Increasingly, I’ve looked for ways to incorporate human input into my statistical modelling of hockey. For all its shortcomings, not the least of which is bias, scouting-based evaluation still captures things that have yet to be appropriately represented in publicly-available NHL data. The success stories told of those who excelled using analytics in hockey will be about people who effectively bridged the gap between two strangely dichotomous schools of thought.
With this in mind, I sought to learn more about the three stars selections that occur every game.1Henceforth, when I say “three stars” it should be understood I mean the game-by-game nominations, not the weekly or monthly awards. My intentions were twofold: I wanted to learn what factors influenced these decisions and how, but most importantly, I wondered if one could derive a Game Score using a model trained on the three stars history. Continue reading “Probabilistic Forecasting and Weighting of Three Star Selections”
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|1.||↑||Henceforth, when I say “three stars” it should be understood I mean the game-by-game nominations, not the weekly or monthly awards.|