This is a model to predict NHL game winners & their likely performance for the rest of the season.
Read more about the package at https://pbulsink.github.io/HockeyModel
Current predictions are below, and are always posted on Bluesky at @bot.bulsink.ca.
Installation now doesn't automatically install documenting, testing, tweeting, graphics and parallel processing requirements. You may wish to run install.packages(c('knitr', 'rmarkdown', 'testthat', 'webshot', 'progress', 'markdown', 'covr', 'tictoc', 'parallel', 'ggrepel', 'gt', 'ggalt', 'ggridges', 'scales', 'ggplot2', 'rtweet', 'devtools', 'usethis')).
- ~~Twitter user @MOCallanain highlighted that the predicted tie rate is < ~0.2, when in actuality it's higher. Likely due to teams playing for loser point, can we parameterize the model to include a tie boost? Diagonal enhanced metric should work - calculate like the DC 0/1 goal enhancement. Model currently re-scales to increase odds to a reasonable amount.~~ DONE
Currently, only scores are used for model generation. Moneypuck has an expansive expected goals model available for download and updated regularly (see http://moneypuck.com/data.htm). Deriving the team performance by expected goals instead of actual could reduce the impact of luck on expected future performance.Won't Do - Use my own xG model instead (see BulsinkBxG).Switch to NHL API for scores and scheduleDONE- ~~Twitter user @joseph__ii picked up on a quirk of the OT/SO odds assignment (see https://twitter.com/joseph__ii/status/1357785234285109248). Try rebalance with league or teams' OT performance measure? ~~ DONE