Which are More Accurate: Fantasy Football Rankings or Projections?
21When deciding how to compare players in fantasy football, managers have an important decision: whether to compare players with rankings or projections. In this article, we compare the accuracy of fantasy football rankings vs. projections.
There are a few possible reasons to expect that rankings may be more accurate than projections, but there are also several reasons to expect that projections may be more accurate than rankings. In the case of rankings, many more analysts provide rankings than projections, so the “wisdom of the crowd” includes a larger crowd for rankings, which may reduce error. Some people argue that the top RB/QB/WR scores about the same number of points every year, so their position ranking matters more their projections. However, there is often considerable variability in actual fantasy points from year to year for the same position rank. For instance, there was a 60+ point difference in the top RB from 2008 to 2009 and a 50+ point difference in the top RB from 2014 to 2015 (according to Pro-Football-Reference.com). This is just one example of variability in actual performance for the same position rank, but there are many other examples. Moreover, what matters for fantasy performance is not whether you had the top ranked RB, but rather, how many more points your RB scored relative to other RBs.
As a result, there are several reasons to expect that projections may be more accurate than rankings. First, projections can be customized to your league settings (unlike rankings). Second, projections tell you how much players are better than each other, whereas rankings do not. Moreover, you can always calculate rankings from projections but you cannot reverse engineer projections from rankings. You can also account for variability and injury risk when examining projections, as we do in our tools.
Method
We were interested in seeing whether rankings or projections were more accurate for predicting actual performance, so our criterion was actual fantasy points scored. We compared the accuracy of 2015 rankings versus projections using standard league scoring settings. We used R-squared (R2) to evaluate prediction accuracy rather than MASE, because we were interested in relative accuracy, not absolute accuracy (i.e., position rank is not on the same metric as actual fantasy points scored, so estimates of absolute accuracy would not be meaningful). For rankings across positions, we used FantasyPros Expert Consensus Rankings (i.e., expert rankings: ECR) and Average Draft Position (i.e., crowd rankings; ADP). We also determined within-position rankings from the ECR and ADP. For projections, we calculated the average of projections across sources using our Projections tool.
R Script
You can download the R script for the analysis here:
Results
FantasyPros had 167 sources of rankings to include in their “wisdom of the crowd” for expert rankings. We had 11 sources of projections to include in our “wisdom of the crowd” for projections, except for K and DST (7 sources).
Despite having considerably fewer sources, projections (R2 = .53) were more accurate than expert rankings (R2 = .27) and crowd rankings (R2 = .23) in predicting actual performance. Projections were nearly twice as accurate as rankings.
When examining within-position rankings versus projections:
QB: Projections (R2 = .50) were more accurate than expert rankings (R2 = .37) and crowd rankings (R2 = .29)
RB: Expert rankings (R2 = .41) were more accurate than projections (R2 = .36) and crowd rankings (R2 = .32)
WR: Projections (R2 = .48) were more accurate than expert rankings (R2 = .44) and crowd rankings (R2 = .29)
TE: Projections (R2 = .47) were more accurate than expert rankings (R2 = .43) and crowd rankings (R2 = .25)
K: Neither expert rankings (R2 = .09) nor crowd rankings (R2 = .03) nor projections (R2 = .02) were accurate, but rankings were more accurate
DST: Neither expert rankings (R2 = .22) nor crowd rankings (R2 = .17) nor projections (R2 = .08) were accurate, but rankings were more accurate
Conclusions
In general, projections were more accurate than rankings, especially for QBs, WRs, and TEs. Projections were nearly twice as accurate as rankings. Interestingly, crowd rankings were slightly less accurate than expert rankings. Neither rankings nor projections were accurate for Ks and DSTs (consistent with our prior findings), but were slightly more accurate for rankings than projections. This may be because there were simply few sources of projections for Ks and DSTs. We expect projections to continue to be considerably more accurate than rankings as we continue to add more sources of projections. Hopefully, this results in an increased accuracy for predicting Ks and DSTs.
The bottom line is that we suggest using projections instead of rankings because 1), projections can be adapted to your league settings (unlike rankings) 2) projections tell you how much players are better than each other, 3) you can calculate rankings from projections but you cannot calculate projections from rankings, 4) you can account for variability risk and injury risk when using projections (as we do in our tools), and 5) projections are generally more accurate than rankings. You can use customized projections for your league settings using our Projections tool.
Why can’t you generate a projection from rankings? Just use the positional mean over X years. Projections are likely using some kind of similarity score or knn algorithm.
My guess why projections are better is that it is easier to rank than project, so the difficulty is a quality filter. If you look at the projectors’ rankings i’d think they are superior.
