Markets Outsmart Polls Every Election. Here's Why.
Jason Dussault
Chief Executive Officer, Co-Founder
This Post is disseminated on behalf of Intellistake Technologies Corp.
There's something fundamentally different about putting your money where your mouth is, and the data proves it: prediction markets have outperformed traditional polling in accuracy for decades.¹
Every election cycle, we watch pollsters struggle with sampling biases, response rates, and the challenge of modeling who will actually show up to vote. Meanwhile, prediction markets—where traders risk real capital on outcomes—quietly compile a more accurate picture. It's not magic. It's an incentive.
The Problem with Traditional Forecasting
Polling has become increasingly unreliable, perhaps more so in recent cycles than ever before. Response rates have plummeted. People don't answer their phones the way they used to. And even when they do, there's a growing gap between what people tell pollsters and how they actually vote.²
The traditional approach tries to solve this with better sampling techniques, more sophisticated weighting, and complex turnout models. But fundamentally, polls are asking people to predict their own future behavior—and to be honest about it with a stranger.
That's a tall order.
Prediction markets take a different approach entirely. They don't ask. They watch what people do when money is on the line.
Where Prediction Markets Began
The concept isn't new. The Iowa Electronic Markets, launched in 1988 by the University of Iowa's Tippie College of Business, pioneered the modern prediction market format.³ Researchers wanted to test whether aggregating the forecasts of traders with skin in the game could outperform traditional polling.
The results were striking. From 1988 to 2004, the Iowa Electronic Markets outperformed polls 74% of the time in presidential elections.¹ That's not a marginal improvement—it's a fundamentally different level of accuracy.
But the roots go even deeper. Prediction markets trace back to 16th-century commodity exchanges and betting markets in Europe, where traders would price future outcomes based on available information.⁴ The concept was formalized in academic literature in the 1980s and 1990s, with economists recognizing that markets could aggregate dispersed information more efficiently than moderately sophisticated benchmarks.⁵
Why Skin-in-the-Game Changes Everything
Here's the difference: when you answer a poll, nothing happens if you're wrong. When you bet money, you feel it.
That changes everything. People stop guessing. They start paying attention. They update their views when new information comes out — because their wallet depends on it.
Polls treat every response the same. The person who's followed every debate counts the same as someone who can't name the vice president. Prediction markets don't work that way. If you're confident, you bet more. If you've been right before, you have more to bet with. The system rewards accuracy, not just participation.
The Infrastructure Challenge
But here's where it gets interesting, and perhaps a bit frustrating. Despite their superior accuracy, prediction markets have remained relatively fragmented and small. Liquidity—the ability to quickly buy or sell positions without moving prices significantly—has been the persistent bottleneck.6
When liquidity is thin, even small trades can cause wild price swings. That reduces accuracy. It makes markets less efficient at aggregating information. And it keeps institutional participants on the sidelines, which further reduces liquidity. It's a circular problem.
This is exactly the infrastructure gap that needs to be solved if prediction markets are going to reach their full potential as forecasting tools. The technology exists. The track record is proven. What's missing is the market microstructure that allows these markets to scale.
Building the Plumbing
At Intellistake, we're working on precisely this challenge. Our
C$1,573,000 development agreement (payable in stages over an 18 - 20 month development term and subsequent 24 month exclusive licensing term) with Prospect Markets focuses on building Gravity — a liquidity management system designed specifically for prediction markets.¹⁰
The goal is straightforward: create the infrastructure that allows prediction markets to handle significantly larger volumes without sacrificing the price discovery mechanism that makes them accurate. Think of it as building the plumbing that lets the wisdom of crowds flow more efficiently.
This isn't about replacing the incentive structure that makes prediction markets work. It's about removing the friction that prevents them from scaling. When liquidity improves, bid-ask spreads tighten. When spreads tighten, more participants can enter and exit positions efficiently. When that happens, the information aggregation process becomes even more robust.
For full details on the Gravity development agreement and technical specifications
see the press release.
