DOI QR코드

DOI QR Code

Prediction of K-league soccer scores using bivariate Poisson distributions

이변량 포아송분포를 이용한 K-리그 골 점수의 예측

  • Received : 2014.07.25
  • Accepted : 2014.09.01
  • Published : 2014.11.30

Abstract

In this paper we choose the best model among several bivariate Poisson models on Korean soccer data. The models considered allow for correlation between the number of goals of two competing teams. We use an R package called bivpois for bivariate Poisson regression models and the data of K-league for season 1983-2012. Finally we conclude that the best fitted model supported by the AIC and BIC is the bivariate Poisson model with constant covariance. The zero and diagonal inflated models did not improve the model fit. The model can be used to examine home-away effect, goodness of fit, attack and defense parameters.

30년 동안의 K-리그 자료를 득점과 실점이 서로 상관이 있다는 가정과 R 패키지를 사용하여 12개의 서로 다른 이변량 포아송모형에 적합시켰다. 그 결과 AIC와 BIC 판정기준 아래에서 공변량 효과가 상수인 이변량 포아송모형이 가장 타당하며, 영과잉 및 대각확대 모형은 필요하지 않은 것으로 나타났다. 제안된 모형은 홈경기의 효과, 팀별 공격능력과 수비능력 및 적합도를 구하는 데 사용될 수 있다.

Keywords

References

  1. Choi, S. B., Kang, C. W., Cho, H. J. and Kang, B. Y. (2011). Social network analysis for a soccer game. Journal of the Korean Data & Information Science Society, 22, 1053-1063.
  2. Gemert, D. (2010). Modelling the scores of premier league football matches, Master's Thesis, University of Amsterdam, Amsterdam, Netherlands.
  3. Greenhough J., Birch P. C., Chapman S. C. and Rowlands G. (2002). Football goal distributions and extremal statistics. Physica A, 316, 615-624. https://doi.org/10.1016/S0378-4371(02)01030-0
  4. Hong, C. S., Jung, M. S. and Lee, J. H. (2010). Prediction model analysis of 2010 South Africa World Cup. Journal of the Korean Data & Information Science Society, 21, 1137-1146.
  5. Karlis, D. and Ntzoufras, I. (2000). On modelling soccer data. Student, 3, 229-245.
  6. Karlis, D. and Ntzoufras, I. (2003). Analysis of sports data by using bivariate Poisson models. Journal of the Royal Statistical Society D, 52, 381-393. https://doi.org/10.1111/1467-9884.00366
  7. Kim, Y. J. (2012). Statistical analysis of K-league data using Poisson model. The Korean Journal of Applied Statistics, 25, 775-783. https://doi.org/10.5351/KJAS.2012.25.5.775
  8. Lee, A. J. (1997). Modeling scores in the premier league: Is Manchester United really the best? Chance, 10, 15-19.
  9. Maher, M. J. (1982). Modelling association football scores. Statistica Neerlandica, 36, 109-118. https://doi.org/10.1111/j.1467-9574.1982.tb00782.x
  10. Moroney M. J. (1956). Facts from figures, 3rd edition, Penguin, London.
  11. Reep C., Pollard R. and Benjamin B. (1971). Skill and chance in ball games. Journal of the Royal Statistical Society A, 134, 623-629. https://doi.org/10.2307/2343657
  12. Shin, S. K., Cho, Y. J., and Cho, Y. S. (2009). A study on points per game using scored goal per game and lossed goal per game in the union of European football professional league. Journal of the Korean Data & Information Science Society, 20, 837-844.

Cited by

  1. Bivariate reliability models with multiple dynamic competing risks vol.27, pp.3, 2016, https://doi.org/10.7465/jkdi.2016.27.3.711