Mid Price Spread Schema for Market Makers
Resolved Markets enables market makers to capture alpha by providing continuous orderbook snapshots from Polymarket's fragmented prediction markets, revealing arbitrage opportunities, inventory imbalances, and optimal pricing across crypto, sports, economics, and weather categories. Access 20Hz orderbook captures with full bid/ask depth, millisecond timestamps, and WebSocket streaming to identify moments when temporary price dislocations create profit opportunities with minimal risk. The platform covers 100+ actively traded markets across all categories, providing the comprehensive market coverage needed to build hedged positions and exploit cross-market inefficiencies without the operational burden of monitoring Polymarket directly.
Resolved Markets ships Mid Price Spread Schema for liquidity providers working on the structured prediction-market data layer. Every quote refresh, cancel, and adversely selected fill on best_bid, best_ask, mid_price, spread, bids[], asks[] is captured at tick resolution.
Data challenges Market Makers run into
Mid Price Spread Schema from Resolved Markets is built around the data gaps Market Makers hit when they try to work with raw Polymarket feeds.
Polymarket orderbook monitoring requires continuous infrastructure investment
Market makers building on Polymarket must operate 24/7 monitoring infrastructure, maintaining WebSocket connections, parsing events, and updating position tracking systems. This requires dedicated engineering resources and operational overhead. Additionally, Polymarket's public API provides limited orderbook history and event detail, forcing custom infrastructure development. Resolved Markets eliminates this build burden—instantly access standardized orderbook snapshots at 20Hz with millisecond precision, allowing you to deploy making strategies without infrastructure engineering.
Latency between order placement and execution creates slippage
Market-making profitability depends on executing faster than competitors. Polymarket's native API introduces 500ms-2s latency between your order submission and trade execution confirmation, plus additional latency querying current orderbooks to update your positions. Resolved Markets provides WebSocket push updates with millisecond precision, reducing decision latency from 1-2 seconds to <100ms. Your algorithms receive price updates the instant orderbooks change, enabling tighter spreads and higher fill rates before competitors react.
Multi-market position monitoring lacks coordination
Market makers tracking positions across multiple prediction markets (crypto futures, sports betting, economics markets) must manually reconcile holdings, exposures, and hedging needs. Resolved Markets captures synchronized orderbooks across 100+ markets with unified timestamps, enabling your position tracking systems to instantly identify hedging opportunities. When a BTC prediction market shifts 2% in your favor, but correlated sports markets shift 1%, you immediately quantify your net exposure and optimal rehedging strategy.
Price discovery signals are delayed or incomplete
Prediction market prices sometimes lead spot/derivatives prices (especially in crypto), creating arbitrage opportunities. However, detecting these dislocations requires simultaneous access to both prediction and spot market data with minimal latency. Most market makers miss dislocation moments because they monitor prediction markets via Polymarket's slow API. Resolved Markets' high-frequency orderbook capture reveals the exact moments when prediction prices diverge from fair value, giving you the timing needed to execute profitable hedges before prices revert.
Built for quantitative work on Mid Price Spread Schema
Orderbook-level prediction-market data that doesn't exist anywhere else.
Identify profitable spread-narrowing opportunities instantly
Market inefficiencies in prediction markets often manifest as bid/ask spread widening—when uncertainty spikes, spreads can double from 0.5 to 1.0 cents on close calls. Resolved Markets' 20Hz snapshots capture these moments, enabling instant quote submission that narrows spread and captures the bid/ask midpoint as profit. Your algorithms detect spread widening within milliseconds and deploy quotes before competitors, earning reliable spread-capture revenue as the market reverts to normal spreads.
Execute arbitrage with minimal latency and slippage
Crypto prediction markets sometimes price moves differently than perpetual futures or spot markets. BTC prediction might quote 68,000-69,000 while spot exchanges quote 68,500, creating 500 point spread opportunity. Resolved Markets captures these dislocations through synchronized orderbook snapshots with millisecond timestamps, revealing the exact windows when arbitrage exists. Execute a short prediction market position and long spot market position with minimal slippage, locking in the dislocation profit before prices converge.
Optimize inventory positioning across linked markets
Large prediction market positions require hedging across multiple markets—a long BTC prediction position might be hedged against short volatility predictions and long spot BTC. Resolved Markets tracks all linked markets simultaneously, calculating your net exposure and suggesting optimal rehedging levels. When position deltas shift, your algorithms receive synchronized updates across all relevant markets, preventing gaps where you're temporarily exposed and unhedged.
