I am not a computer programmer. I am a college FOOTBALL FAN. I put the FANATIC in the fan. I’m also a CPA who uses spreadsheet programs daily. I’ve come up with a model for determining the power ranking of the Division I teams for the entire season. I did this for myself and for other football fans. I’m not trying to impress anyone or score a bundle with the bookies. I just wanted to develop a model that makes sense.
This is a “computer” power ranking because it was prepared using a computer spreadsheet program. In theory, this could have been done on paper. Like I mentioned earlier, I am not a computer programmer, so, if I used any boolean equations, it’s purely accidental.
If you’ve looked at these results in the past, you may notice a few changes. The changes include expanding the rankings to cover FBS and FCS teams, having a static strength of schedule (SOS) formula, expanding the formula for winning and losing games points, expanding the historical adjustment formulas, adding an additional source of points and changing the formulas for home/away and margin points are calculated.
The biggest change is that I’m now ranking all of the FCS and FBS teams. I didn’t want to do this, but Bama made me do it. Their schedule the past few years were so weak, that it simply threw off my results. Plus, with several teams jumping from FCS—I’m writing 1-A and 1-AA from this point forward, to 1-A from 2013-2015, I needed a way to rank them. To adequately accomplish this, I had to go all the way back to the beginning of the rankings and add all of the teams and their results. This is why I stopped publishing the results mid-season last year. Part of the reason I did this was with the old method, I tried to determine a general SOS factor weekly for 1-AA teams. Not only was it nearly impossible, it was impractical and not fair to the 1-A teams that played the relatively tough 1-AA teams. This required me to expand the current equations and enabled me to add the current SOS formula, which is a hell of a lot better than what the BCS said they used.
The SOS formula is calculated by taking a team’s opponents’ total game points from week 2 onward, subtracting the impact of that team’s game from the total, dividing it by the number of weeks that have passed in the season, and adding all of the amounts for the opponents played so far together. Much better than looking at a team’s opponents’ winning percentage and combining it with their opponent’s opponents’ winning percentage like the BCS did. Especially when they were excluding the games played against 1-AA teams. The reason this is better is because many weaker schools play one or two strong teams and many weak teams, and they often play the same teams. These weak teams may have a decent record against their conference mates, but it doesn’t mean that they are a strong team for it. The result of a formula like this—Northern Illinois getting waxed by Florida State in a BCS bowl.
The new source of points is a formula that awards/subtracts points based on its opponent’s current ranking. The other formula of assigning points based on the teams’ relative ranking is also being used. Like all of the computer rankings, teams that win are rewarded and teams that lose are punished. Using these formulas in conjunction further rewards teams that beat better teams more than teams that beat sorry teams, and losing to better teams doesn’t cost as many points as losing to sorry teams.
I really did not want to add preseason rankings, but I realized that not doing so would mean that a win over Alabama State in week 1 would be worth as much as a win over Alabama, and I couldn’t have that. The preseason rankings are based on, but not exactly equal to, the historical composite rankings for each team over the past four seasons. Now, in these rankings, no team is protected by their early ranking. What I mean by this is that this year’s preseason number one will not stay in the top 10, or possibly the top 100 if it loses in Week 1. Even if it wins, another team or thirty teams could pass by them with better wins.
Formulas for home/away and margins are intertwined and depend on relative ranking of the teams. Teams will get points for winning away and/or winning by 17 points or greater. Losing at home and/or by more than 16 points will cost additional points. The amount of points depend on where this team and its opponent are ranked.
Another HUGE change is in the historical adjustment. I decided last season to switch from a per conference adjustment to a per team adjustment. This was also a huge amount of work, but I want to present the most accurate results to you as possible.
I hope you enjoy watching the results as the season unfolds.