[1] A.A. Abbasi and M. Younis, A survey on clustering algorithms for wireless sensor networks, Comput. Commun. 30 (2007), no. 14-15, 2826–2841.
[2] M.R. Abdullah, R.M. Musa, A.B.H.M.B. Maliki, N.A. Kosni, and P.K. Suppiah, Role of psychological factors on the performance of elite soccer players, J. Phys. Educ. Sport 16 (2016), no. 1, 170.
[3] C.C. Aggarwal, Data classification: algorithms and applications, CRC Press, 2014.
[4] F. Amadin and J.C. Obi, English premier league (epl) soccer matches prediction using an adaptive neuro-fuzzy inference system (anfis), Trans. Machine Learn. Artif. Intel. 3 (2015), no. 2, 34.
[5] W. Andreff and N. Scelles, Walter c. neale 50 years after:beyond competitive balance, the league standing effect tested with french football data, J. Sports Econ. 16 (2015), no. 8, 819–834.
[6] S.M. Arabzad, M.E. Tayebi Araghi, S. Sadi-Nezhad, and N. Ghofrani, Football match results prediction using artificial neural networks; the case of iran pro league, J. Appl. Res. Ind. Engin. 1 (2014), no. 3, 159–179.
[7] R. Baboota and H. Kaur, Predictive analysis and modelling football results using machine learning approach for english premier league, Int. J. Forecast. 35 (2019), no. 2, 741–755.
[8] G. Baio and M. Blangiardo, Bayesian hierarchical model for the prediction of football results, J. Appl. Statist. 37 (2010), no. 2, 253–264.
[9] G. Boshnakov, T. Kharrat, and I.G. McHale, A bivariate weibull count model for forecasting association football scores, Int. J. Forecast. 33 (2017), no. 2, 458–466.
[10] E.J. Cand`es, X. Li, Y. Ma, and J. Wright, Robust principal component analysis?, J. ACM (JACM) 58 (2011), no. 3, 11.
[11] A. Caraffa, G. Cerulli, M. Projetti, G. Aisa, and A. Rizzo, Prevention of anterior cruciate ligament injuries in soccer, Knee Surgery Sports Traumatol. Arthros. 4 (1996), no. 1, 19–21.
[12] A. Cortez, A. Trigo, and N. Loureiro, Predicting physiological variables of players that make a winning football team: A machine learning approach, Int. Conf. Comput. Sci. Appl., Springer, 2021, pp. 3–15.
[13] E. Costa, A. Lorena, A.C.P.L.F. Carvalho, and title = A review of performance evaluation measures for hierarchical classifiers booktitle = Evaluation Methods for Machine Learning II: papers from the AAAI-2007 Workshop pages = 1-6 type = Conference Proceedings Freitas, A.
[14] A. Decrop and C. Derbaix, Pride in contemporary sport consumption: A marketing perspective, J. Acad. Market. Sci. 38 (2010), no. 5, 586–603.
[15] M.J. Dixon and S.G. Coles, Modelling association football scores and inefficiencies in the football betting market, J. Royal Statist. Soc.: Ser. C (Applied Statistics) 46 (1997), no. 2, 265–280.
[16] M.J. Dixon and P.F. Pope, The value of statistical forecasts in the uk association football betting market, Int. J. Forecast. 20 (2004), no. 4, 697–711.
[17] Engin Esme and M.S. Kiran, Prediction of football match outcomes based on bookmaker odds by using k-nearest neighbor algorithm, Int. J. Machine Learn. Comput. 8 (2018), no. 1, 26–32.
[18] C.W. Fuller, J. Ekstrand, A. Junge, T.E. Andersen, R. Bahr, J. Dvorak, M. H¨agglund, P. McCrory, and W.H. Meeuwisse, Consensus statement on injury definitions and data collection procedures in studies of football (soccer) injuries, Scand. J. Med. Sci. Sports 16 (2006), no. 2, 83–92.
[19] J. Goddard, Regression models for forecasting goals and match results in association football, Int. J. Forecast. 21 (2005), no. 2, 331–340.