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Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer

  
22 lug 2017
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Audas, R., Dobson, S., & Goddard, J. (2002). The impact of managerial change on team performance in professional sports. Journal of Economics and Business, 54, 633–650.10.1016/S0148-6195(02)00120-0Search in Google Scholar

Cain, M., Law, D., & Peel, D. (2000). The favourite–longshot bias and market efficiency in UK football betting. Scottish Journal of Political Economy, 47, 25–36.10.1111/1467-9485.00151Search in Google Scholar

Dixon, M. & Pope, P. (2004). The value of statistical forecasts in the UK association football betting market. International Journal of Forecasting, 20, 697–711.10.1016/j.ijforecast.2003.12.007Search in Google Scholar

Dobson, S. & Goddard, J. (2001). The Economics of Football. Cambridge University Press, Cambridge.10.1017/CBO9780511493225Search in Google Scholar

Dobson, S. & Goddard, J. (2003). Persistence in sequences of football match results: A Monte Carlo analysis. European Journal of Operational Research, 148, 247–256.10.1016/S0377-2217(02)00681-1Search in Google Scholar

Dobson, S. & Goddard, J. (2008). Forecasting scores and results and testing the efficiency of the fixed-odds betting market in scottish league football. In: Albert, J. & Koning, R., eds., Statistical Thinking in Sports, Boca Raton, Florida, USA: Chapman & Hall, 91–110.Search in Google Scholar

Forrest, D., Goddard, J., & Simmons, R. (2005). Odds-setters as forecasters: the case of English football. International Journal of Forecasting, 21, 551–564.10.1016/j.ijforecast.2005.03.003Search in Google Scholar

Forrest, D. & Simmons, R. (2000). Forecasting sport: the behavior and performance of football tipsters. International Journal of Forecasting, 16, 317–331.10.1016/S0169-2070(00)00050-9Search in Google Scholar

Goddard, J. (2005). Regression models for forecasting goals and match results in association football. International Journal of Forecasting, 21, 331–340.10.1016/j.ijforecast.2004.08.002Search in Google Scholar

Goddard, J. & Asimakopoulos, I. (2004). Forecasting football results and the efficiency of fixed-odds betting. Journal of Forecasting, 23, 51–66.10.1002/for.877Search in Google Scholar

Graham, I. & Stott, H. (2008). Predicting bookmaker odds and efficiency for UK football. Applied Economics, 40, 99–109.10.1080/00036840701728799Search in Google Scholar

Greene, W. (2012). Econometric Analysis, Harlow, England: Pearson, 7th edition.Search in Google Scholar

Hvattum, L. (2015). Playing on artificial turf may be an advantage for Norwegian soccer teams. Journal of Quantitative Analysis in Sports, 11, 183–192.10.1515/jqas-2014-0046Search in Google Scholar

Hvattum, L. & Arntzen, H. (2010). Using ELO ratings for match result prediction in association football. International Journal of Forecasting, 26, 460–470.10.1016/j.ijforecast.2009.10.002Search in Google Scholar

Koning, R. (2000). Balance in competition in Dutch soccer. The Statistician, 49, 419–431.10.1111/1467-9884.00244Search in Google Scholar

Krumer, A. & Lechner, M. (2016). Midweek effect on performance: evidence from the German soccer Bundesliga. Economics Working Paper Series 1609, University of St. Gallen, School of Economics and Political Science.Search in Google Scholar

Kuypers, T. (2000). Information and efficiency: An empirical study of a fixed odds betting market. Applied Economics, 32, 1353–1363.10.1080/00036840050151449Search in Google Scholar

Nyberg, H. (2014). A multinomial logit-based statistical test of association football betting market efficiency. Discussion paper 380, HECER, Helsinki.Search in Google Scholar

Pope, P. & Peel, D. (1989). Information, prices and efficiency in a fixed odds betting market. Economica, 56, 323–341.10.2307/2554281Search in Google Scholar

Van Calster, B., Smiths, T., & Van Huffel, S. (2008). The curse of scoreless draws in soccer: the relationship with a team’s offensive, defensive, and overall performance. Journal of Quantitative Analysis in Sports, 4, Article 4.10.2202/1559-0410.1089Search in Google Scholar

Vlastakis, N., Dotsis, G., & Markellos, R. (2009). How efficient is the european football betting market? Evidence from arbitrage and trading strategies. Journal of Forecasting, 28, 426–444.10.1002/for.1085Search in Google Scholar

Štrumbelj, E. (2014). On determining probability forecasts from betting odds. International Journal of Forecasting, 30, 934–943.10.1016/j.ijforecast.2014.02.008Search in Google Scholar

Štrumbelj, E. (2016). A comment on the bias of probabilities derived from betting odds and their use in measuring outcome uncertainty. Journal of Sports Economics, 17, 12–26.10.1177/1527002513519329Search in Google Scholar

Witten, I. & Frank, E. (2005): Data mining: practical machine learning tools and techniques, San Francisco, CA: Elsevier.Search in Google Scholar

Lingua:
Inglese
Frequenza di pubblicazione:
2 volte all'anno
Argomenti della rivista:
Informatica, Base dati e data mining, Informatica, altro, Sport e ricreazione, Educazione fisica, Sport e ricreazione, altro