[stupac2]

Of course, that never actually happens, so the Casino will adjust the payouts accordingly, giving better payouts to teams that haven't attracted enough money, and worse payouts to those that have attracted too large a share of the betting money.

Right, but WiM's contention is that this adjustment process means that the odds proffered end up being very close to the "wisdom of the crowds" estimate for what the odds actually are. The thing is, though, that this depends on their being both "chumps" (or "homers") who bet on their team no matter what, and "sharks" or people who just want to play the odds and make money. It's not really clear to me that this will balance out into an efficient market (both because I'm sort of skeptical that any market is actually efficient in the real world, except perhaps the largest betting markets, maybe these types of things are big enough but I'm not sure that college game spreads are big enough). That is, the sharks don't necessarily need/want to bet against the homers until the odds are balanced, just until the odds are no longer completely stupid.

So, take a classic homer team like USC. The casino knows that they get a lot of homer bets, so they put they give them artificially high odds knowing that the homers will bet no matter what, but the sharks will only be tempted if the odds are particularly egregious. Where does this balance out? If the market is completely efficient then it'll balance at the true odds, but do we have any particular reason to believe that there's enough shark money to counteract the homer money? I have no idea, and I don't think anyone else does either. The only way to find out (other than opening the Vegas books, which, lol, good luck with that) would be to do a retrospective study to see if certain teams are consistently over-/under-valued, but I'm not sure if even that would do it in terms of this sort of odds (it would work with spreads because there are so many data points, but pre-season championship odds don't have the same amount of information).

[stupac2]

Of course, that never actually happens, so the Casino will adjust the payouts accordingly, giving better payouts to teams that haven't attracted enough money, and worse payouts to those that have attracted too large a share of the betting money.

Right, but WiM's contention is that this adjustment process means that the odds proffered end up being very close to the "wisdom of the crowds" estimate for what the odds actually are. The thing is, though, that this depends on their being both "chumps" (or "homers") who bet on their team no matter what, and "sharks" or people who just want to play the odds and make money. It's not really clear to me that this will balance out into an efficient market (both because I'm sort of skeptical that any market is actually efficient in the real world, except perhaps the largest betting markets, maybe these types of things are big enough but I'm not sure that college game spreads are big enough). That is, the sharks don't necessarily need/want to bet against the homers until the odds are balanced, just until the odds are no longer completely stupid.

So, take a classic homer team like USC. The casino knows that they get a lot of homer bets, so they put they give them artificially high odds knowing that the homers will bet no matter what, but the sharks will only be tempted if the odds are particularly egregious. Where does this balance out? If the market is completely efficient then it'll balance at the true odds, but do we have any particular reason to believe that there's enough shark money to counteract the homer money? I have no idea, and I don't think anyone else does either. The only way to find out (other than opening the Vegas books, which, lol, good luck with that) would be to do a retrospective study to see if certain teams are consistently over-/under-valued, but I'm not sure if even that would do it in terms of this sort of odds (it would work with spreads because there are so many data points, but pre-season championship odds don't have the same amount of information).