Sandbox from Yahoo! Research

Yoopick is a sports prediction contest with a twist.

Instead of picking the exact outcome of a game, you can pick any range you think the score difference or point spread will fall into, for example you might pick Pittsburgh wins by between 2 and 11 points.

The more your prediction is viewed as unlikely by others, and the more you're willing to stake on your prediction, the more you stand to gain. Of course it's all for fun: you win and lose bragging rights only, nothing tangible.

You can play with and against your friends on Facebook.

Like selling in the stock market, you can settle a pick even before the game is over. Depending on what other players have done in the interim, you may be left with a gain or loss. You gain if you were one of the first to pick a popular outcome.

There are a great many sources of sports predictions, include expert communities, statistical number crunchers, bookmakers, and betting exchanges. Many of these sources are highly accurate, however they typically focus on predicting the outright or spread-adjusted winner of the game. Our goal is to obtain more information about the final score, including the relative likelihood of every possible point spread. For example, if our system is working, on average there should be more weight put on point spreads of 3 and 7 in NFL games than on 2,4,6, or 8.

We chose sports as a test domain to tap into the avid fan base and the armies of arm chair (and Aeron chair) prognosticators out there.
However, the same approach should translate well to any situation where you'd like to predict a number, for example, the vote share of a politician or the volume of sales of your company's widget. In addition to giving you the expected value of the number, our approach gives you the confidence or variance of the prediction -- in fact, it gives you the entire probability distribution, or the likelihood of every possible value of the number.

Underneath the hood, Yoopick is a type of combinatorial prediction market where the possible outcomes are the values of the point spread, and each pick is a purchase of a bundle of outcomes in a given interval. We use Hanson's
logarithmic market scoring rules market maker to price the picks -- that is, to set the risk/reward ratio. This pricing mechanism also determines the gain or loss when picks are settled early.

Our market maker can -- and we expect will -- lose on average. Stated another way, we expect players as a whole to gain on average. At the same time, we actively work to improve our market maker to limit its losses to control inflation in the game.

Because the outcomes of a game are tied together in a unified market, picks in one region automatically affect the price of picks in other regions in a logically consistent way. Players have considerable flexibility in how and what information they can inject into the market.
In particular, players can replicate the standard picks like outright winner and spread-adjusted winner if they want, or they can go beyond to pick any interval of the point spread. No matter the form of the pick, all the information flows into a single market that aggregates everything in a unified prediction. In contrast, at venues from Wall Street to Churchill Downs to High Street to Las Vegas Boulevard, markets with many outcomes are usually split into independent one-dimensional markets.

Our goal is to test whether our market design is indeed able to elicit more information than traditional methods. We hope you have fun playing in our petri dish.

David Pennock