I see what you mean. I presented my point in the form of a question. So here is my point. I don’t think the available information on lower level teams would necessarily lead to super accurate ratings. The information you provided regarding rankings being based on prior year results was very informative. For a team like GC with a bunch of new players this means early year rankings are even less accurate. Obviously the only way to settle this is a best of five series between GC and FH!
We agree in part. Prof. Massey agrees with both of us as to early season predictability being low. His program doesn't take into account changes in player or coaching personnel.
That said, his ratings are every bit as accurate for lower and higher rated teams. The
relative difference between, say, #4 and #14 should be the same for #204 and #214.
Here's something from his FAQ:
“Ratings are designed to reflect past performance, namely: winning games, winning against good competition, and winning convincingly. As a consequence, the ratings have some ability to predict the outcome of future games.
For many sports, I post predictions of upcoming games and monitor their success. In most cases, I would trust a computer's prediction over a human's. However, while this is often the most popular and entertaining application of computer ratings, it is not my primary purpose.
Predictions are obtained by extrapolating the analyisis of past performance to estimate future performance. Usually, the past is a resasonable indicator of what to expect in the future. However sporting events are to a great extent random, so upsets will occur. Furthermore, computer ratings are ignorant of many important factors such as injury, weather, motivation, and other intangibles. With this in mind, it is not wise to hold unrealistic expectations of the predictions.
The purpose of the Massey rankings is to order teams based on achievement. This objective may occasionally yield some surprising results: for instance having good teams from weak conferences ranked higer than one might expect. This is not to say that such a team is "better" than all teams below it. It is simply being rewarded for its success at winning the games it has played.
It is incorrect to assume that the Massey model is predicting that the higher ranked team should defeat a lower ranked team. Model predictions can be derived from latent variables, and may not agree with the rankings.”.
Massey Ratings FAQ
I've found that by January his programs are highly accurate, but not infallible, predictors of matchups between any two teams. Early in a season his ratings are generally useful indicators of direction and relative strength, but not better than the educated opinions of serious fans.