ESPN.com produces some excellent analysis. Several of the
writers working there can slice and dice data in ways that reveal
thought-provoking, insightful conclusions. I have a weakness, however, for those
delightfully qualitative pieces known as power rankings.
Even though I know that I should know better, I read them
every week. I literally cannot stop myself from clicking on that link (figuratively,
of course – I could quit if I really wanted to). Imagine, then, just how little
control I had when I saw the NFL
Future Power Rankings link on the lower right side of my screen. These
rankings purported to give a quantitative look at the prospects of each team in
the 2015 season.
I started to suspect something might be amiss when I
looked briefly at the methodology.
The methodology was to poll some of ESPN’s analysts and produce a weighted
average of the results. There were instructions given for each category that
seemed to make sense. Don’t consider players over 27 except at QB; look at the
2012 draft class, the team’s picks in the 2013-15 drafts and their track record
in the draft.
In all, the five categories included Roster (ex-QBs),
QBs, Draft, Front Office and Coaching Staff. The 4 analysts – Trent Dilfer, Mel
Kiper (he of this
track record), Gary Horton and Matt Williamson – voted 1 to 10 for each
category and that was the extent of it.
The results of the survey looked all too familiar. There
was Green Bay at the top, followed closely by New England, the New York Giants,
San Francisco, Pittsburgh and Detroit. Not until seventh was there a team,
Philadelphia, that failed to make the playoffs. Three of the four conference
championship game participants made the top four. It did not appear to be significantly
different from simply ordering teams based on their 2011 record. I decided to
take a look at whether current year results are really that highly correlated
with results in four years?
What’s the
correlation, Kenneth?
Now that these rankings had me going (before I even saw my
Cleveland Browns ranked dead last) I set about analyzing them. The Future Power
Ranking (FPR) number that they produced, a weighted average of 1 to 10 ranks in
five categories to produce a 0 to 100 scale, had an average of 61.1 and a
standard deviation of 13.7. To make this comparable with winning percentage –
the statistic I would consider the parallel to power rankings – we can recenter
it around a mean of .50 with a standard deviation of .205, the actual mean and
standard deviation of winning percentage in 2011. Thus a team with an FPR of
74.8 would have a predicted 2015 winning percentage of .705, both one standard
deviation above the mean.
The figure above shows the implied winning percentages based
on FPR on the vertical axis and 2011 actual winning percentage on the
horizontal axis. The r-squared, as suspected, is relatively significant at 0.65
with a correlation of 0.80. This means that more than half of the variation in
FPR-implied winning percentage is explained simply by looking at a team’s
performance in 2011.
This histogram demonstrates the implied change in
performance from 2011 to 2015 in terms of wins. The FPR has most of the teams
(53%) within +/- one game of their 2011 record. Now all we have to do is see if
this is justified.
Salary cap-era
persistence of performance
The salary cap, put in place for the 1994 season, should
have a significant effect on the persistence of team performance. Teams that
assemble outstanding collections of players will see some of them poached as
they reach free agency and the team cannot afford to keep them all. Also, I
didn’t want to copy records from all the way back to 1920, so the salary cap
era will be our set. This data set will offer 14 different four year periods
from 1994 to 2007 with paired year 0 (e.g., 2007) and year 4 (e.g., 2011) results.
The figure above shows the winning percentage in year 0
along the horizontal axis and the winning percentage in year 4 along the vertical
axis. The r-squared is 0.01. This relationship is effectively meaningless and
the graph highlights that fact with as the values are all over the map.
This histogram demonstrates the misalignment between the
actual changes over four years (in green) and the changes implied by the ESPN
Future Power Ranking (in blue). Of particular note is that the actual data puts
42% of teams changing by four or more games in year 4 as compared to year 0
while the FPR-implied winning percentage has only 9% of teams changing by that
much.
Looking at a three-year trailing average of correlation
over time, there seems to be a small trend towards higher correlation between
winning percentage in year 0 and year 4. There are, however, reasons
to believe that the trend may be reversed in the coming years based on changes
in the 2011 collective bargaining agreement, and it is still well short of the
correlation implied by the FPR.
Here we go
Brownies, here we go!
ESPN offered an interesting idea with the NFL Future
Power Rankings. The data suggests, however, that their experts are reading too
much into current year performance. They need to take the Future Power Rankings
back to the drawing board and reevaluate how to predict future performance so
that I have something to give me a little more hope that Cleveland might
finally be on the right track.
Specifically, they don’t seem willing (able?) to project
which teams will have significant swings in the future. The FPR settles for defining
the future elite as the current elite and misses the opportunity to provide
insightful reasons for which teams will have big changes.
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