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Original Articles

Discovering the Drivers of Football Match Outcomes with Data Mining

, , &
Pages 561-577 | Received 01 Jan 2014, Accepted 01 May 2014, Published online: 09 Feb 2016

References

  • Agresti, A. (2003). Logit models for multinomial responses. In: Categorical Data Analysis, 2nd edition. John Wiley & Sons, Hoboken, NJ.
  • Albert, J., Bennet, J. and Cochran, J. J. (2005). Anthology of Statistics in Sport, ASA-SIAM Series in Statistics andProbablity, SIAM, Philadelphia, ASA, Alexandria.
  • Albert, J., Koning, R. H. (2008). Statistical Thinking in Sports. Chapman & Hall, Boca Raton.
  • Breiman, L., Friedman, J. H., Olshen, R. A. and Stone, C. J. (1984). Classification and Regression Trees. Chapman & Hall, New York.
  • Breiman, L. (1996). Bagging predictors, Machine Learning, 24, 123–140.
  • Breiman, L. (2001). Random forests, Machine Learning, 45(1), 5–32.
  • Breiman, L. (2002). Manual on Setting up, Using, and Understanding Random Forests v3.1. Technical report. http://oz.berkeley.edu/users/breiman/Using_random_forests_V3.Lpdf.
  • Buraimo, B., Forrest, D. and Simmons, R. (2010). The 12th man?: refereeing bias in English and German soccer. Journal of the Royal Statistical Society Series A, Royal Statistical Society, 173(2), 431–449.
  • Calle, M. L. and Urrea, V. (2010). Letter to the editor: stability of random forest importance measures. Briefings in Bioinformatics, 12(1), 86–89.
  • Carpita, M., Sandri, M., Simonetto, A. and Zuccolotto, P. (2013). Football mining with R. in: Data Mining Applications with R (Edited by Y. Zhao, Y. Cen), Chapter 14. Elsevier.
  • Carroll, B., Palmer, P. and Thorn, J. (1988). The Hidden Game of Football. Warner Books, New York.
  • Dohmen, T. (2008). The influence of social forces: evidence from the behavior of football referees. Economic Inquiry, 46, 411–424.
  • Garicano, L., Palacios-Huerta, I. and Prendergast, C. (2005). Favoritism under social pressure. Review of Economics and Statistics, 87, 208–216.
  • Han, J., Kamber, M. and Pei, J. (2011). Data Mining: Concepts and Techniques, 3rd edition. The Morgan Kaufmann Publishers, San Francisco.
  • Hand, D. J., Mannila, H. and Smyth, P. (2001). Principles of Data Mining: Adaptive Computation and Machine Learning. MIT Press, Cambridge.
  • Hastie, T., Tibshirani, R., and Friedman, J. H. (2001). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer, New York.
  • Hopkins, W. G. (2012). The impact-factor Olympics for journals in sport and exercise science and medicine. Sportscience, 16, 17–19, http://sportsci.org/2012/wghif.htm.
  • Hotelling, H. (1933). Analysis of a complex of statistical variables into principal components. Journal of Educational Psychology, 24, 417–441, 498–520.
  • Jolliffe, I. T. (2002). Principal Component Analysis. Springer Verlag, New York.
  • Karlis, D. and Ntzoufras, I. (2003). Analysis of sports data by using bivariate Poisson models. Statistician, 52, 381–393.
  • Koopman, S. J. and Lit, R. (2014). A dynamic bivariate Poisson model for analysing and forecasting match results in the English premier league. Journal of the Royal Statistical Society: Series A (Statistics in Society), early view: DOI: 10.1111/rssa.12042.
  • Kuper, S. (2011). A football revolution. Financial Times Magazine, June 17, 2011, http://gilesrevell.com/files/championsleague.pdf.
  • Liaw, A. and Wiener, M. (2002). Classification and regression by random forest. R News, 2 (3), 18–22.
  • Lucey, B. and Power, D. (2004). Do soccer referees display home team favouritism? Mimeo. Trinity College Dubli, Dublin.
  • Maher, M. J. (1982) Modelling association football scores. Statistics Netherlands, 36, 109–118.
  • McHale, I. G. and Szczepanski, L. (2014). A mixed effects model for identifying goal scoring ability of footballers. Journal of the Royal Statistical Society: Series A (Statistics in Society), 177, 397–417.
  • Min, B., Kim, J., Choe, C., Eom, H. and McKay, R. I. (2008). A compound framework for sports results prediction: a football case study. Knowledge-Based Systems, 21, 551–562.
  • Nicodemus, K. K. (2011). Letter to the editor: on the stability and ranking of predictors from random forest variable importance measures. Briefings in Bioinformatics, 12(4), 369–373.
  • Pearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine, Series 6, 2(11), 559–572.
  • Pollard, R. and Reep, C. (1997). Measuring the effectiveness of playing strategies at soccer. The Statistician, 46(4), 541–550.
  • Rickman, N. and Witt, R. (2008). Favouritism and financial incentives: a natural experiment. Economica, 75, 296–309.
  • Rue, H. and Salvesen, O. (2000). Prediction and retrospective analysis of soccer matches in a league. The Statistician, 49(3), 399–418.
  • Sandri, M. and Zuccolotto, P. (2008). A bias correction algorithm for the gini variable importance measure in classification trees. Journal of Computational and Graphical Statistics, 17(3), 611–628.
  • Sandri, M. and Zuccolotto, P. (2010). Analysis and correction of bias in total decrease in node impurity measures for tree-based algorithms. Statistics and Computing, 20, 393–407.
  • Scoppa, V. (2008). Are subjective evaluations biased by social factors or connections? An econometric analysis of soccer referee decisions. Empirical Economics, 35, 123–140.
  • Slaton, Z. (2012). A Beautiful Numbers Game — Statistically informed soccer writing. http://www.abeautifulnumbersgame.com.
  • Stern, H. (2005). Introduction to the football articles. In Anthology of Statistics in Sport (Edited by Albert, J., Bennet, J., Cochran, J. J.), ASA-SIAM Series in Statistics and Probability, SIAM, Philadelphia, ASA, Alexandria.
  • Strobl, C., Boulesteix, A. L., Zeileis, A. and Hothorn, T. (2007). Bias in random forest variable importance measures: illustrations, sources and a solution. BMC Bioinformatics, 8–25.
  • Sutter, M. and Kocher, M. (2004). Favouritism of agents — the case of referees’ home bias. Journal of Economic Psychology, 25, 461–469.
  • Van Dijkhuizen, A. (2012). Soccernomics 2012 — Euro Football Poland/Ukraine, http://www.abnamromarkets.be/fileadmin/user_upload/TA/2012/120529_-_Soccernomics_2012_ENG.pdf.

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