These are correlations of various college football and men's basketball rankings specifically comparing early weeks' individual rankings with Kenneth Massey's comparison pages' most recent average (mean) rankings. The intent is to show which individual rankings most accurately predict later consensus as represented by the average rankings.
Links to the results of these correlation calculations are at the bottom of this page. The input data is taken from Kenneth Massey's comparison pages:
This explains the pages linked below. You need to be familiar with Kenneth's comparison pages to make sense of them.
Example lines in my pages:
DEN Week10 36% 921 DEN Week11 48% 938
DEN designates the ranking, the same abbreviation as Kenneth's comparison page.
Week10 is the week within the season, the number matching those in Kenneth's historical comparison-page URLs.
921 is the correlation between "DEN" for week 10 and the current "consensus", i.e. the ranking listed on Kenneth's current comparison page derived from the average (mean) ranking.
36% is a percentile, indicating "DEN" had a higher correlation than 36 percent of the rankings included on the week-10 comparison page. The number actually represents the percent of rankings this one beat beat so the highest number is typically in the 95%-98% range (since it didn't beat itself) and the lowest 0%.
Besides comparing all the individual rankings from Kenneth's page, I also threw in some other rankings. For lines with the first column containing:
Consensus correlates earlier weeks' consensus with the current consensus. (By "Consensus", I mean the ranking as the teams are listed on the comparison page, derived from the mean of the individual rankings.) You can see how various individual rankings' predictive ability compares with the predictive ability of the consensus of all rankings. In a typical week it beats almost all individual rankings.
Con2001 (or whatever year) correlates the previous year's final ranking with this year's current ranking. It does NOT use each week from the previous year: only the previous year's final ranking. However, it is listed against each week to show what percentile it achieves as compared to that week's individual rankings. I originally had this thought: "I'll bet the same teams are typically on top every year and last year's consensus ranking might stack up very well against the rankings we all produce, especially in the early weeks". That proved to be false since it shows a low percentile even the first week. I don't know what folks use to initialize their data but it appears to be better than simply taking the previous year's rankings.
For each sport, there are four pages that are calculated with slight differences.
Within each page there are four sections.
As I said above, when I applied my correlation formula in a similar manner to that on Kenneth Massey's comparison page, I haven't been able to reproduce his numbers though mine are generally close to his. Another issue is that the procedure/formula I use does not handle unranked teams in a reasonable manner. Thus you will see negative numbers for some of the correlations when it is only a partial ranking such as AP and USA, and I suppose this is an artifact of the particular formula I use and how I apply it to incomplete rankings.
This doesn't explain why I can't reproduce Kenneth's numbers because differences show up for rankings for which that is not a factor.
Also, I list a "concordance" for each week. This formula also assumes a ranking from 1 to N but has been applied to data that doesn't fill this requirement, thus is a little off.
From Kenneth Massey's Football Comparison 2003/2004
fb-corr-25.html: top 25 only
fb-corr-average.html: against mean ranks
fb-corr-miss.html: with missing ranks filled in
From Kenneth Massey's Basketball Comparison 2002/2003
bb-corr-25.txt: top 25 only
bb-corr-average.txt: against mean rank
bb-corr-miss.txt: with missing ranks filled in
-John Wobus, 9/8/03