Automate quote generation with data-driven pricing models
Manual quote generation requires analyzing each market's spread, volatility, and order flow—time-consuming when monitoring dozens of markets. Resolved Markets' historical orderbook data supports backtesting of pricing models: analyze how competitive spreads should vary with order volume, market depth, and hourly volume patterns. Deploy models incorporating these insights, then feed real-time WebSocket updates directly into your quoting engine. Automatically adjust spreads tighter in high-volume periods and wider during slow periods, optimizing profitability without constant manual oversight.
How Market Makers use Mid Price Spread Schema
Seven categories, hundreds of markets
Prediction markets across crypto, sports, economics, weather, and more — live and historical orderbook data, all queryable through one API.
Crypto
BTC, ETH, SOL, XRP — up/down markets every 5m to 1d.
Equities
S&P 500 (SPX) daily open — up or down predictions.
Social
Elon Musk tweet counts — weekly prediction ranges.
Sports
NBA, NFL, EPL — game outcomes and season predictions.
Economics
Fed decisions, jobs reports — FOMC meetings and macro data.
Weather
44 cities daily — temperature, hurricanes, Arctic ice.
Hyperliquid
BTC, ETH, SOL, XRP perp orderbooks — 1/sec sampling.
Tick-level orderbook snapshots
Every snapshot includes full bid/ask depth, mid prices, spreads, and crypto spot price.
| Side | Bid | Size | Ask | Size | Spread |
|---|---|---|---|---|---|
| UP | 0.5400 | 1,240 | 0.5500 | 1,100 | 1.00% |
| UP | 0.5300 | 980 | 0.5600 | 1,450 | 3.00% |
| UP | 0.5200 | 1,560 | 0.5700 | 890 | 5.00% |
| UP | 0.5100 | 2,100 | 0.5800 | 2,300 | 7.00% |
| UP | 0.5000 | 1,800 | 0.5900 | 1,700 | 9.00% |
| UP | 0.4900 | 3,200 | 0.6000 | 3,100 | 11.00% |
cryptoLowCardinality(String)BTCtimeframeLowCardinality(String)5mtoken_sideEnum8('UP','DOWN')UPtimestampDateTime64(3)2026-05-09 03:14:12.061crypto_priceFloat64$80,471.01best_bidFloat640.5400best_askFloat640.5500mid_priceFloat640.5450spreadFloat640.0100bidsArray(Tuple(F64,F64))[(0.54,1240),...]asksArray(Tuple(F64,F64))[(0.55,1100),...]Comprehensive market coverage
Prediction markets across multiple categories, captured continuously with high-frequency precision.
Mid Price Spread Schema ships with
What Market Makers build with Mid Price Spread Schema
Up and running in minutes
Three steps from signup to live Mid Price Spread Schema in your application.
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Sign Up FreeExplore the API
Browse 11 endpoints with live examples. Test requests directly from the docs.
API ReferenceStart Building
Integrate live Mid Price Spread Schema into your research pipeline, trading bot, or analytics platform.
fetch('/v1/markets/live', { headers: { 'X-API-Key': key } })
curl -H 'X-API-Key: rm_xxx' 'https://api.resolvedmarkets.com/v1/markets/history/recent?limit=20'includebook=true on any /api/snapshot callWiring Mid Price Spread Schema into your workflow
Market makers deploy Mid Price Spread Schema via WebSocket streaming for live quoting decisions and the REST API for backtesting. The 20Hz capture in Mid Price Spread Schema ensures no orderbook state changes are missed between quote updates.
- Databricks notebook starter kit for Mid Price Spread Schema
- Native ClickHouse JDBC/ODBC connector
- Snowflake Snowpipe ingest for streaming Mid Price Spread Schema
Why Market Makers pick Mid Price Spread Schema
- 20Hz orderbook capture with sub-100ms WebSocket latency eliminates infrastructure burden and execution delay that competitors face
- Full bid/ask depth arrays enable data-driven pricing models that optimize spread width for profitability across all market conditions
- Unified access to 100+ cross-category markets enables portfolio-level position management and hedging optimization impossible with fragmented APIs
- Historical microstructure dataset supports rigorous strategy backtesting—validate your making algorithms against months of real orderbook data before deploying capital
Why Mid Price Spread Schema matters
Mid Price Spread Schema matters for market makers because slow data is silent adverse selection. DateTime64(3) timestamps with full bid/ask arrays on best_bid, best_ask, mid_price, spread, bids[], asks[] closes that gap, so liquidity providers can model the same depth dynamics they would on a centralized venue.
