Journal of the Korean Data and Information Science Society

한국데이터정보과학회 (The Korean Data and Information Science Society)
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한국남자프로농구 경기기록 분석을 통한 승패결정요인 추정: 2010-2011시즌, 2011-2012시즌 정규리그 기록 적용

Estimating the determinants of victory and defeat through analyzing records of Korean pro-basketball

  • 김세형 (한국체육대학교 체육측정평가실) ;
  • 이준우 (호서대학교 기초과학연구소) ;
  • 이미숙 (한국체육대학교 사회체육학과)
  • Kim, Sae-Hyung (Lab of Measurement and Evaluation in Physical Education, Korea National Sport University) ;
  • Lee, Jun-Woo (Basic Science Institute, Hoseo University) ;
  • Lee, Mi-Sook (School of Community Sport, Korea National Sport University)
  • 투고 : 2012.08.31
  • 심사 : 2012.09.23
  • 발행 : 2012.09.30
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초록

한국남자프로농구 경기기록을 이용하여 승패결정요인을 분석하였다. 2010년 10월부터 2011년 3월까지, 2011년 10월부터 2012년 3월까지 치러진 정규리그 (540경기)의 기록을 분석하여 승패결정요인을 추정하였다. 한국농구연맹은 7개 공격변인과 7개 수비변인에 대한 자료를 제공하고 있다. 이들 자료 중에 공헌도와 공격력에 적용되는 6개 공격변인 (2점슛 성공률, 3점슛 성공률, 자유투 성공률, 공격리바운드, 어시스트, 턴오버)과 4개 수비변인 (수비리바운드, 스틸, 굿디펜스, 블록슛)이 승패에 미치는 영향을 통계적으로 분석하기 위해 로지스틱회귀분석과 의사결정나무분석을 적용하였다. 두 분석은 PASW와 Answer Tree 통계프로그램을 사용하였으며 모든 유의수준은 .05로 설정하였다. 로지스틱회귀분석 결과, 6개 공격변인 중 2점슛 성공률, 3점슛 성공률, 턴오버가 통계적으로 승패에 유의미한 영향을 미치고 4개 수비변인 중 굿디펜스를 제외한 수비리바운드, 스틸, 블록슛이 통계적으로 승패에 유의미한 영향을 미치는 것으로 나타났다. 그리고 공격변인 의사결정나무분석 결과에서는 2점슛 성공률이 51%-58%이며, 3P%가 31%를 초과하고 TO가 11개 이하일때 승리할 수 있는 확률이 80.85%로 가장 높게 나타났다. 이에 반해 수비변인 의사결정나무분석 결과, 수비리바운드가 24개를 초과하고 스틸이 6개를 초과하며, 블록슛이 2개를 초과할 때 승리할 수 있는 확률이 94.12%로 가장 높게 나타났다.

The purpose of this study was to estimate the determinants of victory and defeat through analyzing records of Korean men pro-basketball. Statistical models of victory and defeat were established by collecting present basketball records (2010-2011, 2011-2012 season). Korea Basketball League (KBL) informs records of every pro-basketball game data. The six offence variables (2P%, 3P%, FT%, OR, AS, TO), and the four defense variables (DR, ST, GD, BS) were used in this study. PASW program was used for logistic regression and Answer Tree program was used for the decision tree. All significance levels were set at .05. Major results were as follows. In the logistic regression, 2P%, 3P%, and TO were three offense variables significantly affecting victory and defeat, and DR, ST, and BS were three significant defense variables. Offensive variables 2P%, 3P%, TO, and AS are used in constructing the decision tree. The highest percentage of victory was 80.85% when 2P% was in 51%-58%, 3P% was more than 31 percent, and TO was less than 11 times. In the decision tree of the defence variables, the highest percentage of victory was 94.12% when DR was more than 24, ST was more than six, and BS was more than two times.

키워드

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  2. Analyzing records of Korean pro-basketball using general linear model vol.26, pp.4, 2015, https://doi.org/10.7465/jkdi.2015.26.4.957
  3. Winning Factors: How Players' Positional Offensive and Defensive Skills Affect Probability of Victory in the Korea Basketball League vol.10, pp.2-3, 2015, https://doi.org/10.1260/1747-9541.10.2-3.453
  4. An exploration of tour skill factors influential to game results of LPGA players vol.24, pp.2, 2013, https://doi.org/10.7465/jkdi.2013.24.2.369
  5. 게임 데이터를 이용한 지표 개발과 승패예측모형 설계 vol.28, pp.2, 2012, https://doi.org/10.7465/jkdi.2017.28.2.237
  6. Factors Contributing to Winning in Ice Hockey: Analysis of 2017 Ice Hockey World Championship vol.57, pp.4, 2012, https://doi.org/10.23949/kjpe.2018.07.57.4.27