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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 30 specific predictions and 24 of them have proven correct, a hit rate of 80%.
In Week 2, I broke down what regression to the mean really is, what causes it, how we can benefit from it, and what the guiding philosophy of this column would be. No specific prediction was made.
In Week 3, I dove into the reasons why yards per carry is almost entirely noise, shared some research to that effect, and predicted that the sample of backs with lots of carries but a poor per-carry average would outrush the sample with fewer carries but more yards per carry.
In Week 4, I talked about yard-to-touchdown ratios and why they were the most powerful regression target in football that absolutely no one talks about, then predicted that touchdowns were going to follow yards going forward (but the yards wouldn't follow back).
In Week 5, we looked at ten years worth of data to see whether early-season results better predicted rest-of-year performance than preseason ADP and we found that, while the exact details fluctuated from year to year, overall they did not. No specific prediction was made.
|Statistic for regression||Performance before prediction||Performance since prediction||Weeks remaining|
|Yards per Carry||Group A had 10% more rushing yards per game||Group A has 10% more rushing yards per game||1|
|Yards per Touchdown||Group A scored 9% more fantasy points per game||Group B scores 22% more fantasy points per game||2|
As I mentioned last week, things look very grim for our yards per carry prediction, but not because we were wrong to bet against yards per carry. Over the last three weeks, our "high ypc" backs average 4.70 yards per carry while our "low ypc" backs average 4.89. Yards per carry is pseudoscience.
No, the real problem here is that our "low-volume" Group A backs went from 13.9 carries per game to 14.1 carries per while our "high-volume" Group B backs fell from 17.7 carries per game all the way down to 12.1 carries per game. The reasons will get a full write-up next week if (as is almost certain) the prediction fails, but there's no single explanation. Instead, of the 10 Group B backs, only two (Darrell Henderson once and Ezekiel Elliott three times) have topped their prior per-game carry average in any game since the prediction. Meanwhile, nine of the eleven Group A backs have combined to top their per-game average seventeen times.
Our second prediction is still trucking along, though. Our "high touchdown" receivers scored 0.40 touchdowns per game while our "low touchdown" receivers scored 0.38 touchdowns per game, but Group B kept their yardage advantage.
The Science of Intuition
One goal of this column is to convince you that regression to the mean is real, it is powerful, and it is everywhere. To explain what it is and how (and why) it works. Another goal is to give you lists of players who are underperforming and players who are overperforming so you can make informed decisions about what to do with them going forward.
But another goal is to equip you with the tools to spot regression in the wild on your own, to help you develop intuitions about what kinds of performances are sustainable and what kinds of performances are unsustainable. Obviously, I'll highlight certain stats and give you my opinions on them. Yards per carry: bad. Yards per touchdown: sustainable, but only within a narrow range from about 100-200. Interception rate: bad. (Sorry, spoiler alert.)
But as years go on, one fact of life in fantasy football is exposure to new statistics. If you listen to football commentary these days you might hear about things like Air Yards, Completion Percentage over Expectation (or CPOE), or Expected Points Added (or EPA). Some of these stats didn't even exist until a few years ago. Are they good? Are they bad?
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