Gamma API Scans: What They Reveal on Polymarket

Gamma API scans on Polymarket reveal real-time market positioning and price sensitivity data, showing how much a market’s outcome probability is likely to move for a given change in the underlying prediction. These scans expose trader concentration, liquidity depth, and the implied volatility of prediction markets, helping users identify crowded trades and potential price dislocations before they happen.

Formula

The gamma scan itself is not a single formula but a set of metrics derived from the options-style pricing model applied to prediction markets. The core quantity is gamma, the second derivative of the option price with respect to the underlying probability. In prediction markets, gamma measures how quickly the delta (the rate of change of the contract price) changes as the market probability moves. A practical proxy is the curvature of the price-yield curve around the current price. For a binary market with price p and time to expiration T (in years), the Black-Scholes-inspired gamma is approximated by:

Gamma = (1 / (p * (1-p) * sigma * sqrt(T))) * phi(d1)

where sigma is the implied volatility, phi is the standard normal density, and d1 = (ln(p/(1-p)) + (sigma^2/2)*T) / (sigma * sqrt(T)). In practice, scans use the market’s order book and recent trade history to estimate these inputs.

Worked Example

Suppose a market has a current price of $0.60 (implying a 60% chance), a time to expiration of 7 days (T = 7/365 = 0.0192 years), and an implied volatility of 80% (sigma = 0.80). First, compute d1:

d1 = (ln(0.60/0.40) + (0.80^2/2)*0.0192) / (0.80 * sqrt(0.0192)) = (0.4055 + 0.0061) / (0.80 * 0.1386) = 0.4116 / 0.1109 = 3.71

phi(3.71) = (1/sqrt(2*pi)) * exp(-3.71^2/2) = 0.3989 * exp(-6.88) = 0.3989 * 0.00103 = 0.00041

Gamma = (1 / (0.60 * 0.40 * 0.80 * 0.1386)) * 0.00041 = (1 / 0.0266) * 0.00041 = 37.6 * 0.00041 = 0.0154

So gamma is approximately 0.0154, meaning that for a 1 percentage point change in the underlying probability, the delta changes by about 0.0154. In practice, gamma values are small; scans often report them in scaled units (e.g., gamma * 1000) for readability.

What Gamma Scans Actually Show

Gamma scans on Polymarket aggregate data from the platform’s public API, which provides order book snapshots, trade history, and market metadata. From these, the scan computes:

• Gamma exposure: the aggregate gamma across all open positions, indicating how much market makers and large traders are hedged.
• Delta: the first derivative, showing the direction and magnitude of price sensitivity.
• Implied volatility (IV): derived from the prices of contracts at different strikes, reflecting the market’s expected uncertainty.
• Open interest: the number of outstanding contracts, revealing participation levels.
• Order book depth: the volume of bids and asks at various price levels, indicating liquidity.

These metrics together paint a picture of how “heated” a market is. High gamma means that as the price moves, the delta changes rapidly, leading to larger potential swings. Low gamma indicates a more stable market with less sensitivity to new information.

How to Read a Gamma Scan

When you look at a gamma scan for a Polymarket market, focus on the following:

• Gamma sign and magnitude: Positive gamma (long gamma) means traders are net buyers of options-like contracts, which can amplify price moves. Negative gamma (short gamma) means traders are net sellers, often leading to price suppression and potential squeezes.
• Implied volatility vs. historical volatility: If IV is significantly higher than recent price fluctuations, the market may be overpricing uncertainty, offering selling opportunities. Conversely, low IV relative to historical movement may indicate underpriced risk.
• Open interest and volume: High open interest with low volume suggests positions are being held, not traded, which can lead to sharp moves when those positions are unwound.
• Order book imbalance: A large bid-ask spread or thin order book can signal low liquidity, making large trades more impactful on price.

Common Misconceptions

One common misconception is that gamma scans can predict the direction of a market. They cannot; they only measure sensitivity and positioning. A high gamma market is not “more likely to move up”—it is simply more reactive to any news. Another misconception is that gamma is the same as volatility. Volatility is the magnitude of price fluctuations; gamma is how that volatility changes with price. They are related but distinct.

Also, some users assume that gamma scans are only useful for options traders. In prediction markets, every contract is essentially a binary option, so gamma analysis applies directly. Even casual bettors can use gamma to gauge whether a market is overbought or oversold relative to its risk.

Limitations and Caveats

Gamma scans rely on the accuracy of the underlying data. Polymarket’s API provides real-time data, but there can be delays or gaps in order book snapshots. Additionally, the Black-Scholes model assumes continuous trading and no transaction costs, which is not true for prediction markets. Therefore, gamma values are estimates, not exact measurements.

Another limitation is that gamma scans do not account for the possibility of market manipulation. A whale could place a large order to skew the order book, affecting the computed gamma. Always cross-reference gamma with other indicators like volume and price history.

Practical Use Cases

Traders use gamma scans to:

• Identify markets where a small piece of news could cause a large price swing (high gamma).
• Find markets with low liquidity and high gamma, which might be prone to slippage.
• Compare implied volatility across similar markets to spot mispriced uncertainty.
• Monitor changes in gamma over time to see if positioning is building up before an event.

For example, before a major political election, gamma scans on the winner markets might show rising IV and positive gamma, indicating that traders are buying protection and expecting volatile swings. This can inform a strategy of selling premium (betting against the move) if you believe the market is overreacting.

Frequently Asked Questions

How do I access gamma scans for Polymarket?

Several third-party analytics sites offer gamma scans for Polymarket markets. You can also compute basic gamma yourself using the API data and the formula above, but that requires programming. Most users rely on dashboards that visualize gamma, IV, and open interest in a user-friendly way.

What is the difference between gamma and delta in prediction markets?

Delta measures how much the price of a contract changes when the underlying probability changes by 1%. Gamma measures how much that delta changes. In simple terms, delta is speed, gamma is acceleration. A market with high gamma will see its delta change quickly, leading to non-linear price movements.

Can gamma scans predict market crashes?

No. Gamma scans can indicate that a market is fragile (high gamma, low liquidity), which makes it more susceptible to crashes, but they cannot predict the timing or cause. They are risk indicators, not forecasting tools. Always combine gamma with fundamental analysis of the event itself.

Are gamma scans free?

Many basic gamma scan tools are free, but advanced features like historical gamma charts or alerts may require a subscription. Polymarket’s own API is free, but building a custom gamma scanner requires technical skill. Check each analytics site for its pricing model.

How often is gamma updated?

Gamma is recalculated whenever new trade or order book data is available. On active markets, this can be every few seconds. On illiquid markets, updates may be less frequent. Most scanners timestamp their data so you can see how recent it is.

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