From Iowa to Polymarket: The Wild History of Prediction Markets

Picture this: It's 1988, and a group of finance professors at the University of Iowa just had a wild idea. What if they let people bet real money on election outcomes? Not in some smoky back room, but as a legitimate academic experiment. They called it the Iowa Electronic Markets, and they had no idea they were lighting the fuse on one of the most controversial — and accurate — forecasting tools ever created.

Fast-forward 36 years, and prediction markets had their biggest moment yet. In 2024, Polymarket processed over $3 billion in bets on the presidential election, while platforms like Kalshi made headlines for predicting everything from Federal Reserve decisions to Taylor Swift's next career move. But the path from Iowa's computer lab to the prediction market boom is littered with scandals, shutdowns, and enough regulatory drama to fill a Netflix series.

Let's dive into the wild history of prediction markets — the story of how betting on the future became big business.

The Humble Beginnings: Iowa's Accidental Revolution

The Iowa Electronic Markets (IEM) started as an answer to a simple question: Could financial markets predict election outcomes better than polls?

In 1988, professors Robert Forsythe and Forrest Nelson created what was essentially the world's first modern prediction market. Students and faculty could trade contracts on whether George H.W. Bush or Michael Dukakis would win the presidency. Each "Bush wins" contract paid $1 if he won, zero if he lost. If the market price was 60 cents, it meant traders collectively thought Bush had a 60% chance of winning.

The results were stunning. While polls showed a dead heat right up until election day, the Iowa market correctly predicted Bush's decisive victory weeks in advance. The prediction market had cracked the code that pollsters couldn't: it aggregated not just what people said they'd do, but what they were willing to risk money on.

But here's the kicker — the Iowa Electronic Markets are still running today, 36 years later. They've successfully predicted every presidential election, often outperforming traditional polls by significant margins. Not bad for an academic side project that started with a $500 maximum bet limit.

The Wild West Era: InTrade's Rise and Spectacular Fall

While Iowa's professors were quietly proving prediction markets worked, entrepreneurs smelled opportunity. Enter InTrade, the platform that would become synonymous with prediction markets in the 2000s.

Founded in Ireland in 2001, InTrade was prediction markets' first attempt at going mainstream. They offered bets on everything: elections, celebrity deaths, sporting events, even whether weapons of mass destruction would be found in Iraq. (Spoiler alert: the market correctly predicted they wouldn't be.)

InTrade's golden moment came during the 2008 election. While polls showed Obama and McCain in a tight race, InTrade's prices reflected Obama's growing momentum weeks before traditional media caught on. Suddenly, CNBC anchors were quoting InTrade prices alongside stock indices. Prediction markets had arrived.

But success bred controversy. InTrade operated in a regulatory gray area, technically illegal for Americans but widely used anyway. The platform's Irish registration provided legal cover, but it was a house of cards waiting to collapse.

The end came in 2013, not from regulators but from good old-fashioned financial mismanagement. InTrade's operator had been using customer deposits as a personal piggy bank. When the Commodity Futures Trading Commission (CFTC) finally moved to shut them down, there was barely any money left to return to users. The prediction market revolution's first poster child had flamed out spectacularly.

The DARPA Debacle: When Prediction Markets Made Headlines for All the Wrong Reasons

Just as prediction markets were gaining credibility, along came a scandal so bizarre it reads like political satire. In 2003, the Pentagon's research arm DARPA (Defense Advanced Research Projects Agency) announced the "Policy Analysis Market" — a prediction market for terrorism.

The idea was actually brilliant from a forecasting perspective: create a market where intelligence analysts could bet on geopolitical events, Middle East stability, and yes, potential terrorist attacks. The market's prices would aggregate classified intelligence in real-time, potentially providing early warning signals.

The execution? Not so brilliant.

Senators Hillary Clinton and Byron Dorgan held a press conference calling it a "terrorism futures market" and "morally repugnant." The media ran with headlines like "Pentagon's Terror Betting Parlor." Within 24 hours, the program was dead, and prediction markets had their first major PR disaster.

The irony is thick: DARPA was essentially proposing the same intelligence aggregation that proved so effective in Iowa's election markets. But betting on Bush vs. Gore is one thing; betting on terrorist attacks is quite another in the public imagination.

This controversy would cast a shadow over prediction markets for years, giving regulators ammunition to argue these platforms were inherently problematic.

The Crypto Chapter: Augur's Ambitious Experiment

Fast-forward to 2014, when the crypto boom promised to solve prediction markets' biggest problem: regulation. Augur emerged as the first major attempt to build a decentralized prediction market on the blockchain.

The pitch was compelling: no central authority to shut down, no geographic restrictions, and complete resistance to regulatory interference. Augur raised $5.1 million in one of the first major crowdfunding campaigns and spent four years building what many considered a technical masterpiece.

But Augur's launch in 2018 revealed the dark side of complete decentralization. With no content moderation, the platform immediately filled with assassination markets and other unsavory bets that made the DARPA terrorism market look quaint by comparison. Legitimate predictive questions were drowned out by a cesspool of offensive content.

