It's a mid-March tradition in offices and homes across the country:picking the winners of the NCAA men's basketball tournament. Now you can try Predictalot, a game from Yahoo! Research that takes tourney pick'em to new extremes*. Construct almost any prediction you can think of, like “Duke will advance further than UNC”, or “Every final four team name will start with U”. Check the odds and then invest points on your favorites for a chance to win. Sell your predictions anytime, stock-market style, even as you follow the basketball games live. Accumulate points and climb your way to the top of the leaderboard.

The basic game play is simple: select a prediction type, customize it, and invest points on it. Yet you'll never run out of odds to explore: you can make hundreds of millions of predictions! The odds on each update are continuously based on other players' predictions and the on-court action.

If you're a gamer and not so interested in the underlying math, you can stop here. On the other hand, if you're curious and would like a peek under the hood, read on: there's some interesting technology hidden in the engine.

In the tournament, after the play-in game, the 64 top college basketball teams play 63 games in a single elimination tournament. So there are 2⁶³ or 9.2 quintillion total possible outcomes, or ways the entire tournament can unfold. Predictalot implicitly keeps track of the odds for them all! To put this in perspective, it's estimated that there are about 10 quintillion individual insects on earth. Of course, for all practical purposes, we can't store 9.2 quintillion numbers, even with today's computers. Instead, we compute the odds for any outcome on the fly by scanning through the predictions placed so far.

A prediction is a statement, like “Duke will win in the first round”, that will be either true or false in the final outcome. In this case, the prediction is true in exactly half, or 2⁶² of the 2⁶³ possible outcomes. (Note: this does not mean the odds are 50% - remember the outcomes themselves are not all equally likely.) In theory, Predictalot can support predictions on any set of outcomes. That's 2 to the power 2⁶³ or more than a googol predictions. For now, we restrict you to "only" hundreds of millions of predictions categorized into thirteen types. Computing the odds of a prediction precisely is too slow. Technically, the problem is #P-hard, or harder than the famous travelling salesman problem. So we must resort to approximating the odds by randomly sampling the outcome space. Sampling is a tricky business - equal parts art and science - and we're still actively exploring ways to increase the speed, stability, and accuracy of our sampling.

Because we track all possible outcomes, the predictions are automatically interconnected in ways you would expect. A large play on Duke to win the tournament instantly and automatically increases the odds of Duke winning in the first round; after all, Duke can't win the whole thing without getting past the first round.

In technical terms, Predictalot is a combinatorial prediction market of the sort academics like Yahoo! and George Mason University professor Robin Hanson have been dreaming about since early in the decade. We built the first version during an internal Yahoo! Hack Day. Finally, we leveraged the Yahoo! Application Platform to quickly build a public version of the game. (Note that anyone can develop a YAP app that's visible to millions - there's good sample code, it supports YUI and OpenSocial, and it's easy to get started.) After many fits and starts, late nights, and eventually all nighters, we're proud and excited to go live with Predictalot version 1.0. I can't rave enough about the talent and dedication of the research engineers who gave the game a professional look and feel and production speed, turning a pie-in-the-sky idea into reality. We have many features and upgrades in mind for future versions, but the core functionality is in place and we hope you enjoy the game.

With 9.2 quintillion outcomes, Predictalot is to our knowledge the largest prediction market built, testing the limits of what the wisdom of crowds can produce. Predictalot is a game, and we hope it's fun to play. We'd also like to pave the way for serious use of combinatorial prediction market technology.

Why did Yahoo! build Predictalot? Predictalot is a smarter market, letting humans and computers each do what they do best. People enter predictions in simple terms they understand like how one team fares against another. The computer handles the massive yet methodical number crunching needed to combine all the pieces together into a coherent overall prediction of a complex event. Markets like Predictalot, WeatherBill, CombineNet, and Internet advertising systems, to name a few, represent the evolution of markets in the digital age, empowering users with extreme customization. More and more, matching buyers with sellers - the core function of markets - requires sophisticated algorithms, including machine learning and optimization. Predictalot attempts to illustrate this trend in an entertaining way.

David Pennock
Mani Abrol, Janet George, Tom Gulik, Mridul Muralidharan, Sudar Muthu, Navneet Nair, Abe Othman, Daniel Reeves, Pras Sarkar

News Coverage

• New York Times - Crowdsourcing the N.C.A.A. Tournament
• Venture Beat via New York Times - Yahoo’s New Crowdsourcing Predictalot App Picks NCAA Winners
• Yodel Anecdotal - Testing the Wisdom of Crowds on the Madness of NCAA Basketball

*Predictalot for the NCAA Basketball Tournament has closed. We will relaunch Predicalot for the FIFA World Cup soon.