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Professor who developed one of computer models for BCS speaks (December 11, 2003)
Discussion ThreadPosted 11:56 a.m.,
December 12, 2003
(#23) -
Tom T
"Also, one thing that bothers me about the strength of schedule component is that it keeps adjusting itself throughout the season beyond what seems relevant. For example, USC lost points when Syracuse beat Notre Dame because USC played Notre Dame two months ago. But did USC really get perceptively weaker when SU beat ND? Or to put it another way, if USC and LSU were scheduled to play each other, and then SU beat ND, would the betting line on USC/LSU change as the result of this seemingly unrelated game? I seriously doubt it."
I think the idea is that, as you see how an opponent does against other teams, that tells you more about how impressive your win (or loss) against them was. Suppose, for example, that Team A beats the number 1 team in the country in September. People would see that and think, wow, that Team A must be pretty good, they just beat the #1 team in the country.
But, now, suppose that a couple of months later, this (now former) #1 team in the country lost three straight games to fairly mediocre competition. All of a sudden, that win by Team A doesn't look so good -- it wasn't against the best team in the country, it was against a mediocre team that was severely overrated.
To a lesser degree, this is what happened when ND lost to Syracuse. Assuming the computer dealt with this correctly, basically ND's loss to Syracuse made ND look worse, so, therefore, USC's win over ND was less impressive, because it was against a worse opponent than one might have thought at the time that USC won that game. That seems reasonable to me.
A method for determining the probability that a given team was the true best team in some particular year (January 6, 2004)
Posted 11:56 a.m.,
January 6, 2004
(#2) -
Tom T
Guy,
One way to start to get at your question is to calculate the expected number of WS champs with the best record. The most straightforward way to do that is just to calculate the expected WS champs for the best team year-by-year. For example, the 1990 A's would have been expected to win 0.543 World Series that year.
If you add these up for every year from 1990 - 2002 (except 1994), you would expect the best team to have won 5.245 World Series over this time period. In fact, they won 1 ('98 Yanks). On the other hand, 5 of them did participate in the World Series (although we would have expected more, since the probability of making the World Series is greater than the probability of winning it).
I'm not sure what to do with those numbers except to say that the "best teams" in baseball do certainly look like they win the WS less than you'd expect.
A method for determining the probability that a given team was the true best team in some particular year (January 6, 2004)
Posted 9:31 a.m.,
January 7, 2004
(#12) -
Tom T
Guy,
One thing to remember is that, prior to 1997, the AL and NL teams never played each other and had no common opponents, so, really, all you can do in that case is identify the probability of being the best team in the AL and the probability of being the best team in the NL, unless you have some basis for making an assumption about the relative strengths of the two leagues.
In fact, from 1990 - 1996, 7 of the 12 World Series participants were identified by this system as having the highest probability of being the best team in their own league. I think that's actually pretty good.