RE: B12 vs P12: Tale of the Tape
Here is what they say are the advantages. of this method.
Advantages in this Method
First and foremost, the rankings are based only on results from the field , with absolutely no influence from opinion, past performance, tradition or any other bias factor. This is why there is no pre-season poll here. All teams are assumed equal at the beginning of the year. If you include some kind of human input, what's the point of a computer poll in the first place? Garbage in, garbage out.
NOTE: Bear in mind that because there is no pre-season poll, the early rankings will not look much like the press polls. The rankings are based on results so far within the season of play.
Second, strength of schedule has a strong influence on the final ranking. Padding the schedule wins you very little. For instance, Wisconsin with 4 losses finished the 2000 season ahead of well ahead of TCU with only 2 losses. That's because Wisconsin's Big 10 schedule was much, much more difficult than TCU's WAC schedule.
Third, as with the NFL, NHL, NBA, and Major League, score margin does not matter at all in determining ranking, so winning big, despite influencing pollsters, does not influence this scheme. The object of football is winning the game, not winning by a large margin. Now, other games have other metrics. In golf we have strokes; in texas holdem we have winnings; in NASCAR we have points standings; but in football, we have one simple overriding metric: did you win the football game?
Ignoring margin of victory eliminates the need for ad hoc score deflation methods and home/away adjustments. If you have to go to great lengths to deflate scores, why use scores?
What about home/away? Though reasonable arguments can be made for a home/away factor, I do not know of a simple, mathematically consistent means of rating the relative difficulty of playing at the Swamp vs. playing at Wallace-Wade Stadium. The home advantage for some teams is simply more than it is for others. There are further complicating factors, such as home weather for a northern team in November vs. home weather for a southern team in August.
Even the pollsters seem to forgive or forget big scores or surprisingly close scores, home or away, after a few weeks. Usually, after a few weeks, a W is a W and an L is an L, as it should be anyway.
Fourth, in this method, only very simple statistical principals, with absolutely no fine tuning or ad hoc adjustments are used to construct a system of 120 equations with 120 variables, representing each team according only to its wins and losses, (see Ranking Method). The computer simply solves those equations to arrive at a rating (and ranking) for each team.
Fifth, comparison between this scheme and the final press polls (1998, 1999, 2000, 2001, 2002) proves that the scheme produces sensible results.
The fractional ranking discrepancy between my system and the polls varies between 0.200 and 0.298 in all cases, typically a quarter. In other words, a typical ranking difference between my poll and either press poll would be around 1 place at a ranking of #4, and around 5 places at #20. The press polls themselves vary between 0.037 and 0.095 over those years. So one might expect, for a given team, a ranking disagreement of about 1 in the top 15.
So the Coaches and AP pollsters agree with each other about 4 times better than they agree with me. However, one would expect that the Coaches and AP polls agree very well for a very simple artificial reason. The coaches read the AP poll, and the media voters read the Coaches' poll, so there is statistical feedback between the two polls, right or wrong. A computer scheme, like this one, does not read other polls.
The bottom line in these comparisons, is that my rankings have
agreed in all nine years with the media and coaches on the national champion,
agreed with the media and coaches on the top two teams in 8 out of 9 years
most often agreed on the top 5, and
agreed on the top 10 within a place or two,
which I call a remarkable success, given the radically different systems of ranking system in question. Since we don't really know the "true" rankings of the teams, we, in fact, are not able to say whether the media polls or my rankings are better, but the fact that the agreement is, in practice, quite good provides reason to believe that neither is totally out to lunch.
So, here we have a scheme to rank college football teams that is absolutely free from human influence or opinion, accounts for schedule strength, ignores runaway scores, and yet produces common sense results, which at the end of the season compare very favorably with human rankings (and other computer rankings). What else do you want?
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B12 vs P12: Tale of the Tape
