Franckie Burns BÀsta sammanfattningen av plus/minus jag lÀst. Hatten av!
Franckie Burns Plus-minus har alltid varit ett trubbigt mĂ„tt - det gĂ€ller framförallt nĂ€r urvalet Ă€r litet (âsmall sample sizeâ som de sĂ€ger). MĂ„lchanser och skott framĂ„t respektive bakĂ„t sĂ€ger mer dĂ„ skottprocent och rĂ€ddningsprocent jĂ€mnar ut sig över tid. Skapar man konsekvent chanser sĂ„ kommer puckarna börja gĂ„ in till slut. SlĂ€pper man konsekvent till chanser bakĂ„t sĂ„ kommer det börja ringa Ă„t det hĂ„llet, svĂ„rare Ă€n sĂ„ Ă€r det inte. Blivande GM @Hank fĂ„r gĂ€rna komma in och nyansera detta om han tycker att jag ger en missvisande bild.
Exakt sÄ. Att tillÀgga i fallet med Maxwell Àr Àven att han ligger pÄ en ohÄllbar PDO-nivÄ pÄ 92 (lÀgst i laget), men ligger pÄ 55% i Corsi (bÀst i laget).
För den som vill lÀsa lite mer sÄ finns det artiklar som denna:
Plus-minus is the most useless and misleading statistic in hockey analytics today
Plus-minus is a terrible number for measuring how good a player is.
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The amount of control an individual player has over their own plus-minus is very tiny. Players make mistakes all the time. They can also excel at times. All too often, goals are scored, and you had nothing to do with it.
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Plus-minus is very flawed. It really shouldnât be used anymore, as Corsi and Fenwick are better indicators. Shots are inherently a far bigger sample size than goals, and we should acknowledge this.
och denna:
Why Plus/Minus is the worst statistic in hockey and should be abolished
Donât get me wrong, goals are the end objective, and in the very long run it should be worth at least a look, but we also know that sometimes players get lucky bounces, or that goaltenders steal games. This uncertainty means we canât rely on goals for predictivity.
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Combining a rare event with highly variable confounding variables and you get a number that takes a very long while to settle. With plus/minus, this often means multiple seasons.
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Looking at goals as a measure of outscoring doesnât necessarily tell you who will outscore in the future, and we have far more effective means in determining who will.
Det finns studier pÄ hur bra olika statistika mÄtt Àr pÄ att förutse framtida resultat. HÀr Àr en som visar just detta, dÀr man har jÀmfört xG, Corsi (CF%) och plus/minus (GF%).:
Expected Goals (xG) significantly outperforms score-adjusted Corsi (CF%) and Goals For (GF%) in predicting future goals at the team and player levels.
