Welcome to the fantasy football draft training series, where you learn how to draft like the pros. In the last video, I broke down exactly how you should create power ratings for quarterbacks. In this video, it’s the running backs’ turn. Remember, the process is pretty basic: we multiply our projected points by the consistency correlations I’m about to show you, then add it all up for a final power rating.
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Here are the correlations: .49 for rushing yards, .47 for rushing touchdowns, .65 for receptions, .55 for receiving yards, and .29 for receiving touchdowns. Each number is representative of the percentage of a running back’s stats that carry over from year to year. For rushing yards, for example, the average RB sees 49 percent of his production carry over from one season to the next, with the rest regressing back toward a league mean.Is preparing for the draft killing you? Power up here and never look back.
Both rushing yards and touchdowns are moderately consistent, but the predictability of running back receptions is pretty remarkable. As one of the more consistent stats, it’s easy to see why pass-catching running backs are valuable. Actually, running backs who catch a lot of passes even hold more value in non-PPR leagues. Think about it: more ways to beat defenses is always a good thing and it makes pass-catching backs safe from week to week. Receiving touchdowns, as a low-frequency event for running backs, are rather volatile. That means we shouldn’t give them much weight in our final rankings.
How to implement the running back correlations
To show you how to implement the running back correlations, let’s use Chris Johnson as an example. Assume you project Johnson for 1,200 yards and seven touchdowns on the ground and 35 receptions, 250 yards, and one touchdown as a receiver in 2013. You’d then use your league’s scoring system to calculate the points Johnson would put up with those numbers, which I’ve listed in a traditional PPR league.
Now we can multiply those projected points by the corresponding consistency correlations for each stat. For Johnson’s rushing yards, for example, we multiply the 120 projected points by the .49 strength of correlation to get a 58.8 rushing yard rating.
Finally, we can simply add together each individual rating to obtain Johnson’s overall 2013 power rating. Like the one I produced for Cam Newton in the previous video, this numerical value isn’t useful in isolation, but once we calculate the power ratings for other running backs, the comparisons we can make will be more accurate than if we were to compare traditional projections.
You can see an example of this in the weight placed on Johnson’s rushing touchdowns and receptions. The touchdowns were originally worth more in our initial projections, but they’re not nearly as predictable as receptions. Because of that, the receptions ended up being more valuable in the final power rating. Remember, a projection is only as good as its predictability.
In the next video, I’ll give you the wide receiver consistency correlations and we’ll go over the same process for that position. Thanks for checking out the fantasyknuckleheads.com fantasy football "how to draft" training series. If you have any questions, check out the member forum.