Mid Price Spread Schema in context
Liquidity provision on Polymarket is competitive enough that Mid Price Spread Schema is no longer optional. Market makers need DateTime64(3) timestamps with full bid/ask arrays to model queue position, identify quote flicker, and avoid adverse selection across best_bid, best_ask, mid_price, spread, bids[], asks[].
Frequently asked: Mid Price Spread Schema for Market Makers
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How does WebSocket latency compare to directly monitoring Polymarket's API?
Polymarket's public WebSocket API delivers updates every 500ms-1s, with additional latency in parsing and processing. Resolved Markets' purpose-built WebSocket stream delivers 20Hz updates (every 50ms) with parsed orderbook snapshots ready to feed directly into your pricing algorithms. This 10-20x latency reduction enables you to detect arbitrage moments and submit competitive quotes before Polymarket's own API subscribers react, giving you first-mover advantage on profitable opportunities.
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Can I use Resolved Markets to arbitrage between Polymarket and other crypto/sports betting platforms?
Yes—many market makers run arbitrage between Polymarket prediction markets and traditional betting exchanges, sports betting sites, or crypto derivatives. Resolved Markets provides the high-frequency Polymarket orderbook data; integrate external exchange APIs to detect dislocations instantly. Our millisecond timestamps enable precise correlation—identify the exact moment when Polymarket's BTC price diverges from Kraken, execute the arbitrage, and profit from the convergence. Historical data lets you backtest dislocation detection strategies.
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What order types and market conditions does Resolved Markets capture?
Resolved Markets captures complete orderbook state snapshots at 20Hz—every resting order's price, quantity, and side. This includes limit orders, partially filled orders, and cancelled orders. Snapshots reflect the exact orderbook state at that moment, enabling you to simulate your quoting behavior against real historical orderbooks. Capture rates may vary during extreme volatility (we maintain 20Hz during crypto events, standard intervals during low-activity sports/economics markets).
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How can I backtest market-making strategies against historical orderbook data?
Export historical orderbook snapshots for any time period—your strategy simulator receives the exact same data feed (orderbook state, timestamps, market conditions) that your live algorithm would. Simulate order placement, execution against the orderbook, inventory changes, and profit/loss. ClickHouse storage enables rapid time-window queries, so you can quickly test strategy variations across weeks or months of data without extracting gigabytes of files.
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Does Resolved Markets capture all liquidity on Polymarket, or do some orders/pools go unrecorded?
Resolved Markets captures all resting orders and liquidity pools visible on Polymarket's orderbook at snapshot time with full depth. Our 20Hz sampling ensures you capture ~99% of meaningful order changes (some ultra-rapid order placements and cancellations may be missed due to sampling). For deterministic backtesting, historical snapshots represent the ground truth state available to any market participant at that moment, enabling realistic simulation of your execution against actual market conditions.
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How do market makers use Mid Price Spread Schema for spread optimization?
Market makers replay Mid Price Spread Schema to identify optimal spread levels at each volatility regime. DateTime64(3) timestamps with full bid/ask arrays captures the rapid quote refreshes that drive realized vs quoted spread measurement.
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What markets are best for market making with Mid Price Spread Schema?
High-volume Polymarket contracts in best_bid, best_ask, mid_price, spread, bids[], asks[] with consistent daily activity. Mid Price Spread Schema exposes deep bid/ask arrays so market makers can size queue position before quoting.
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How do market makers manage inventory risk on Mid Price Spread Schema?
Full depth arrays inside Mid Price Spread Schema reveal queue position, competing liquidity, and potential adverse selection. Historical replay shows how inventory accumulates under different conditions.
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Is Mid Price Spread Schema compatible with Apache Iceberg or Delta Lake?
Yes. Bulk Parquet exports of Mid Price Spread Schema drop directly into Iceberg or Delta tables for time-travel queries and ACID semantics.
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Can I use Mid Price Spread Schema with dbt?
Yes. Most teams build dbt models that consume Mid Price Spread Schema via the ClickHouse connector and derive downstream features (spread, depth imbalance, mid-price velocity).