While football season is behind us, the amount of money generated by the NCAA and its schools remains of interest to us. Thanks to our friend Wesley Turner, we have acquired data on all NCAA Division I schools for total football revenue and expense. Much of the data can be further investigated at USA today’s website, and when available at Equity in athletics .
As would be expected, the big name football factories spend the most money on football related expenses, but the amount of profit that is generated on average per year is staggering. Over the 7 year period of 2003 till 2009, the top 10 schools (Texas, Georgia, Florida, Notre Dame, Michigan, Alabama, Penn State, LSU, Auburn and Ohio State) generated more than $30 million in profit per year. Texas which generates on average almost $50 million a year, has seen incredible sustained growth. In 2003, their profit margin was $34.6 million. In the year 2009? $68.8 million!
We have spent the last several days filling out our NCAA tournament brackets (as most of you probably have as well). This post looks at which teams have played competitively versus higher ranked foes, and which teams played poorly versus lower ranked opponents.
We investigated the number of times a given team has lost or won in an upset. Upsets were defined as whenever a lower seeded defeated a team with a higher seed. While it is very possible that a 1 seed might lose to a 2 seed, an 8 seed to a 9 seed, we took into account both the seed differential during the contest as well as the point differential. Compiling data from the past 5 years of tournament play, as well as using our handy Matlab tool kit, we came up with the following “biggest losers” and “biggest winners”.
March Madness is upon us, and to get a taste for your brackets choices, play around with the following Java applet to see the historical win percentages for each round of play. A “NaN” indicates that that matchup has never happened before (i.e. a 16 seed winning the first round will create a “NaN” for the 3rd round winner). For complete data see the post on NCAA tournament seedings.
The NCAA tournament is coming up in a few weeks with Selection Sunday just down the road. This means one thing… March Madness pools! Looking at historical data, the selection committee has done an excellent job in their seedings…
At Matlab Geeks we crunched through all 15 weeks of AP voting and tabulated how college football teams were ranked throughout this season. Non-surprisingly, the automatic BCS qualifying conferences had the most number of teams ranked throughout the year, with a great portion of them coming from the Big 10 and SEC. We also looked at our version of “strength of schedule”. We investigated each Division 1 team and looked at their week by week opponent and how many votes that opponent received the week they played and also during the final week of voting. Oregon State ended up having the toughest schedule, while several teams played the entire year without playing a single team that received any votes, much less any ranked teams. Read on for some pretty graphs/charts and some Matlab tips for how to perform the analysis.