I paid for the site, yet it says I am still in active. Does anyone know how long this usually take?

I paid for the site, yet it says I am still in active. Does anyone know how long this usually take?

Yeah I was kind of toungue in cheek Pete. Every year we get more model brackets and honestly I love that best. Its like the good old "dot system" used in horse racing for years. Lots of models to analyze saves so much time in going it over yourself. There just has to be one guinea pig and you are it my friend. lol

Good job as always. Cheers

Yeah I was kind of toungue in cheek Pete. Every year we get more model brackets and honestly I love that best. Its like the good old "dot system" used in horse racing for years. Lots of models to analyze saves so much time in going it over yourself. There just has to be one guinea pig and you are it my friend. lol Good job as always. Cheers

Yeah...I'm gonna be dying by Monday moanin'...bear with me, Spooky. I'll get all the models done by Monday...just not sure when on Monday.

Yeah...I'm gonna be dying by Monday moanin'...bear with me, Spooky. I'll get all the models done by Monday...just not sure when on Monday.

Get some rest this weekend cause we are gonna be waiting for all your brackets to be completed first thing on Monday Morning. :)

Great stuff Pete

Get some rest this weekend cause we are gonna be waiting for all your brackets to be completed first thing on Monday Morning. :) Great stuff Pete

Efficiency ratings of top ten teams hit an all- time low—can madness be far behind?:

This morning, I took some time off from my final big number crunching push to revisit how the ten most efficient teams are doing. In a recent blog, I pointed out that the Pythag efficiency ratings of the top 10 tens gave a good indication of how predictable the tournament would be. Generally speaking, the higher the overall efficiency of the top 10, the more chalky the tourney. The lower the overall efficiency, the more upset- laden the dance will be.

Last year, the average Pythag of the top 10 teams was .9631. That figure was the lowest of any of the seven tourneys we studied. And guess what? Those top ten teams performed the worst in their tournament. In fact, the three years where the top ten teams had the worst Pythag (2010, 2006 and 2009), were also the three years when they had the lowest tourney winning percentage. Conversely, the two years when the top ten came into the dance with the highest Pythag rating—2007 and 2008—were also the most predictable tourneys.

So where do the 2011 top ten teams fall on this chart? Here’s where the blood comes in:



The last time I did this analysis on March 3, the 2011 top ten was better than last year’s bunch—and owned the same Pythag (.9638) as the 2009 teams. In the space of 11 days, the top ten has suffered a major hit. Last night’s abysmal performances by Purdue and Wisconsin and losses by Notre Dame and Pitt didn’t help. The average Pythag of the top ten is now down to an alarmingly low .9603. That means there will be blood in this upcoming dance—whether it’s Blue Devil or Buckeye or Jayhawk blood (insert Charlie Sheen joke here) is too early to tell. But I’m guessing that we’re in for another tourney of double- digit upsets.

After the field gets set, I compare the top 52 ranked teams (basically the top 13 seeds) in terms of Pythag with their historical counterparts. The shape of the two curves usually gives a good indication of what sort of tourney we’re in for. Last year, the curve showed weak top seeds and strong low seeds—just the formula for tourney madness.
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Efficiency ratings of top ten teams hit an all- time low—can madness be far behind?: This morning, I took some time off from my final big number crunching push to revisit how the ten most efficient teams are doing. In a recent blog, I pointed out that the Pythag efficiency ratings of the top 10 tens gave a good indication of how predictable the tournament would be. Generally speaking, the higher the overall efficiency of the top 10, the more chalky the tourney. The lower the overall efficiency, the more upset- laden the dance will be. Last year, the average Pythag of the top 10 teams was .9631. That figure was the lowest of any of the seven tourneys we studied. And guess what? Those top ten teams performed the worst in their tournament. In fact, the three years where the top ten teams had the worst Pythag (2010, 2006 and 2009), were also the three years when they had the lowest tourney winning percentage. Conversely, the two years when the top ten came into the dance with the highest Pythag rating—2007 and 2008—were also the most predictable tourneys. So where do the 2011 top ten teams fall on this chart? Here’s where the blood comes in: <IMG SRC=/ blog/ 11_ lastpythcheck.gif> The last time I did this analysis on March 3, the 2011 top ten was better than last year’s bunch—and owned the same Pythag (.9638) as the 2009 teams. In the space of 11 days, the top ten has suffered a major hit. Last night’s abysmal performances by Purdue and Wisconsin and losses by Notre Dame and Pitt didn’t help. The average Pythag of the top ten is now down to an alarmingly low .9603. That means there will be blood in this upcoming dance—whether it’s Blue Devil or Buckeye or Jayhawk blood (insert Charlie Sheen joke here) is too early to tell. But I’m guessing that we’re in for another tourney of double- digit upsets. After the field gets set, I compare the top 52 ranked teams (basically the top 13 seeds) in terms of Pythag with their historical counterparts. The shape of the two curves usually gives a good indication of what sort of tourney we’re in for. Last year, the curve showed weak top seeds and strong low seeds—just the formula for tourney madness.