Comments (1)
Hey! This is a good suggestion; thanks for opening it.
Adding model evaluation metrics generally seems like a really good idea. RPS is, as you point out, particularly nice for evaluating 1X2 predictions. Off the top of my head, this and log loss seems like the key ones. Maybe even a Kelly staked betting-related metric could be worth adding at some point?
It seems like (tidy?) model evaluation could be a good idea for an R package in itself. I should probably see if one already exists. Although even if something like that does already exist, it seems like it'd be a good idea to export in regista's namespace so that models + evaluation come together.
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Related Issues (20)
- Return tibbles
- Use rsample > modelr HOT 1
- Use tidyeval > lazyeval HOT 1
- Create a package site HOT 1
- Dixon-Robinson fit
- predict.dixoncoles requires unnecessary home/away goals columns
- Informative error message when predicting with different factor levels
- Warnings after fit HOT 2
- Dixon-Robinson predict method HOT 1
- Broom model methods
- Include example goal-times data
- Correct old blogs and documentation
- Speed up dixoncoles tests
- Dixoncoles really really slow HOT 6
- DixonColes error message HOT 5
- Can't create table of scoreline probabilities without dixoncoles class object HOT 3
- error with broom HOT 8
- Use Github Actions
- Unplayed games - factor issues HOT 8
- Non-list contrasts argument ignored while modeling HOT 1
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from regista.