[
Ahsan-ul-Haq, M., Al-Bossly, A., El-Morshedy, M., & Eliwa, M. S. (2022). Poisson XLindley distribution for count data: statistical and reliability properties with estimation techniques and inference. Computational Intelligence and neuroscience, 2022(1), 6503670.
]Search in Google Scholar
[
Baio, G., & Blangiardo, M. (2010). Bayesian hierarchical model for the prediction of football results. Journal of Applied Statistics, 37(2), 253-264.
]Search in Google Scholar
[
Best D. J., Rayner J. C. W. (1997). Crockett.s test of fit for the Bivariate Poisson. Biometrical Journal, 39(4):423.430.
]Search in Google Scholar
[
Boshnakov, G., Kharrat, T., & McHale, I. G. (2017). A bivariate Weibull count model for forecasting association football scores. International Journal of Forecasting, 33(2), 458-466.
]Search in Google Scholar
[
Bradley, R. A. and Terry, M. E. (1952). Rank analysis of incomplete blockdesigns: I. The method of paired comparisons. Biometrika, 39, 324-345.
]Search in Google Scholar
[
Cheon S., Song S.H., Jung B.C. (2009). Tests for independence in a bivariatenegative binomial model. J. Korean Statist. Soc., 38: 185-190.
]Search in Google Scholar
[
Chouia, S., & Zeghdoudi, H. (2021). The XLindley distribution: Properties and application. Journal of Statistical Theory and Applications, 20(2), 318-327.
]Search in Google Scholar
[
Constantinou, A. C., Fenton, N. E., & Neil, M. (2012). pi-football: A Bayesian network model for forecasting Association Football match outcomes. Knowledge-Based Systems, 36, 322-339.
]Search in Google Scholar
[
Cox, D.R. and D.V. Hinkley, (1979). Theoretical Statistics. 1st Edn., CRCPress, ISBN-10: 0412161605, pp: 528.
]Search in Google Scholar
[
McNeil, D. (1979). A QUICK TEST OF FIT OF A BIVARIATE DISTRIBUTION. In Interactive Statistics: Proceedings of the Applied Statistics Conference, Sydney, February 8-9, 1979 (p. 185). North-Holland.
]Search in Google Scholar
[
Dixon, M. J., Coles, S. G. (1997). Modelling association football scores andinefficiencies in the football betting market. Applied Statistics, 46(2), 265.
]Search in Google Scholar
[
Famoye, F. and P.C. Consul, (1995). Bivariate generalized Poisson distribution with some applications. Metrika, 42: 127-138.
]Search in Google Scholar
[
Famoye, F. (2010). On the bivariate negative binomial regression model. Journal of Applied Statistics, 37(6), 969-981.
]Search in Google Scholar
[
Ghitany M. E., Atieh B., Nadarajah S. (2008). Lindley distribution and itsapplications. Math. Comput. Simulation, 78, pp. 493-506.
]Search in Google Scholar
[
Goddard, J. (2005). Regression models for forecasting goals and matchresults in association football. International Journal of Forecasting, 21(2), 331-340.
]Search in Google Scholar
[
Goddard, J., & Asimakopoulos, I. (2004). Forecasting football results and the efficiency of .xed-odds betting. Journal of Forecasting, 23(1), 51-66.
]Search in Google Scholar
[
Holgate, P., (1964). Estimation for the bivariate Poisson distribution. Biometrika, 51: 241-245.
]Search in Google Scholar
[
Johnson, N.L., S. Kotz and N. Balakrishnan, (1997). Discrete Multivariate Distributions. 1st Edn., Wiley, New York, ISBN-10: 0471128449, pp: 328.
]Search in Google Scholar
[
Jung, B.C., M. Jhun and S.M. Han, (2009). Score test for overdispersionin the bivariate negative binomial models. J. Statist. Comput. Simulat., 79:11-24.
]Search in Google Scholar
[
Karlis, D. and I. Ntzoufras, (2003). Analysis of sports data by using Bivariate Poisson models. Statistician, 52: 381-393.
]Search in Google Scholar
[
Karlis, D., &Ntzoufras, I. (2009). Bayesian modelling of football outcomes: using the Skellam.s distribution for the goal difference. IMA Journal of Management Mathematics, 20(2), 133-145.
]Search in Google Scholar
[
Kocherlakota, S., & Kocherlakota, K. (2017). Bivariate discrete distributions. CRC Press.
]Search in Google Scholar
[
Khodja, N., Gemeay, A. M., Zeghdoudi, H., Karakaya, K., Alshangiti, A. M., Bakr, M. E., Hussam, E. (2023). Modeling voltage real data set by a new version of Lindley distribution. IEEE Access, 11, 67220-67229.
]Search in Google Scholar
[
Lakshminarayana, J., S.N.N. Pandit and K.S. Rao, (1999). On a bivariatePoisson distribution. Communicat. Statist. Theory Methods, 28: 267-276.
]Search in Google Scholar
[
Lindley, D. V. (1958). Fiducial distributions and Bayes’ theorem. Journal of the Royal Statistical Society. Series B (Methodological), 102-107.
]Search in Google Scholar
[
Lord, D. and S.R. Geedipally, (2011). The negative binomial-Lindley distribution as a tool for analyzing crash data characterized by a large amount of zeros. Accident Anal. Prevent., 43: 1738-1742.
