Dr. Green and White Sports Authority

As the calendar reaches July and the college football preseason magazines begin to hit the shelves, I have an annual tradition of doing a simulation-assisted deep dive into the coming college football season.  Over the years, I have developed an algorithm and tracking spreadsheet that I use to generate in-season power rankings and projected point spreads. In the preseason, I have found that I can use the same algorithm to project the outcome of the full season, if I use preseason rankings to seed the math. Basically, I ask the question: if the preseason rankings are correct, what is the most likely outcome of the coming season , considering each team’s actual schedule and a historically reasonable probability of upsets, specifically when good teams face slightly weaker teams on the road? Now, I could (and have in the past) spend several paragraphs going into the details of my methodology, but the key points are as follows. This year, I used the average rankings from 5 separate sou

Around this time of year, the various pre-season college football publications start appearing on the shelves. For some time now, I have often wondered if there was a good way to evaluate how good or bad the various preseason rankings really are.  This year, I decided that I would try to figure it out.  Now, it would straightforward to simply compare the various preseason rankings to the post-season CFB playoff ranking, AP ranking, or coaches poll.  But, that only tells the story for about 1/3 of all Division 1, and I was looking for something a bit more comprehensive. From time to time, I have discussed and posted data based on an algorithm that I have developed to generate my own power rankings.  Since my method does assign a ranking to all 128 Div. 1 teams, is typically a reasonable predicter of Vegas spreads (more on that later), and since I also tabulate preseason predictions from various sources to support my annual preseason analysis (coming soon to a message board near you