Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/30375
Title: Estimação de rating no futebol: campeonato brasileiro de 2017
Other Titles: Estimation of rating in football: championship brazilian of 2017
Authors: Bueno Filho, Júlio Sílvio de Sousa
Guimarães, Paulo Henrique Sales
Oliveira, Deive Ciro de
Keywords: Futebol - Estimativa - Brasil
Futebol - Forças de ataque
Futebol - Forças de defesa
Distribuição de probabilidade
Distribuição de Poisson
Estimativa de classificação
Previsão
Soccer estimation - Brasil
Soccer attack forces
Soccer defense forces
Probability distribution
Poisson distribution
Rating estimation
Prediction
Issue Date: 4-Sep-2018
Publisher: Universidade Federal de Lavras
Citation: GALVÃO, L. R. Estimação de rating no futebol: campeonato brasileiro de 2017. 2018. 48 p. Dissertação (Mestrado em Estatística e Experimentação Agropecuária)–Universidade Federal de Lavras, Lavras, 2018.
Abstract: Observing games from 2017 Brazilian Footbal Championship League series A, we adjusted Poisson models with linear predictors for the expectation of the number of goals from home and away teams. We estimated attacking (g ) and defense (d ) strength parameters for each team. A common home advantage effect (m ) was used for all teams. The first leg of the double roundrobin was used to estimate initial ratings. Those parameters were then re-estimated at each round of the second leg. We intend to present a descriptive model that could estimate as well as predict scores and results from each game. Additionial features of the final table could also be predicted as probability of playing South American Champions League or being demoted to series B of the competition. Model has been shown flexible in the pure likelihood analysis version, but some of desirable features of parametric Bayesian inference could enhance some of its properties and will be object of future research.
URI: http://repositorio.ufla.br/jspui/handle/1/30375
Appears in Collections:Estatística e Experimentação Agropecuária - Mestrado (Dissertações)

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