]Search in Google Scholar
[
Loukas S. and Kemp C. D. (1986), The Index of Dispersion Test for the Bivariate Poisson Distribution. International Biometric Society, Vol. 42, No. 4,pp. 941-948.
]Search in Google Scholar
[
Maher,M. J. (1982).Modelling association footballscores. Statistica Neerlandica, 36(3),109.118.
]Search in Google Scholar
[
Mahmoudi E. and Zakerzadeh H. (2010), Generalized Poisson-Lindley distribution, Communications in Statistics- Theory and Methods, 39, 1785 - 1798.
]Search in Google Scholar
[
Marek, P., .edivá, B., & µToupal, T. (2014). Modeling and prediction of icehockey match results. Journal of quantitative analysis in sports, 10(3), 357-365.
]Search in Google Scholar
[
Mitchell, C. R., & Paulson, A. S. (1981). A new bivariate negative binomial distribution. Naval Research Logistics Quarterly, 28(3), 359-374.
]Search in Google Scholar
[
Owen, A. (2011). Dynamic Bayesian forecasting models of football matchoutcomes with estimation of the evolution variance parameter. IMA Journal of Management Mathematics, 22(2), 99-113.
]Search in Google Scholar
[
Paul, S.R. and N.I. Ho, (1989). Estimation in the bivariate poisson distribution and hypothesis testingconcerning independence. Communicat. Statist.Theory Methods. 18: 1123-1133.
]Search in Google Scholar
[
Reep, C., & Benjamin, B. (1968). Skill and chance in association football. Journal of the Royal Statistical Society. Series A (General), 131(4), 581-585.
]Search in Google Scholar
[
Sadeghkhani, A., & Ahmed, S. E. (2020). The application of predictive distribution estimation in multiple-inflated poisson models to ice hockey data. Model Assisted Statistics and Applications, 15(2), 127-137.
]Search in Google Scholar
[
Sankaran, M., (1970). The discrete Poisson-Lindley distribution. Biometrics, 26: 145-149.
]Search in Google Scholar
[
Seghier, F. Z., Zeghdoudi, H., & Raman, V. (2023). A Novel Discrete Distribution: Properties and Application Using Nipah Virus Infection Data Set. European Journal of Statistics, 3, 3-3.
]Search in Google Scholar
[
Shanker, R. (2016a). The discrete poisson-amarendra distribution. Int. J. Stat. Distrib. Appl, 2(2), 14-21.
]Search in Google Scholar
[
Shanker R. (2016b), The discrete Poisson-Sujatha distribution. International Journal of Probability and Statistics. 5(1):1-9.
]Search in Google Scholar
[
Shanker R. (2017), The discrete poisson-garima distribution. Biometrics & Biostatistics International Journal, 5(2):48-53.
]Search in Google Scholar
[
Seghier, F. Z., Ahsan-ul-Haq, M., Zeghdoudi, H., & Hashmi, S. (2023). A new generalization of poisson distribution for over-dispersed, count data: mathematical properties, regression model and applications. Lobachevskii Journal of Mathematics, 44(9), 3850-3859.
]Search in Google Scholar
[
Tsokos, A., Narayanan, S., Kosmidis, I., Baio, G., Cucuringu, M., Whitaker, G., & Király, F. (2019). Modeling outcomes of soccer matches. Machine Learning, 108, 77-95.
]Search in Google Scholar
[
Wheatcroft, E. (2021). Forecasting football matches by predicting match statistics. Journal of Sports Analytics, 7(2), 77-97.
]Search in Google Scholar
[
Zamani, H., Faroughi, P., & Ismail, N. (2014, June). Bivariate Poisson-weighted exponential distribution with applications. In AIP Conference Proceedings (Vol. 1602, No. 1, pp. 964-968). American Institute of Physics.
]Search in Google Scholar
[
Zamani, H., P. Faroughi and N. Ismail, (2015). Bivariate Poisson-Lindley Distribution with Application, Journal of Mathematics and Statistics, 11 (1): 1-6.
]Search in Google Scholar
[
Zeghdoudi, H., & Nedjar, S. (2017). On Poisson pseudo Lindley distribution: Properties and applications. Journal of probability and statistical science, 15(1), 19-28.
]Search in Google Scholar
[
Shahin, S. (2023). Sports Data Analysis by using Bivariate Poisson Models in the Bayesian Framework. Quaid-e-Awam University Research Journal of Engineering Science and Technology, 21(1), 7-15.
]Search in Google Scholar
[
Wheatcroft, E. (2021). Forecasting football matches by predicting match statistics. Journal of Sports Analytics, 7(2), 77-97.
]Search in Google Scholar
[
Singh, A., Scarf, P., & Baker, R. (2023). A unified theory for bivariate scores in possessive ball-sports: the case of handball. European Journal of Operational Research, 304(3), 1099-1112.
]Search in Google Scholar
[
[1] Data Set I :https://www.the-sports.org/football-soccer-2021-2022-german-bundesligaepr114545.html. 2023
]Search in Google Scholar
[
[2] Data Set II :https://www.the-sports.org/football-soccer-2019-2020-german-bundesligaepr98318.html. 2024
]Search in Google Scholar
