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Welcome to Regression Alert, your weekly guide to using regression to predict the future with uncanny accuracy.
For those who are new to the feature, here's the deal: every week, I dive into the topic of regression to the mean. Sometimes I'll explain what it really is, why you hear so much about it, and how you can harness its power for yourself. Sometimes I'll give some practical examples of regression at work.
In weeks where I'm giving practical examples, I will select a metric to focus on. I'll rank all players in the league according to that metric, and separate the top players into Group A and the bottom players into Group B. I will verify that the players in Group A have outscored the players in Group B to that point in the season. And then I will predict that, by the magic of regression, Group B will outscore Group A going forward.
Crucially, I don't get to pick my samples (other than choosing which metric to focus on). If the metric I'm focusing on is touchdown rate, and Christian McCaffrey is one of the high outliers in touchdown rate, then Christian McCaffrey goes into Group A and may the fantasy gods show mercy on my predictions.
Most importantly, because predictions mean nothing without accountability, I track the results of my predictions over the course of the season and highlight when they prove correct and also when they prove incorrect. Here's a list of my predictions from 2020 and their final results. Here's the same list from 2019 and their final results, here's the list from 2018, and here's the list from 2017. Over four seasons, I have made 22 or 23 specific predictions (depending on how you count them), and 18 of them have proven correct, a hit rate of 78-82%.
An Easy Win to Start Us Off
If you read last week's column, you know that one of the keys to profiting off of regression to the mean is recognizing that everything regresses, but not everything regresses at the same rate. The more a statistic is dominated by luck, the more that statistic is going to swing wildly from one sample to the next.
Because I'm going to be making predictions and tracking their accuracy, I want to start the season off with my best prediction, the one I'm most confident in. And to make that prediction, I want to focus on the statistic that is more dominated by luck and random chance than any other statistic I know. I want to focus on yards per carry (ypc).
Yards per carry is one of the most beloved statistics for judging running backs. Jamaal Charles has never averaged below 5 yards per carry in a season where he's had at least 20 carries*, therefore Jamaal Charles is a star. Trent Richardson had 1300 yards from scrimmage and 12 touchdowns as a rookie, ranking as a top-10 fantasy back, but his 3.6 yard per carry was an early warning sign that he would eventually be regarded as a colossal bust.
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