As you look over those two .pdf files linked from the NCAA's website in the previous sentence, you will notice that some non-BCS conferences received BCS money, and that some individual schools receive BCS money (such as independents like Notre Dame, Army and Navy). This presents some questions as to how to calculate the Gini coefficient (measure of income inequality or in this case revenue distribution inequality). Should I include all who have received BCS money (both BCS conferences, non-BCS conferences and individual teams)? If so, then this might give a biased picture, since individual teams and non-BCS conferences will normally receive much less than an entire conference leading to a higher level of income inequality that in reality. So how should I account for this problem? I decided that I would also calculate the Gini coefficient two additional ways. One is that I will include all non-BCS conference and all individual teams as one category as a measure of revenue distribution inequality, and the other is that I will only include the BCS conferences and BCS independent teams - with the independent teams aggregated into one category, much as I do for the NCAA FBS Production Model.
Here are the measures of BCS revenue distribution inequality from 2004-05 to 2010-11.
|Gini 1||Gini 2||Gini 3|
As you can see including both teams and BCS and non-BCS conferences (Gini 1) has a much higher level of BCS revenue distribution inequality than if I aggregate all the teams and non-BCS conferences into one group (Gini 2). There is not much of a difference between only BCS members when aggregating the independents into one group (Gini 3) with BCS revenue distribution measure Gini 2.
Either way, there is some BCS revenue distribution inequality, it is lower than what I found among the 70 participants in my blog about the NCAA bowl inequality - linked at the beginning of this blog.