Win projections and regression to the mean

I get a kick out of win projections regardless of sport; not to pick on Peter King, but this is just the most recent in a long, long, long-standing tradition.

King picks no team in the NFL to have a record better than 12-4 and no team to have a record worse record than 3-13. At face value that may not seem like anything bizarre, but that would be a truly historic level of parity. Not since 2003 have either of those predictions come true-- no team finished below 3-13 during that season-- and the last time both of those conditions were met was in 1993. Basically, he's predicting a level of parity not seen in professional football in about twenty years.

When computer models run these things, you tend to find most likely outcomes. The problem is, when you've got 30+ samples of teams, something fairly unlikely is probably going to happen to somebody. There was a projection for baseball wins a few years back that predicted something like 8 teams to have exactly .500 records. Not only had that never happened (or even close), but the total number of exactly .500 teams was something around 8 over the previous 10 years.

I can understand why someone would predict this-- someone's more likely to remember a significant error (you picked my team to go 1-15 and they made the playoffs!) than a pretty-close prediction (boy, they sure showed you-- 11-5 instead of 9-7!). Nonetheless, I'd love to see someone step out on a limb-- and I'd have no problem with them trumpeting their prediction at the end of the season if it ended up correct.

Did Intrade Forsee Bin Laden's Capture?

Intrade might have foreseen the capture of Saddam Hussein, but it doesn't look like that was the case this time:

And the prediction market doesn't appear to be waiting around for a long-form death certificate to close the deal.

Intrade on on the Probability of Health Care Reform

Intrade on the probability that "A federal government run health insurance plan to be approved before midnight ET 31 Dec 2009"
Trade volume is about 12 thousand, and Intrade closed the day at just under 25%.

The narrative I am inclined to draw from it is that the expectations of his speech acted to improve the likelihood slightly, but after a day of analysis, the likelihood has returned to the pre-speech announcement levels.

Prediction Markets in Demand For Hospital Services

Interesting new study in the Journal of Prediction Markets:

Prediction Markets as a Medical Forecasting Tool: Demand for Hospital Services
By Rajakovich, David; Vladimirov, Vladimir
Volume 3, Number 2, August 2009 , pp. 78-106(29)

Background
This paper presents the outcome of a study conducted at the Royal Devon and Exeter Hospital in which a prediction market was established in order to forecast demand for services. To the researcher's knowledge, it does not appear that prediction markets have been previously utilized in a healthcare environment.

Purposes
The purpose of this study is to provide evidence for the effective use of prediction markets in a healthcare environment.

Methodology and Approach
The study was conducted over a period of one week, and involved sixty-five participants. Each was asked to provide an estimate for demand for services at the Royal Devon and Exeter Hospital. Characteristics gathered for each participant included level of education, occupation, directorate, number of years worked for the hospital, and number of years worked for the National Health Service.

Findings
The study confirms the effectiveness of prediction markets to forecast future events as overall hospital demand was forecasted with an error of only 0.3%. The prediction market was less successful in predicting demand for services for each department, which the researcher attributes to the small sample size and lack of diversity of participants. Additionally, only a very small percentage of the characteristics captured registered a statistically significant correlation with the accuracy of the estimate. Further studies should focus on different characteristics and/or use a larger sample size to either confirm or refute the existence of such characteristics.

Practical Implications
The findings of this work could potentially be used as an innovative way to augment the forecasting function for a wide range of healthcare facilities. With the preliminary success of this study to forecast demand, further research in the field is warranted.