Prediction Market 2.0 Outlook: 5 New Product Forms Beyond "Pure Gambling"

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Original text: neel daftary

Compiled by: Odaily Planet Daily Golem

The future of prediction markets may very well be dominated by Polymarket/Kalshi, capturing all attention and market share. However, even so, we may ultimately use entirely new designs of prediction markets that cater to everyone's needs and align with their preferences and interests.

How has the trading of Meme coins evolved? From 2015 when we only needed to buy tokens with a dog printed on them, to 2025 when we need to learn how to use tools (Axiom), track wallets (Cielo, Nansen, Arkham), and also join a community to search for tokens together on platforms like Solana, BNB, and Base.

Every opportunity that arises in the field of cryptocurrency begins with simple patterns. Over time, these simple patterns either fade away (e.g., NFTs) or become more complex with the addition of more participants, leading to the gradual disappearance of early advantages (e.g., meme coins). Of course, users also want to engage in more complex games, as can be seen from the evolution of most video games (e.g., God of War, Assassin's Creed, FIFA, etc.). To maintain appeal and relevance to the core user base, games and game-like platforms need to increase functionality and complexity, allowing top players to stand out from 99% of players.

When this situation occurs again and corresponds with the prediction market category, it will no longer be a single, large platform, but a complete ecosystem containing numerous prediction-related applications.

These standalone products can leverage the core mechanisms of prediction markets (incentivized forecasting and stakeholder engagement) to create entirely new experiences. Here are five highly anticipated categories:

Expected Impact on Trading: Taking Lightcone as an Example

This may be the latest and most complex primitive concept, surpassing the realm of probability, allowing users to trade the impact of events.

It can be understood this way: prediction markets tell you the probability of an event occurring (P), while spot markets tell you the spot price of the event occurring (S). However, the new category defined by Lightcone, “influence markets,” aims to separate and price influence (I).

The platform operates by cloning assets into a “parallel universe” based on future events. For example, users can deposit 1 BTC before the US elections and then receive two new tradable tokens, Trump-BTC and Kamala-BTC.

These tokens are traded in independent “parallel universes.” When events occur (for example, if Trump wins), all Trump-BTC can be exchanged for real Bitcoin, while all Kamala-BTC will go to zero (and vice versa).

The advantage of this model lies in the emergence of two entirely new applications:

New Information Machines: They provide us with an experimental space to predict financial impact. By comparing the prices of Trump-BTC (e.g., $130,000) and Kamala-BTC (e.g., $91,000) with the current spot Bitcoin price ($102,000), the market clearly tells us the expected financial impact of each outcome, which is completely unrelated to the probability of the outcomes occurring.

“Event-based” hedging: Traders can hedge specific risks without paying a premium unless the risk occurs. For example, a trader concerned about a specific credit event (such as a Saylor default) can hold strSolvent-BTC while selling their strDefault-BTC in exchange for strDefault-USDC.

If a default occurs, their strDefault-USDC will turn into real USDC. They successfully hedged and sold Bitcoin before the event occurred; if no default happens, their strSolvent-BTC can be exchanged for their original Bitcoin. They still hold long positions, and the hedge operation incurred no costs.

This is a complex tool. It removes the “probability” variable from trading, allowing institutions and traders to trade solely based on influencing factors, which is indeed a whole new financial foundation.

Public Opinion Market: Betting on Beliefs

This is a fascinating concept where participants no longer bet on objective facts (e.g., “Will Ethereum reach $5000?”) but rather on what people will believe.

For example: “Will over 70% of participants bet 'yes' in this market?”

This model has two major advantages:

Quick settlement: The market can settle once a day or every few hours based solely on its internal dynamics. It does not rely on slow external oracles.

Monetization of social capital: It rewards players who can accurately predict collective psychology rather than facts. This is a way to directly monetize cultural influence and cultural understanding.

Currently, platforms like Melee, vPOP, and opinions.fun are trying to build this model, allowing people to convert social capital into profit.

Virtual Sports: High-Frequency Prediction Market

Virtual sports is a $25 billion industry, at the core of which lies a cyclical prediction market.

On the Football.Fun platform, users do not place a single bet but instead make combination predictions. Forming a team is essentially betting on the overall performance of the players, all of whom are subject to budget constraints.

The reason this model is powerful is because:

It can bring continuous and periodic betting volumes (for example, weekly NFL/NBA/PL tournaments).

It allows users to monetize the expertise they accumulate by watching more than 10 hours of matches each week.

The native advantage of cryptocurrency lies in its tradable assets. Digital player cards themselves are a prediction of a player's in-game value. Native virtual sports in cryptocurrency allow players to profit by participating in pure player card trading (similar to gacha boxes, physical collectibles) and regularly conducted cyclical prediction market games.

Opportunity Market: Private Placement Information Mining

This is the second innovative mechanism proposed by the Paradigm team, enabling prediction markets to solve the problems faced by enterprises: finding valuable early information.

The model is as follows:

Initiator (VC): Provides all liquidity for the private placement market (for example, “Will we invest in Y startup this year?”).

Scout (Expert): Use their own information and expertise to purchase shares of “yes”.

Signal: Price increase becomes a proprietary aggregation signal for VCs/institutions, indicating the market should investigate/reinvestigate this project.

This is essentially a decentralized scouting program. It can also address the “free-rider problem” in some way (the signals are private and only the initiator can access them) and the liquidity issue (the initiator is a permanent market maker).

Betting on market governance wisdom

This is a governance model that delegates policy decision-making power to the wisdom of the market. Its core concept is: “People will vote based on values, but will bet based on beliefs.”

The operation is as follows:

A DAO reaches a consensus on a certain value or goal (for example, “maximizing monthly active users”).

Propose a proposal (“Proposal 123: Spend 50,000 tokens to launch a new incentive campaign”).

Create two conditional prediction markets: Market A, “If Proposal 123 passes, what will the number of monthly active users be on December 31?”; Market B, “If Proposal 123 fails, what will the number of monthly active users be on December 31?”

If the price (predicted value) of Market A is higher than that of Market B, the proposal is automatically approved.

It forces participants to invest funds in their beliefs, transforming governance from a subjective popularity contest into an information-driven practice.

But to be honest, the innovations in the application layer of prediction markets go far beyond this. In addition to the applications listed above, we are also seeing concepts like the prediction market-based news platform Boring News and the specialized prediction market fund PolyFund being developed.

The design space for prediction market applications has only just begun to be explored, and we are not optimistic enough.