Tradesports.com’s market for which bubble teams would make it to the NCAA Men’s Basketball Tournament mis-predicted three selections. This performance ties for last among the selections of thirty experts. The top performer was The Bracket Project, which wrongly predicted only one team, Syracuse instead of Arkansas. The consensus opinion of the thirty experts wrongly selected two teams, selecting Syracuse and Drexel instead of Stanford and Arkansas. Perhaps the most followed bracketologist, Joe Lunardi of ESPN also wrongly selected the same two teams as the consensus opinion. Tradesports.com’s market gave a higher probability of being selected to Syracuse, Drexel, and Kansas State in comparison to the selected teams Illinois, Old Dominion, and Arkansas. None of the thirty expert selections missed more than three teams. The chart below lists prices for bubble teams on Tradesports as of 5:45pm, just 15 minutes before the selection show. Of course, this sample is way too small to make any general conclusions about the accuracy of markets versus experts, but score one for the experts.

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• Deep-Pocketed Manipulators are a Prediction Market’s Friend.
• Evaluating Probabilistic Predictions — David Pennock Edition
• Drawing a parallel between our reluctance to seek advice and the experts’ reluctance to take the market-generated probabilistic predictions in an un-discriminating, un-critical fashion
• Secrets of an Inkling Top Trader: Spotting Riskless Arbitrage Opportunities
• The Sim Exchange’s predictions more accurate than Lazard Capital Markets and Wedbush Morgan’s ones.

There’s an important difference between shares of ownership in real companies and these game shares. Shares of ownership in real companies have intrinsic value. Even for stocks that don’t pay dividends, shares of a real company represent ownership of the company’s assets. Thus, a stock’s price can’t fall too far below the company’s liquidation value because a smart trader could buyout the company and sell off its assets for more than the share price. Doing this makes money. I don’t think this property applies to the game shares since they don’t seem to be claims on anything but the ability to sell off the shares to someone else.

The simExchange seems like an excellent example of Keynes’ beauty contest view of speculative markets. If there are naive traders who believe that shares have value based on actual game sales, then strategic traders will try to anticipate what naive traders will believe. Even though strategic traders know the shares have no intrinsic value (no dividends and no way to liquidate based on actual sales), they will trade to anticipate what naive traders will believe about sales. Thus, even though game shares have no intrinsic value (even in play money terms), as long as there is some level of belief that prices do correspond to sales, strategic traders will enforce this view.

I would be interested in a test of Shiau’s claim that “A stock’s price on the simExchange corresponds to the lifetime worldwide sales of a game, in which 1 DKP corresponds to 10,000 copies sold.” I could see this statement being basically correct if traders perceive that prices actually work this way and perceive that others perceive that prices actually work this way. Do the market makers try to enforce this connection? How do market makers on the exchange set their prices?

Previous: Robin Hanson on the Sim Exchage and The structure of simExchange game stocks

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• Keith Jacks Gamble: simExchange is somewhat OK, but will remained confined in play-money land.
• The structure of simExchange game stocks
• Why should I join the simExchange?
• An invitation to join the simExchange beta
• The simExchange on July video game sales

Someone pointed out to me that Protrade has posted their top 5 impact plays of the Super Bowl. But note that they derive the probability impact of each play from an unspecified algorithm. This algorithm estimated that the Bears had a 50% chance of winning at the start of the game, which is far from the probability implied by the Las Vegas odds. These Las Vegas odds have proven over an over again to be as accurate as any other measure. My analysis uses a market-based measure of the probability impact of each play, which builds in how a play affected the market’s expectation of future plays. For example, Protrade’s analysis estimates that Hester’s TD return (their 2nd highest impact play) gave the Bears a 70% chance of winning (20% increase), whereas my analysis estimates that the Bears had a 42.75% chance of winning (10.25% increase, just out of my top 5) following the TD. I think the market correctly anticipated that the Colts would not continue to kick to Hester, so the TD amounted to just 7 points and not much of an indication how the rest of the game would play out.

I suspect that someone who tried trading in a real money market using the Protrade probability estimates would have lost a heck of a lot of money during the Super Bowl (though admittedly this is a small sample of just one game).

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• Super Bowl Analysis Highlights
• Super Bowl Analysis Highlights — Keith Jacks Gamble’s Second Turn
• Awesome Graph of 2007 Super Bowl Probabilities
• Super Bowl Analysis Highlights — MR Comments
• Super Bowl XLI

• The Colts entered the game with a 68% chance of winning.
• The Bears winning the coin toss made them 0.5% more likely to win.
• Devin Hester’s kick return for a touchdown made the Bears 10.25% more likely to win.
• Thomas Jones’ 52 yard run to the Colts’ 5 yard line had the biggest impact of any offensive play. (10.75%)
• When the Bears took an 8 point lead, the market still viewed the Colts as the favorite to win.
• Kelvin Hayden’s interception was the biggest impact play of the game. It increased the Colts chances of winning by 18% to 94.5%.
• The market was fully convinced of a Colts victory with 5:00 left in the game.
• MVP Peyton Manning ranks only 6th on the list of top impact players of the game for the Colts.
• Rex Grossman’s poor play contributed 36.5% to the Colts’ chance of winning, more than twice as much as the top performing Colt.

Full Analysis

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Midas Oracle .ORG = Site Map + Archives + Best + Charts + Exchanges + Software + Links + Network + Write A Post Or A Page + How To Publish

• Super Bowl Analysis Highlights — Keith Jacks Gamble’s Second Turn
• Super Bowl Analysis Highlights — MR Comments
• An Analysis of the 2007 Superbowl Using Price Changes on TradeSports
• Top 5 Plays of the Super Bowl? Market says No.
• Awesome Graph of 2007 Super Bowl Probabilities