※ 引述《zsh (噓 只是溝通的一種手段)》之銘言： : 多看看比賽吧 : 已經說過多少遍 : 別只拿數據來說嘴? : 籃球數據的根本是建立在什麼上面 : ->籃板 助攻 得分 出手數 火鍋 失誤......等等 : 一個好的單擋 帶來的效應有辦法反應在數據上面嗎? : 那一個好的單檔對球隊重要嗎? : 很重要吧 : 這麼重要的事情 竟然沒辦法在數據中呈現 : 這只是其中一小部份而已 : 籃球數據根本連最基本的樣本採樣的項目都不周全 : 後面得到的結論是能有多週全 多有代表性? : 所以別再拿數據出來丟人現眼啦~ : 假如數據對於籃球這麼重要 : 湖人還會二連霸 kobe還會拿下兩度fmvp : 你還是趕快去吃飯吧 Like most devoted NBA fans, we enjoy looking at boxscores. They'e often incredibly informative. And yet boxscores fail to capture many important elements of play: lockdown defense, screens, rotations, hustle plays, and so on that can affect the game's bottom line That's why we believe it's necessary to think outside the boxscore in order to adequately measure each player's true value to his team. The plus-minus statistic, which tracks all changes in scoring while each player is on the court, is one promising approach that's gained traction in recent years. But this metric suffers from a key drawback: each player's rating is heavily dependent upon the quality of his on-court teammates. Even a mere role player on a great team (e.g., Glen Davis) typically has a higher plus-minus rating than a superstar on a bad team (Dwyane Wade). Fortunately, this limitation can be overcome through the use of advanced mathematical techniques, which make it possible to isolate the unique effects of each player on the court. In other words, we can statistically adjust each player's plus-minus rating to account for the simultaneous impact of all his teammates and opponents [1]. Hence the name: adjusted plus-minus [2]. 希望你看得懂英文 --

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