- Home Archives for August 2011
It's a much more difficult question than it first seems. Averaging the performance of all the recent QBs by age doesn't work. A survivor bias ensures that only the successful QBs stay in the league long enough to have their stats in the sample. Another complication is the the steady inflation of passing stats over the years. In this post, I'll try to tackle those problems to better understand how QB performance is affected by age.
Adrian Peterson is currently the highest paid RB, due to make $11 million this season, which is probably two to three times too much. RBs, and the running game in general, do not have the impact on wins and losses the same way the passing game does. But more importantly, the spread between the best and the mediocre RBs is much smaller than the the spread among quarterbacks.
We can't quantify the value of a player the way the MLB analysts can, with Wins Above Replacement and other stats. But we can at least make some back-of-the-envelope, order-of-magnitude estimates.
ESPN has a talented new analytics team, and their first foray into football is their Total QB Rating. It seems the first thing anyone does when they get into advanced football stats is to create their own QB rating system. The QBR is a major improvement over the NFL's traditional passer rating, and there are a lot of things I like about it, but it's not perfect. I'll try to summarize my understanding of the stat, and then I'll list the things I like about it and the things I don't like so much. As we say in the fighter pilot business--the goods and others.
According to ESPN's own explanation, the stat is based on three primary concepts--Expected Points, Win Probability, and division of credit. As I understand it, QBR begins with a QB's Expected Points Added for each play in which he was directly involved, including both pass plays and runs. It modifies each play's EPA value according to a clutch factor, which is based on Win Probability (WP). Here, I use something similar known as Leverage Index (LI). LI is the ratio of the potential swing in WP for a play compared to the average play's potential swing in WP. For example, an LI of 3 means that a play is 3 times more critical to a game's outcome than the typical NFL play. (You can find any play's LI on the interactive WP graphs here by hovering your cursor over the graph. I still consider it a 'beta' stat because I haven't settled on a final, single definition of potential success and failure for every play.)