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한국프로야구에서의 투수평가지표

Pitching grade index in Korean pro-baseball

  • 투고 : 2014.01.22
  • 심사 : 2014.03.12
  • 발행 : 2014.05.31

초록

투수를 평가할 때 중요한 요소는 일반적으로 다승과 방어율을 사용하지만 이 지표들은 팀의 도움 또는 운과 같은 요소의 영향을 받는다. 그래서 야구통계학자들은 투수 개인의 능력만을 측정하는 많은 지표들을 제안하였는데 이와 같은 평가지표들은 가짓수가 너무 많고 복잡하기 때문에 팬들을 때때로 당황하게 만든다. 본 연구에서는 대표적인 투수평가지표들을 이용하여 지표들의 특성을 반영하는 주성분을 찾아보고 한국프로야구에 적합한 투수들의 능력을 객관적으로 평가할 수 있는 투수지표를 제안하였다.

In baseball, the traditional measure of pitchers are wins and ERA. But these statistics are influenced by luck or team power. So sabermetrician proposes a number of indicators that predict future performance. We determine a new measure, which we call pitching grade index (PGI) that efficiently summarizes a pitcher's performance on a numerical scale using principal components analysis. The PGI statistic can often be useful to assessing a pitcher's individual contribution. Also K-means clustering algorithm are used for segmentation of players into groups.

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참고문헌

  1. Chea, J. S., Cho, E. H. and Eom, H. J. (2010). Comparisons of the outcomes of statistical models applied to the prediction of post-season entry in korean professional baseball. The Korean Journal of Measurement and Evaluation in Physical Education and Sport Science, 12, 33-48.
  2. Kim, H. J. (2012). Effects of on-base and slugging ability on run productivity in Korean professional baseball. Journal of the Korean Data & Information Science Society, 23, 1065-1074. https://doi.org/10.7465/jkdi.2012.23.6.1065
  3. Korea Baseball Organization (2001-2006). 2000-2005 official baseball guide, Korea Baseball Organization, Seoul.
  4. Korea Baseball Organization (2013). http://www.koreabaseball.com/Record.
  5. Lee, J. T. and Bang, S. Y. (2010). Forecasting attendance in the Korean professional baseball league using GARCH models. Journal of the Korean Data & Information Science Society, 21, 1041-1049.
  6. Seung, H. B. and Kang, K. H. (2012). A study on relationship between the performance of professional baseball players and annual salary. Journal of the Korean Data & Information Science Society, 23, 285-298. https://doi.org/10.7465/jkdi.2012.23.2.285

피인용 문헌

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  2. A study on prediction for attendances of Korean probaseball games using covariates vol.25, pp.6, 2014, https://doi.org/10.7465/jkdi.2014.25.6.1481
  3. Measuring the accuracy of the Pythagorean theorem in Korean pro-baseball vol.26, pp.3, 2015, https://doi.org/10.7465/jkdi.2015.26.3.653
  4. Alternative hitting ability index for KBO vol.27, pp.3, 2016, https://doi.org/10.7465/jkdi.2016.27.3.677
  5. The winning probability in Korean series of Korean professional baseball vol.27, pp.3, 2016, https://doi.org/10.7465/jkdi.2016.27.3.663
  6. 한국프로야구에서 투수 연봉에 영향을 주는 요인 vol.28, pp.2, 2014, https://doi.org/10.7465/jkdi.2017.28.2.317
  7. 한국프로야구에서 FIP 계수의 추정 vol.28, pp.3, 2014, https://doi.org/10.7465/jkdi.2017.28.3.625
  8. 2017년 한국프로야구 타자력 예측모형 개발 vol.28, pp.3, 2014, https://doi.org/10.7465/jkdi.2017.28.3.635