The user experience was equally problematic. Creating a market required deep technical knowledge, and resolving disputes involved complex token-voting mechanisms that few users understood. Augur proved that while decentralization solved the regulatory problem, it created a host of new ones.

Despite raising millions and generating massive hype, Augur never achieved meaningful adoption. The platform processed maybe $10 million in total volume — less than Polymarket now does on a busy Tuesday.

The Regulatory Gauntlet: How the CFTC Shaped the Industry

Understanding modern prediction markets requires understanding their regulatory dance with the Commodity Futures Trading Commission (CFTC). In the U.S., prediction markets exist in a peculiar legal limbo — not quite gambling, not quite securities, but something the CFTC regulates as commodity derivatives.

The CFTC's approach has been inconsistent, to put it mildly. They allowed Iowa's academic markets to operate with minimal oversight while aggressively pursuing commercial platforms like InTrade. The agency granted Kalshi approval to operate legally in the U.S., but only for certain types of markets. Political betting? Mostly forbidden. Interest rate predictions? Totally fine.

This regulatory uncertainty has forced most prediction market innovation offshore. Polymarket operates from outside the U.S. despite serving American users (wink wink). PredictIt survived for years under academic exemption before the CFTC revoked their no-action letter in 2022.

The inconsistency reflects a deeper philosophical divide about prediction markets. Are they valuable forecasting tools that deserve protection, or thinly veiled gambling operations that need restriction? Different administrations have taken different approaches, keeping the entire industry in regulatory purgatory.

Polymarket's Breakthrough: Prediction Markets Go Mainstream

Enter Polymarket, the platform that finally cracked the code on making prediction markets both accessible and accurate. Founded in 2020 by then-22-year-old Shayne Coplan, Polymarket learned from every previous failure.

Unlike Augur, Polymarket maintained content moderation and user-friendly interfaces. Unlike InTrade, they built on blockchain infrastructure that made financial manipulation much harder. Unlike Iowa, they offered high limits and real liquidity.

The 2024 election became Polymarket's breakout moment. While polls showed a dead heat between Trump and Harris right up until election day, Polymarket's prices consistently favored Trump by significant margins. When Trump won decisively, prediction markets had their biggest vindication since Iowa's early successes.

The platform processed over $3 billion in election-related volume, with individual markets seeing tens of millions in trades. Suddenly, everyone from Wall Street traders to cable news anchors was watching Polymarket prices. The platform had achieved what previous prediction markets only dreamed of: mainstream legitimacy.

But Polymarket's success raises new questions about the future of prediction markets. Operating offshore while serving U.S. users isn't a long-term solution. Can prediction markets achieve full regulatory acceptance in the United States?

The Characters Behind the Revolution

Every technological revolution has its characters, and prediction markets have produced some memorable ones. There's Robin Hanson, the economist who provided much of the intellectual framework for prediction markets and still evangelizes their potential. Nate Silver built his empire partly on the insights gleaned from prediction market prices.

Shayne Coplan became prediction markets' unlikely poster child — a young entrepreneur who turned what many considered a solved problem into a billion-dollar platform. Even Donald Trump became an inadvertent prediction market advocate, frequently citing betting odds (when they favored him) as evidence of his electoral strength.

Then there are the traders who make these markets work. Some are sophisticated quantitative analysts building complex models. Others are just politically obsessed individuals with strong opinions and money to back them up. The beauty of prediction markets is that both contribute to price discovery — passion and expertise often converge on accurate predictions.

What's Next: The Future of Forecasting

Today's prediction markets look nothing like Iowa's simple election contracts, but they're solving the same fundamental problem: how do we aggregate dispersed information to make better predictions?

Platforms like Kalshi are pushing into financial markets, offering contracts on everything from unemployment rates to cryptocurrency prices. Metaculus has built a community of thousands of forecasters tackling complex scientific and technological questions. Even traditional financial institutions are experimenting with prediction market mechanisms.

The regulatory landscape is slowly evolving too. The U.K. has taken a more permissive approach, while countries like Australia are exploring frameworks for regulated political betting. Eventually, the U.S. will likely follow suit — the forecasting advantages are simply too valuable to ignore indefinitely.

But perhaps the most important development is cultural acceptance. Prediction markets are no longer seen as exotic financial instruments but as legitimate sources of information. When news anchors cite betting odds alongside polls, when researchers use market prices to validate their models, when ordinary people check Polymarket before making decisions — that's when you know a technology has truly arrived.

The Vindication

From Iowa's computer lab to Polymarket's billion-dollar volumes, prediction markets have survived every attempt to kill them. They've weathered scandals, regulatory crackdowns, technical failures, and public relations disasters. They keep coming back for one simple reason: they work.

Every accurate election prediction, every successful policy forecast, every time markets spot trends that experts miss — it's another piece of evidence that crowds with skin in the game often know more than experts without it.

The wild history of prediction markets isn't just about betting on the future. It's about democracy, information aggregation, and the eternal human desire to peek around the corner of time. And judging by recent success, this story is just getting started.