의 승패와 패배의 차이점을 조사하였다. 승리와 패배 팀은 전체 경기 데이터 (N=10)와 개별 쿼터 (N=40)를 사용하여 비교되었다. 일련의 Wilcoxon Signed Ranks 테스트를 사용하여 전체 경기와 개별 쿼터 내에서 성과를 낸 사람과 잃는 사람을 구별하는 관련성과 지표를 식별하였다. 테스트 결과 3점 (p<0.05)과 어시스트 (p<0.05)는 경기 내 팀의 승패에서 크게 차이가 있다고 할 수 있다. 그러나 2점 슛 (p <0.05), 2점 샷 시도 (P <0.05), 2 점 샷의 백분율 (p <0.05), 3 점 샷 (p <0.05), 수비 리바운드 (p <0.05) ) 및 지원 (p <0.05)은 분기 내 실적의 승패에서 크게 다르게 나타나고 있다. 위와 같은 분석 작업은 성과분석에 따라 코치에게 현재 성과를 설명하는 관련성과 지표를 기반으로 해야 한다. 실시간 분석 및 피드백 시나리오 내에서 가장 최근 분기 내에서 즉각적인 성과를 기반으로 의사 결정을 지원하는 추가 이점이 있다. 결과적으로, 실시간 분석 시스템은 코치의 결정을 뒷받침하기 위해 필요하며 유효성 특성을 갖는 성능 지표를 사용한다.

Keywords

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