<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The goal of our research was to use simulation modelling for prediction of the Croatian First Football League seasonal ranking and analyse variation in teams’ performance during a season. We have developed a model of the number of goals scored by a team in a match based on the Poisson distribution. Parameters of the model were estimated from the data on consecutive matches in a season. Variation in a team’s performance was modelled as a moving parameter estimate. The final rankings were predicted from 1000 simulation runs of the second part of the season based on parameter estimates from the first part of the season. For each team the most frequent outcome of the simulation defined the team’s rank. The method was tested on seasons 2014/15 and 2015/16. Prediction was correct for six teams in the season 2014/15 and five teams in the season 2015/16. Proposed methods enable dynamic monitoring of a team’s performance and prediction of final rankings during the season. An advantage of the prediction method is that in addition to predicting the final ranking it also estimates probabilities of alternative positions.</p></abstract>

The goal of our research was to use simulation modelling for prediction of the Croatian First Football League seasonal ranking and analyse variation in teams’ performance during a season. We have developed a model of the number of goals scored by a team in a match based on the Poisson distribution. Parameters of the model were estimated from the data on consecutive matches in a season. Variation in a team’s performance was modelled as a moving parameter estimate. The final rankings were predicted from 1000 simulation runs of the second part of the season based on parameter estimates from the first part of the season. For each team the most frequent outcome of the simulation defined the team’s rank. The method was tested on seasons 2014/15 and 2015/16. Prediction was correct for six teams in the season 2014/15 and five teams in the season 2015/16. Proposed methods enable dynamic monitoring of a team’s performance and prediction of final rankings during the season. An advantage of the prediction method is that in addition to predicting the final ranking it also estimates probabilities of alternative positions.

Croatian First Football League: Teams' performance in the championship

Faculty of Organization and Informatics, University of Zagreb, Varaždin,

Croatian Review of Economic, Business and Social Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Croatian First Football League: Teams' performance in the championship"}

The goal of our research was to use simulation modelling for prediction of the Croatian First Football League seasonal ranking and analyse variation in teams’...

Croatian First Football League: Teams' performance in the championship

Data publikacji: 15 paź 2016

Zakres stron: 15 - 23

Otrzymano: 25 maj 2016

Przyjęty: 24 sie 2016

DOI: https://doi.org/10.1515/crebss-2016-0006

Słowa kluczowe
football, performance monitoring, Poisson distribution, predictive analytics, simulation, sports analytics

© 2016

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Croatian First Football League: Teams' performance in the championship

Data publikacji: 15 paź 2016

Zakres stron: 15 - 23

Otrzymano: 25 maj 2016

Przyjęty: 24 sie 2016

DOI: https://doi.org/10.1515/crebss-2016-0006

Słowa kluczowefootball, performance monitoring, Poisson distribution, predictive analytics, simulation, sports analytics

© 2016

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Słowa kluczowe
football, performance monitoring, Poisson distribution, predictive analytics, simulation, sports analytics