What Comes Next
We're at an inflection point. Prediction markets have proven their accuracy over nearly four decades of real-world testing. Institutional validation from organizations like the Federal Reserve has arrived.8 Regulatory frameworks are gradually adapting to accommodate these tools.
What's needed now is infrastructure that matches the sophistication of the forecasting mechanism itself. Markets that can handle the volume. Systems that can manage liquidity across multiple outcomes and time horizons. Technology that makes participation accessible without compromising the skin-in-the-game incentives that drive accuracy.
I think we're going to look back on this period as the moment when prediction markets transitioned from academic curiosity to mainstream forecasting tools. The data has always been there. The proof points have been accumulating for decades. Now the infrastructure is catching up.
The question isn't whether prediction markets are more accurate than polls—the evidence on that is clear. The question is how quickly we can build the systems that let them reach their full potential. Because in a world of increasing complexity and uncertainty, we need forecasting tools that actually work.
And perhaps the most interesting question of all: what other domains beyond politics could benefit from this skin-in-the-game approach to forecasting?
Disclaimer
There has been significant volatility in digital assets and their value can decline rapidly, which in turn would lead to a decline in the stock price of companies holding digital assets. Intellistake is a start-up that does not have the same access to capital as other larger more established companies.
Intellistake has just commenced operating its business and is at an early stage of development. Intellistake is entering this space by acquiring and operating blockchain validator hardware that supports AI networks and investing in AI-related digital tokens to primarily operate validator hardware.
Intellistake is presently evaluating the regulatory framework for tokenization. Any tokenization will be subject to it being completed in compliance with applicable law, regulatory requirements and terms of any underlying agreements associated with the underlying assets. The actual structure of such tokenization, the assets that would be subject to tokenization, and the associated timeline, have not yet been determined. Intellistake will provide further updates as material developments related to this tokenization strategy occur.
Intellistake is developing custom AI software systems called "AI Agents" for businesses. It recently announced the development of IntelliScope, a newly designed enterprise artificial-intelligence (AI) suite that applies decentralized AI technologies to deliver transparent and verifiable corporate intelligence. IntelliScope, which is in testing, is being publicly introduced as Intellistake's enterprise AI suite, reflecting the Company's focus on advancing practical applications of decentralized AI technologies.
The IntelliScope suite is being developed as a collection of modular AI agents, each intended to address specific enterprise challenges. Development has advanced through internal closed testing, where functionality is being refined and validated. Built to leverage decentralized AI technologies developed within the ASI Alliance FET token ecosystem, IntelliScope is now preparing to move into closed beta testing with an enterprise client, a phase focused on gathering feedback to shape premium features and expand real-world use cases.
The Company intends to deliver these solutions either as one-time projects or ongoing subscription services. Revenue is expected to come from implementation fees and monthly subscription payments. The Company does not presently have any customers. Intellistake is just commencing operations. It is targeting significant growth but its business is subject to several risks related to general business, economic and social uncertainties; the sufficiency of cash to meet liquidity needs; legislative, political and competitive developments; the inherent risks involved in the digital currency and general securities markets; the volatility of digital currency prices and the additional risks identified in the "Risk Factors" section of the Company’s filings with applicable securities regulators. Intellistake has not yet developed or commercialized its AI solutions.
Completion of the Singularity Venture Hub (“SVH”) acquisition remains subject to completion of satisfactory due diligence, the negotiation, and execution of a definitive agreement ("Definitive Agreement") that will include representations, warranties, covenants, indemnities, termination rights, and other provisions customary for a transaction of this nature, no objection from the Canadian Securities Exchange, and shareholder approval of SVH, if required.
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Although the Company has attempted to identify factors that could cause actual results to differ materially from those described in forward-looking information, there may be other factors that cause results not to be as anticipated. Readers should not place undue reliance on forward-looking information. The forward-looking information is made as of the date of this report. Except as required by applicable securities laws, the Company does not undertake any obligation to publicly update forward-looking information.
