pi-football: A Bayesian network model for forecasting Association Football match outcomes

Baio, 2010, Bayesian hierarchical model for the prediction of football results, Journal of Applied Statistics, 37, 253, 10.1080/02664760802684177

Cain, 2000, The favourite-loghshot bias and market efficiency in UK football betting, Scottish Journal of Political Economy, 47, 25, 10.1111/1467-9485.00151

Constantinou, 2012, Solving the problem of inadequate scoring rules for assessing probabilistic football forecast models, Journal of Quantitative Analysis in Sports, 8, 10.1515/1559-0410.1418

Crowder, 2002, Dynamic modelling and prediction of English football league matches for betting, The Statistician, 51, 157, 10.1111/1467-9884.00308

Dixon, 1997, Modelling association football scores and inefficienies in the football betting market, Applied Statistics, 46, 265, 10.1111/1467-9876.00065

Dixon, 2004, The value of statistical forecasts in the UK association football betting market, International Journal of Forecasting, 20, 697, 10.1016/j.ijforecast.2003.12.007

Falter, 2000, Demand for football and intra-match winning probability: an essay on the glorious uncertainty of sports, Applied Economics, 32, 1757, 10.1080/000368400421101

Fenton, 2007, Using ranked nodes to model qualitative judgments in Bayesian networks, IEEE TKDE, 19, 1420

Forrest, 2000, Forecasting sport: the behaviour and performance of football tipsters, International Journal of Forecasting, 16, 317, 10.1016/S0169-2070(00)00050-9

Forrest, 2002, Outcome uncertainty and attendance demand in sport: the case of English soccer, The Statistician, 2, 241

Forrest, 2008, Sentiment in the betting market on Spanish football, Applied Economics, 40, 119, 10.1080/00036840701522895

Forrest, 2005, Odds-setters as forecasters: the case of English football, International Journal of Forecasting, 21, 551, 10.1016/j.ijforecast.2005.03.003

Goddard, 2005, Regression models for forecasting goals and match results in association football, International Journal of Forecasting, 21, 331, 10.1016/j.ijforecast.2004.08.002

Goddard, 2004, Forecasting football results and the efficiency of fixed-odds betting, Journal of Forecasting, 23, 51, 10.1002/for.877

Graham, 2008, Predicting bookmaker odds and efficiency for UK football, Applied Economics, 40, 99, 10.1080/00036840701728799

Halicioglu, 2005, Can we predict the outcome of the international football tournaments?: the case of Euro 2000, Doğuş Üniversitesi Dergisi, 6, 112, 10.31671/dogus.2019.288

F. Halicioglu, Forecasting the professional team sporting events: evidence from Euro 2000 and 2004 football tournaments, in: 5th International Conference on Sports and Culture: Economic, Management and Marketing Aspects, Athens, Greece, 2005, pp. 30–31.

Hirotsu, 2003, An evaluation of characteristics of teams in association football by using a Markov process model, The Statistician, 52, 591, 10.1046/j.0039-0526.2003.00437.x

Hvattum, 2010, Using ELO ratings for match result prediction in association football, International Journal of Forecasting, 26, 460, 10.1016/j.ijforecast.2009.10.002

Joseph, 2006, Predicting football results using Bayesian nets and other machine learning techniques, Knowledge-Based Systems, 7, 544, 10.1016/j.knosys.2006.04.011

Karlis, 2003, Analysis of sports data by using bivariate Poisson models, The Statistician, 52, 381, 10.1111/1467-9884.00366

Knorr-Held, 2000, Dynamic rating of sports teams, The Statistician, 49, 261, 10.1111/1467-9884.00236

Koning, 2000, Balance in competition in Dutch soccer, The Statistician, 49, 419, 10.1111/1467-9884.00244

Koning, 2003, A simulation model for football championships, European Journal of Operational Research, 148, 268, 10.1016/S0377-2217(02)00683-5

Kuypers, 2000, Information and efficiency: an empirical study of a fixed odds betting market, Applied Economics, 32, 1353, 10.1080/00036840050151449

Lee, 1997, Modeling scores in the Premier League: is Manchester United really the best?, Chance, 10, 15, 10.1080/09332480.1997.10554791

Leitch, 1991, Economic forecast evaluation: profits versus the conventional error measures, American Economic Association, 580

Leitner, 2010, Forecasting sports tournaments by ratings of (prob)abilities: a comparison for the EURO 2008, International Journal of Forecasting, 26, 471, 10.1016/j.ijforecast.2009.10.001

Maher, 1982, Modelling association football scores, Statististica Neerlandica, 36, 109, 10.1111/j.1467-9574.1982.tb00782.x

Min, 2008, A compound framework for sports results prediction: a football case study, Knowledge-Based Systems, 21, 551, 10.1016/j.knosys.2008.03.016

Peel, 1989, Outcome uncertainty and the demand for football, Scottish Journal of Political Economy, 35, 242, 10.1111/j.1467-9485.1988.tb01049.x

Peel, 1992, The demand for football: some evidence on outcome uncertainty, Empirical Economics, 4, 567

Peel, 1997, Handicaps, outcome uncertainty and attendance demand, Applied Economic Letters, 4, 567, 10.1080/135048597355041

Pope, 1989, Information, prices and efficiency in a fixed-odds betting market, Economica, 56, 323, 10.2307/2554281

Ridder, 1994, Estimating the effect of a red card in soccer, Journal of the American Statistical Association, 89, 1124, 10.1080/01621459.1994.10476850

Rotshtein, 2005, Football predictions based on a fuzzy model with genetic and neural tuning, Cybernetics and Systems Analysis, 41, 619, 10.1007/s10559-005-0098-4

Rue, 2000, Prediction and retrospective analysis of soccer matches in a league, The Statistician, 3, 339

A. Tsakonas, G. Dounias, S. Shtovba, V. Vivdyuk, Soft computing-based result prediction of football games, in: The First International Conference on Inductive Modelling (ICIM’2002), Lviv, Ukraine, 2002.

Vecer, 2009, Estimating the effect of the red card in soccer, Journal of Quantitative Analysis in Sports, 5, 10.2202/1559-0410.1146

Wilks, 1995, Statistical methods in the atmospheric sciences, vol. 59