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MetaWorldPeace, WrathOfGod, and I were at the Philadelphia Snow Bowl that day, just up I-95 from Baltimore.

At kickoff:

And the three of us:

Hand and toe warmers: highly recommended

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Although I wasn’t able to get historical betting market data, I’d imagine that data is available somewhere, and if it were compiled then there’s no reason the same hotness logic couldn’t be applied to historical games too.

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Gambletron 2000 can only record data for games where there is an active betting market. In practice nearly every NFL, NBA, and major European soccer game has an active market, but some less popular sports don’t. College sports in particular vary: if there are big-name teams involved, they often have gambling markets, but smaller teams typically do not.

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Unfortunately Gambletron 2000 was only turned on in time to catch the final 4 games of the 2013 World Series, so any analysis of baseball would be based on a woefully small sample size. But Gambletron 2000 continues to collect data every day, so once the 2014 baseball season is underway then we can do better analysis of baseball.

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To be clear, if Boise State had a market-implied 40% probability of winning, that does not necessarily mean that Boise State truly had a 40% probability of winning. What it does mean is that there were two market participants, one of whom wanted to buy a contract on Boise State at a price corresponding to a 40% win probability, and the other of whom wanted to sell the contract at that price, and the exchange matched them up so that they could transact.

One likely explanation is that the buyer thought Boise had a higher than 40% chance of winning, while the seller thought Boise had a less than 40% chance, though we could imagine other reasons for the transaction – maybe the seller previously bought the same contracts at 10%, and she just wanted to lock in her gains and reduce risk, even if she thought Boise St at 40% was still an attractive bet.

If enough people participate in the market, the negotiated prices should take into account all available information. Roughly speaking, if it were so obvious that Boise State’s true probability of winning were 30%, there should be someone in the market willing to sell Boise State contracts at 40%, and continue selling until the price goes down to 30%.

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Intrade was particularly well known for its prediction markets on US Elections. If you look around you can also find markets on everything from the Academy Awards to the weather

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According to the Case-Shiller 10-City Composite Index, home prices have increased about 30% since they hit their low point in early 2011:

That sounds good, but at the same time, home prices remain about 20% below their 2006 peak, and are at the same level as they were in mid-2004. That means on average if you bought a house 10 years ago, it’s still only worth what it was when you bought it.

Furthermore, the number of home sales remains historically low:

The annual rate of repeat sales is still 45% lower than it was at its peak in 2006, and is comparable to the rate of sales all the way back in 1991, more than 20 years ago!

It’s notoriously difficult to measure home prices, because homes are relatively illiquid and don’t change hands very often, but repeat sales indexes like Case-Shiller are about the best we can do, and they suggest that the national housing recovery has a long way to go before it reaches the previous peaks

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