Hi Eric,
Good question. You could impute a projection estimate from the ranking based on the historical average of projections for a given position rank, but it would be fairly inaccurate because of the considerable year-to-year variability in fantasy points by position rank. It’s easier to go from a higher level of measurement to a lower level of measurement (e.g., interval/ratio to ordinal) than the other way around: http://web.csulb.edu/~msaintg/ppa696/696meas.htm. In other words, using rankings throws away a lot of useful information that is included in projections.
FantasyPros actually tracks the accuracy of the sources of rankings. The sources providing projections don’t appear to be higher than the others: http://www.fantasypros.com/nfl/accuracy/draft.php. That suggests that it’s not simply a quality filter.
Hope that helps,
Isaac
Where did you get your scores from?
https://fantasyfootballanalytics.net/about-the-site/faq#sources
Do you get the same result if you compare FFA projections to ADP rankings, rather than expert rankings? I know that ADP doesn’t allow you to compare value between positions, but I would assume that ADP reflects the ‘wisdom of the crowd’ even more accurately than projections WITHIN positions, since the crowd’s perception of projection/ranking sources is baked into ADP (and the crowd = tens of thousands of drafters, not just FFball analysts).
How would one test this hypothesis?
Good idea! I just added tests of ADP accuracy to the scripts and article. ADP was slightly less accurate than expert rankings, and was generally less accurate than projections. Thanks for the suggestion!
Is it possible to get data on projections vs rankings (ECR and ADP) for previous years before 2015?
Whatever we have available to download in the Projections tool (http://apps.fantasyfootballanalytics.net/) is what we have available—I don’t remember how many past years we have ECR and ADP available.
Hey Issac,
Thanks for the response. I guess I was more referring to the R-squared values of previous years comparing projections to ECR and ADP. The 2015 values were .53, .27 and .23, respectively. I honestly have no idea how long it takes to come up with those stats so if it’s way too time consuming, then definitely don’t worry about it. Thank you!!
Have you measured the results of using your calculated projections to generate a nameless list of positions with points (#1 WR1, #2 WR2, #3 RB1, #4 WR3, etc.), and then populating that list using expert rankings? Seems like you might get the best of both worlds.
We include expert consensus rankings in our draft tool to give users the option to use projections or rankings.
I guess what I am saying is that it might not have to come down to only using projections, or only using rankings. Use both.
If more = better for “wisdom of the crowd”, then there are way more rankings available than projections. In that case rankings should be more accurate in predicting how many points a player will score relative to another player in the same position. But, rankings are limited since they don’t tell you the actual points or point spread between players, and can’t compare across position types.
Projections can be calculated using your method, sorted by position type in Excel, then all player names can be deleted and replaced by the players from rankings (e.g. sort WRs from high to low point projections, delete player names/teams, paste in WR player ranking–repeat for each position and re-sort by VORP).
Edit for above: should read “paste in WR player by ranking”
https://fantasyfootballanalytics.net/2016/04/accuracy-of-rankings-vs-projections.html#comment-14958
I am not following how the referred posts relates. Are you saying that using a handful of projections is more accurate that using the dozens of rankings from FantasyPros in predicting the WR1, WR2, WR3, etc.?
I was linking to a comment (not the post) in which I discuss that expected points by position rank aren’t that accurate because they vary considerably from year-to-year. For example, there is a 60+ point difference in the top RB from 2008 to 2009 (according to ProFootballReference). This is just one example, but there are many others. Also, we’ve already shown that projections are more accurate than rankings 🙂
HI Isaac,
It strikes me from looking at my own data (I am not sure the data that you used) that there is a large potential error in this analysis. If you simply take each position and plot Fantasy Points vs. ADP you see that the relationship is quite nonlinear. Projected points are intended to have a linear relationship with actual points (identity relationship to be exact) but ADP does not. Of course R^2 will be lower for ADP/Rankings when you are fitting linear models to a nonlinear relationship. What happens if you use a simple linear transform of the data (log transform, etc.) to linearize the relationship first?
Hey Wes,
Good question. We make the scripts available so users can replicate our findings and examine any number of alternative models and approaches. I’d argue that, even if you find that [insert nonlinear relationship here] better accounts for the association, it’d be hard to justify that people use that nonlinear relationship when making mental judgments of ADP. At the very least, projections have a clearer meaning in relation to points (i.e., they have greater face validity), and therefore are more useful.
Hope that helps,
Isaac
Does this hold true historically?
I can never find Jason Croom. TE BUF. in the projections
This was a fascinating read! I never really considered the differences between rankings and projections in depth. It’s interesting to see how each can influence decisions in different ways. I’d love to hear more examples of where one has significantly outperformed the other. Thanks for the insights!