A look at how rest impacts results in soccer and tennis.
We look at 4 different models to see whether the number of days since a previous match has an effect on the probability of winning:
- Poisson GLM
- Bivariate poisson
- Linear model for goal difference
- Proportional odds ordered logit
We use a logistic GLM model to evaluate the effect of previous match length on winning probability. We explore different ways of controlling for player ability.
- EDA: includes a quick look into the tennis covariates.
- Figures: Makes figures and tables for the paper.
- data-processing: Cleans the data and manipulates it into modelable form.
- writing: rmd file for the paper and intermediate versions.
- models: files in which the models are built.
- Masters_Paper_Chloe.key/pdf: presentation of the work given on 11/01/18
- Soccer: The data comes from the engsoccerdata R package.
- Tennis: The data was found on kaggle. https://www.kaggle.com/gmadevs/atp-matches-dataset