Viewing prediction markets from a casino perspective: differences from casinos, fatal flaws, and the ultimate form

How to truly understand prediction markets?

Some say it’s just a casino, while others see it as a great innovation in information trading.

So, what exactly is a prediction market?

The word “casino” carries many negative and gray connotations,

Betting on probabilities, guessing ups and downs, placing bets—though prediction markets operate and feel like casinos,

Purely viewing prediction markets as casinos is actually more about lazy thinking and dismissing new things.

After systematic research, I believe prediction markets are not just casinos, nor merely transforming casinos, but are “information trading markets” that can genuinely influence the world and aggregate market information.

We can analyze prediction markets from a casino perspective.

1. What are the core differences between prediction markets and casinos?

The fundamental difference lies in pricing power and risk bearers.

Casinos: centralized house setting prices + unlimited bets,

Prediction markets: collective user pricing + mutual bets.

Here’s a comparison table:

Let’s look at two examples for a clearer understanding of the differences:

Casino example: Betting on “World Cup Brazil wins”

You bet 100 yuan, odds 1.95

The house sets the price; you can only accept

Brazil wins → you get 195, house loses 95

Brazil loses → house takes 100

The house is your sole opponent, bearing all risks

The house profits long-term through house edge (5%)

Prediction market example: Betting on “2028 US Election Trump wins”

Current Yes price = 0.60 USD (market price)

You buy 100 shares of Yes → spend 60 USDC

Someone sells you Yes → they believe Trump won’t win

You and the “Yes seller” are betting against each other

Platform (Polymarket) does not participate in the bets, only charges a 1% transaction fee

Prices are driven by all buyers and sellers, like stocks

Simply put, a casino is you playing cards against the house; a prediction market is you playing cards with friends.

2. What are the advantages of prediction markets over casinos?

Moving from house-bettor interactions in casinos to user-to-user betting in prediction markets brings many changes.

Compared to traditional casinos, prediction markets have four significant structural advantages:

1️⃣ No need for complex risk control modeling

Under the mechanism of prediction markets, even niche long-tail events can be successfully created.

For example, “Will it rain in a specific city tomorrow?”—such niche events can be traded freely.

This is because users often possess informational advantages, and prices are automatically formed through market supply and demand.

For traditional casinos, the house lacks sufficient data support, so they dare not open such markets recklessly.

Traditional casinos must rely on manual setting of odds and strict limits.

2️⃣ Platform operators bear zero risk

Prediction market platforms do not act as counterparties → thus, they will never face a catastrophic failure.

They only need to collect relatively low transaction fees (usually between 0.5% and 2%) to be profitable.

In contrast, in traditional casinos, if the house goes bankrupt = the entire platform faces a crisis.

This is because the house must bear all the enormous risks of unlimited bets alone.

3️⃣ Liquidity is crowdsourced

In prediction markets, all participating users are essentially liquidity providers.

In traditional casinos, all liquidity depends on the house alone.

In this case, small markets must impose strict limits to prevent large funds from crashing the market.

4️⃣ Supports flexible exit at any time

In prediction markets, users can sell their positions at any time, just like trading stocks, greatly improving capital efficiency.

Prediction markets also support leverage trading, risk hedging, and various complex portfolio strategies.

In traditional casinos, once you place a bet, your funds are fully locked; participants cannot exit midway and must hold until settlement.

In summary, the transformation of prediction markets is to disperse the house into the market, with advantages of zero risk control, zero risk, high efficiency, and broad coverage.

But everything has two sides—what do prediction markets sacrifice?

Mainly, market controllability and large capital capacity.

3. What are the flaws of prediction markets?

Prediction markets have a critical flaw in mechanism design: they cannot form market makers.

Let’s first understand what a market maker is: continuously posting bid/ask quotes, earning the spread + fees.

For example, on an exchange, you post buy at 99 yuan / sell at 101 yuan; if someone buys your sell order → you earn a 2 yuan spread, which is a long-term positive EV (Expected Value).

Why is market making difficult in prediction markets?

Mainly due to three mechanism issues:

1️⃣ No closing mechanism

In prediction markets, trading can occur at any time before the event result, even in the last second.

This leads to insider players placing bets in the final minute, consuming all liquidity.

2️⃣ No slippage/limits

In prediction markets, large orders can be executed at the current market price.

This causes market maker orders to be instantly broken through, leading to high-position entries.

3️⃣ Zero-cost exit

Insider players can attack or defend, while market makers can only passively take orders.

Looking back at traditional casino house:

They can close the market (stop trading 30 minutes before the event ends), impose limits (max 1000U), allow slippage (automatic price increase for large orders), or refuse orders.

Thus, the house can achieve positive EV, with an advantage of 2%-5%.

In prediction markets, market makers lack protective mechanisms + are precisely targeted by insiders → long-term losses (negative EV).

Negative EV means the game is mathematically doomed to lose money; smart players either avoid being the house or become a controllable house with closing, limits, and slippage.

On platforms like Polymarket, which have unlimited, zero-cost exit and market-based pricing, any unconditional liquidity provider will inevitably lose money.

The final result is poor liquidity in long-tail markets, and large funds cannot enter effectively.

4. What solutions can address the critical flaws of prediction markets?

Currently, the only systematic solution to the three major flaws of prediction markets is: proprietary automated market maker (AMM) protocols.

The full English name is: Permissionless Proprietary Automated Market Maker for Prediction Markets.

This is a DeFi protocol that allows anyone to create prediction markets, with controllable slippage, external professional LPs providing liquidity and earning positive EV returns.

Simply put, it’s a hybrid of Polymarket + Hyperliquid + Uniswap, designed specifically for large casino funds.

Three core elements:

1️⃣ Permissionless pool creation

Anyone can create markets, solving the cold start problem of long-tail markets.

Experience similar to Uniswap: any wallet address can create any trading pair.

2️⃣ Controllable liquidity pools

Market creators set slippage curves and closing times to prevent malicious large orders or insider sniping at the end.

For example, support dynamic slippage curves (higher slippage with larger volume), automatic pool lock N minutes before the event, maximum single bet size, etc.

3️⃣ Professional LPs

External market makers deposit funds to earn fees, achieving positive EV.

Positive EV attracts professional market makers.

In fact, Hyperliquid is already a top-tier implementation of a PropAMM, suitable for high-frequency market making, with more controllable and professional dynamic fee rates.

5. Summary

This article, from a casino perspective, systematically explains the differences, advantages, and flaws of prediction markets, and proposes relevant solutions.

Hope everyone can gain a deeper understanding of prediction markets and see the future development trajectory.

Prediction markets can be divided into three stages:

1️⃣ Traditional casino form: black and gray money laundering, mainly user vs. house betting, with issues of high risk control costs and platform failure risks.

2️⃣ First-generation prediction markets: exemplified by Polymarket, where players bet against each other; flaws include negative EV for market makers, dead long-tail markets, and difficulty attracting large funds.

3️⃣ Second-generation prediction markets: PropAMM-like protocols, permissionless + controllable slippage + professional LPs, systematically solving the three major existing flaws.

Who can first realize the complete version of Polymarket + Hyperliquid + Uniswap may seize this hundred-billion-dollar market!