Princeton Engineering 10

Princeton Engineering 10 - Plug in a few numbers. Press the...

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Plug in a few numbers. Press the Calculate button. And just like that, a number pops out, displaying your quarterback’s performance. 31.4? He had a bad day. 128.7? He put up a show. Amazing isn’t it? I would like to say that the NFL Quarterback Rating Formula precisely measures quarterback performance. But it doesn’t. The problem is two-fold. First, all variables towards quarterback performance must be included to produce a precise rating. Second, these predictors need to be perfectly quantified. Presently the formula includes attempts, completions, passing yards, passing touchdowns, and interceptions as predictors that comprise a quarterback’s rating. However, the formula lacks sacks, composure, and fumbles, among many other predictors, that are crucial towards determining quarterback performance. I like to think of this as gathering pieces to a puzzle. The more predictors you have, the better your model will be. But the quarterback formula is not limited to just gathering predictors. These
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