Methodology

Why?
and
How?

That's the two main questions that are
brought up over and over as I discuss my
new rating system and its results. Why do
we need another ranking system? How
does the ranking system really work?

First, the why.
The problem with college football is that
there are only a limited number of games
and teams vary greatly in strength of the
competition they play. You'll see many
try to get around this by opining on what
teams they think are the 'best,' pointing
out records v top25/top30/top10 or some
other level according to some poll, looking
at conference and/or road records, or
quoting some esoteric strength of schedule
that is often just a linear weighting of
opponents' computer ranking or based on
opponents' win percentage. This always
struck me as a very poor way of doing
things. I came across the colton index for
NCAA bball and its objections to the rpi's
use for that game. Many things in that
complaint struck a chord in me. What really
matters is how tough it is to win or lose
given a schedule. A linear rating is very poor
for that. For instance, a home favorite of 21.5
wins about 94.7% of the time while a home
favorite of 27.5 wins 97.5% of the time. That
isn't much of a difference for playing a team
that is 6 points better than another. Compare
that instead to a home favorite of 3 points
winning 54.5% of the time verse a 9 point
home favorite winning 74%. The same 6 point
difference is HUGE as far as the difference
between winning and losing. The system
advocated in this blog tries to play upon that
difference to point out whom are the best
teams in wins and losses. While arguing who
is/are the 'best' teams is a fun topic and leads
to interesting debate, the champion in nearly
every sport is given to the team with the best
win/loss records. Champion trophies are not
given to the team that 'experts' think is the
'best.' This rating system tries to reward the
teams that earn it on the field!

Now, for the how:

1) (edited in italics 10/20/08) Each team
is ordinally ranked 1 to 120 following the
massey combined rankings. Massey
combined is a system that uses weighting
of every available poll to create a consensus
poll. For every ranking, I gather that ranking's
sagarin overall score. Sagarin overall is the best
known computer evaluation system and the
most reliable from everything I've seen and used.

2) I then pull out the rating for the a base
level team according to sagarin predictor.
When trying to pick out the top teams, I've
compared to a #5 team. If I was looking
at the differences between teams about
number 20, I'd use the #20 team's score
as a baseline.

3) (edited in italics 10/20/08)
Next, I construct a ex post facto 'spread'
for each game by taking the difference
between the baseline ranking and each
opponent's sagarin predictor and add or
subtract a xxblanket 3xx point home-field
advantage. Beginning 2008, the home-field
advantage is no longer a blanket 3 points.
Instead, the HFA listed by Phil Steele for
each individual team will be used. These
are available in Phil Steele's yearly guides.
Phil Steele is a well known and respected
college football guru.

4) From there, I convert the 'spread' into
a win pct by comparing the 'spread' to a
database that has the actual win pcts for
each game played at that spread in college
football from 1993 to 2006 (ty to goldsheet
for that info).

5) After obtaining win pcts for a baseline
team against each team on the schedule, I
just use simple math to project the average
amount of wins the baseline team should
have against that schedule.

6) I then subtract the projected baseline
team's win total from the actual win total for
the specific team under consideration to
obtain a result for how many wins a team
has outperformed a generic baseline team.

7) For giggles, I go further and work through
every possible combination to see what would
a baseline teams' win total look like against
that schedule for all possible outcomes.

It's time for a ranking tool that isn't clouded
by 'brand name' schools or preseason polls.
I'm not arguing this ranking identifies the
'best' teams. I am arguing that this ranking
does a great job and should be a tool in
identifying the teams that have proven it on-
the-field with win/loss results.