Analysis of the Predictive Accuracy of "Fantasy Points-Allowed"

Since I've been so involved with statistical analysis of fantasy point projections, I have long wondered just how significant fantasy data (and trends) can be for predicting future outcomes. That's what this analysis is about.

I'm sure you all have seen some fantasy commentary like "Seattle has allowed the 6th fewest fantasy points to tight ends this season"... and then we all kind of hope that is information gives good guidance for our weekly lineup selections.

So I especially wanted to focus on the predictive worth of "fantasy points-allowed" by opponents.

TL;DR-- For most positions, Points-allowed is a poor measure, with correlation less than 0.10. (Therefore little improvement over a coin-flip.) In comparison, the offensive fantasy "points-for" are more predictive, correlations in the range of 0.15-0.20. Finally, by combining raw data, points-gained, and points-allowed into a single cross-validated prediction model, correlations can reach 0.35 for most positions.

Approach

I analyzed weekly running averages of fantasy points-for and fantasy points-allowed during 3 years (2017-2019). I created running-average time series, to represent an average of fantasy points from preceding weeks-- All these weekly averages were then used to calculate correlations with the actual weekly fantasy point outcomes/results.

I furthermore tested a few variations, to try and improve the method of averaging:

1. As I just described, the base case is a simple seasonal average of all prior weeks, within a given season.

2. I also tested a running average of fixed length, and I optimized the number of weeks used. For example, RB points-for becomes more predictive by using only the preceding 5 weeks of data. (For early weeks, I tried optimizing the usage of previous-season data, so also including 2016).

3. I also included my personally developed method of modifying averages to account for strength of opponent. There's too much to explain here about this, but the idea is that defensively allowing a lot of RB points to e.g. DAL-offense does not "count" as much as allowing a lot of RB points to WAS. It's a lot to explain, but I do it carefully to avoid a number of objections that you might think of. This procedure can make significant improvements; which is why I use this for all my projections.

Results - Accuracies for each position

Before looking at points-allowed, let's first get familiar with "points-for", meaning the offensive fantasy points scored by each position. To be clear, WR here refers to the team total: "total fantasy points scored by all WRs on a given team, each week."

_{Correlations between weekly seasonal averages and subsequent weekly results.}

Firstly, in the bar chart above, you can see that the accuracy is generally improved by using more smartly optimized averages. In other words, straightforward seasonal averaging gave lower reliability in all cases, when compared to the other 2 methods. Secondly, notice the range of outcomes: the values of the correlation coefficients fall around 0.15-0.20-- a bit mediocre if you treat these as projections. For reference, 0.15-0.20 is roughly in the range of the accuracy of usual kicker projections. They still carry meaning, but with predictive accuracy significantly below the levels of Vegas betting lines (0.36).

Next, look at the predictive accuracy of using points-allowed:

_{Correlations between weekly seasonal averages of "points allowed" and subsequent weekly results.}

First of all, notice that the "points-allowed" accuracies are significantly lower than the "points-for" accuracies shown before. (With the exception of D/ST, because points-allowed-to-D/ST now represents a team's offensive strength.) QB, RB, and TE take huge hits compared to their "points-for" counterparts. Secondly, notice again that the 2 types of improved averaging can make a big difference: most of the blue bars are hopelessly low. This means that RB-allowed, WR-allowed, and especially TE-allowed have very little predictive meaning, especially if you use straightforward seasonal averaging.

Last week, I presented this same chart, in the context of "how predictable is each position". I'm pretty convinced that most positions are represented reasonably well, which means we can compare against the "points-for" and "points-against" indicators. The overall point is that achieving correlations in the range of 0.35 carries a lot more value than a simple points-allowed approach with correlations less than 0.06 (for RB, TE, WR). So be careful when you hear information about points-allowed. After all, your favorite rankings source probably incorporates that information already.

/Subvertadown