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1. Min, B.,  Choe, C. and McKay, R. I. (2006) “A compound approach for football result prediction”,

Working Papers, Seoul National University.

http://sc.snu.ac.kr/PAPERS/aj06_FRES_final.pdf

 

2.  Min, B., Kim, J., Choe, C. and McKay, R. I. (2007) “A compound framework for sport prediction: the case of football”,

Working Papers, Seoul National University.

http://sc.snu.ac.kr/PAPERS/bhmin07_KBS.pdf.

 

3. Min, B., Choe, C., Eom, H. and McKay, R. I. (2008) “A compound framework for sports results prediction: a football case study”,

Knowledge-Based Systems, Vol.21, No.7, pp.551-562.

DOI:10.1016/j.knosys.2008.03.016

 

4. Sindik, J. and Vidal, N. (2009) “Uncertainty coefficient as a method for optimization of the competition systems in various sports”,

Sport Science, Vol. 2, No.1, pp.95-100.

http://sposci.com/PDFS/BR0201/SVEE/04%20CL%2015%20JS.pdf

 

5. Buursma, D. (2011) “Predicting sports events from past results: towards effective betting on football matches”,

Conference Paper, presented at 14th Twente Student Conference on IT, 21 January 2011, Twente, Holland.

http://arbre.nl/Refrooster20102011S1.pdf

referaat.cs.utwente.nl/TSConIT/download.php?id=931

 

6. Petrunin, Y.Y. (2011) “Analysis of the football performance: from classical methods to neural network”,

Conference Paper, presented at Electronic Culture: Intellectual Innovative Technologies in the Socio-Cultural Sphere, Russian Interdisciplinary Conference, Moscow State University, 26 October 2011, Russia.

 http://www.ec-ai.ru/elib/15.pdf

 

7. Imamoglu, O., Cebi, M., Elioz, M. (2011) “Dunya kupasindaki gollerin teknik ve taktik kriterlere gore analizi”,

Turkiye Kickboks Federasyonu Spor Bilimleri Dergisi, Cilt 4, Sayi 2.

http://edergi.kickboks.gov.tr/Arsiv

 

8. Constantinou, A.C., Fenton, N.E. (2012) “Determining the level of ability of football teams by dynamic ratings based on the relative discrepancies in scores between adversaries”,

Working Papers, Queen Mary University, London.

http://www.constantinou.info/downloads/papers/pi-ratings.pdf

 

9. Constantinou, A.C., Fenton, N.E., Neil, M. (2012) “A Bayesian network model for forecasting Association Football match outcomes”,

Working Papers, Queen Mary University, London.

http://constantinou.info/downloads/papers/pi-model11.pdf

 

10. Constantinou, A.C., Fenton, N.E., Neil, M. (2012) “pi-football: A Bayesian network model for forecasting Association Football match outcomes”,

Knowledge-Based Systems, Vol.36, pp.322-339.

http://dx.doi.org/10.1016/j.knosys.2012.07.008,

 

11. Constantinou, A.C. (2012) “Bayesian networks for prediction, risk assessment and decision making in an inefficient association football gambling market”,

PhD Thesis in Risk and Information Management, Queen Mary University, London.

http://constantinou.info/downloads/papers/Constantinou-Ph.D.pdf

 

12. Imamoglu, et al. (2012) “Descriptive analysis of the 2012 European football championship goals based on technical and tactical criteria”

Conference Paper, presented in Thailand.

https://www.researchgate.net/publication/325922845_Descriptive_Analysis_of_The_2012_European_Football_Championship_Goals_Based_on_Technical_and_Tactical_Criteria

 

13. Constantinou, A.C.,  N.E., Fenton. (2013) “Determining the level of ability of football teams by dynamic ratings based on the relative discrepancies in scores between adversaries”,

Journal of Quantitative Analysis in Sports, Vol.9, No.1.

http://www.degruyter.com/view/j/jqas.ahead-of-print/jqas-2012-0036/jqas-2012-0036.xml?format=INT

 

14. Arabzad, S.M., et al. (2014) “Football match results prediction using artificial neural networks: the case of Iran pro league”,

Applied Research on Industrial Engineering, Vol.1, No.3, pp.159-179.

http://grandjournals.com/NVL/Gallery/contents/1132afee-6640-4c9d-9b90-a3c55efc40a3.pdf