A bivariate Weibull count model for forecasting association football scores

106 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Forecasting football match results in national league competitions using score-driven time series models (2019, unknown): “For example, Dixon and Robinson (1998) treat the numbers of goals scored by the competing teams during a match as interacting birth processes, while Boshnakov, Kharrat, and McHale (2017) deal with them within a bivariate distribution based on Weibull inter-arrival-times count processes and a copula…”
Ranking soccer teams on basis of their current strength: a comparison of maximum likelihood approaches (2017, background): “Notwithstanding, we mention some important contributions in this field: Dixon and Coles (1997) added an additional parameter to adjust for the probabilities on low scoring games (0-0, 1-0, 0-1 and 1-1), McHale and Scarf (2011) investigated copula dependence structures, and Boshnakov et al. (2017) re”