Dr. Green and White Sports Authority

Stat Geek Analysis of MSU vs. Stanford I will be the first to admit that I am not world’s best X’s and O’s guy.  But, I am good at math, so I thought that I would take a look at the stat match-up between MSU and Stanford, including looking at each team’s opponents and see what it looks like.  I was able to pull rushing and passing data for all Div. 1 teams from the NCAA website and analyze it.  I general broke down four main statistical areas: rush offense, pass offense, rush defense, and pass defense (all on a yards per attempt basis to normalize for style of play as much as possible). Here is the synopsis:  In general, Stanford is the most balanced team MSU have faced all year, finishing no worse than 31 st in any category, but it is not clear that they are better than OSU.  Statically, Stanford is roughly equivalent to Indiana on offense and Iowa on defense.  As for MSU, statistically, we are actually one of the worst offenses they have faced...

It is hard to believe that 12 months have already past.  My baby daughter has grown into a 1-year old toddler, which means it is July again.  The MLB All Star game has faded in the rearview mirror. The long, dark summer of baseball is beginning to wane, which signals that college football is only about a month away.  In the Fanson household, that can only mean one thing: it is time for spreadsheet.  I introduced the spreadsheet 2 years ago, but just to refresh everyone’s memory, I will now insert the same explanatory paragraph that I used last year.  I starting putting the spreadsheet together in grad school and I have been making steady improvements to it over the years.  I used to just track scores and standings, but over time I have refined the algorithms to predict game outcome / point spreads and generate power rankings.  As the 2013 season approaches, I have once again inputted the schedule information into the latest version of the spreadsh...

It is that time of year again!  What time you ask? Fanson baby watch 2012?  Well, yes, but it is also time once again to break open the football spreadsheet.  I introduced the spreadsheet last, year, but just to refresh everyone’s memory, I starting putting the spreadsheet together in grad school and I have been making steady improvements to it over the years.  I used to just track scores and standings, but over time I have refined the algorithms to predict game outcome / point spreads and generate power rankings.  As the 2012 season approaches, I have once again inputted the schedule information into the latest version of the spreadsheet and am taking an early look at what to expect.  If I take the pre-season rankings for each team, convert that to an estimated power ranking, and simulate the season by correcting for a teams performance at home or on the road (roughly a 3-point advantage for the home team), I have been able to predict the final record of ...