Sports Markets

Sports prediction market data API — NBA, NFL, EPL

Polymarket lists discrete-outcome markets on every NBA, NFL, and English Premier League game. Resolved Markets captures their orderbooks event-driven at ~2 Hz, stores every snapshot with full bid/ask depth in ClickHouse, and exposes the data through the same REST + WebSocket + MCP interface used for crypto markets. No 31-day retention cliff. No category-specific surcharges.

Last updated:

  • NBA · NFL · EPLLeagues covered
  • ~2 HzCapture rate
  • UnlimitedHistorical retention
  • Pro / EnterpriseTier required

What is captured

Each Polymarket sports market has two tokens — UP (one team wins) and DOWN (the other) — and each token has its own orderbook in USDC probabilities (0.01–0.99). For every event from the upstream Polymarket WebSocket, we apply the delta in memory, derive best bid/ask, mid, spread, depth at the top 5 levels, and persist a full snapshot if the top-of-book changed. Every snapshot carries:

  • Full bids and asks arrays as Array(Tuple(price, size))
  • best_bid, best_ask, mid, spread
  • Cumulative depth at the top 5 price levels per side
  • Monotonic sequence_number (gap detection)
  • event_timestamp from Polymarket and capture_timestamp from our pipeline
  • Token side (UP / DOWN) and the parent condition_id

Pull live NBA orderbooks

# 1. List active NBA markets
curl -s "https://api.resolvedmarkets.com/v1/markets/live?category=sports&subcategory=NBA" \
  -H "X-API-Key: rm_your_key" | jq '.markets[] | {slug, condition_id, question}'

# 2. Pull live orderbook for one market
curl -s "https://api.resolvedmarkets.com/v1/markets/<condition_id>/orderbook" \
  -H "X-API-Key: rm_your_key" | jq '.up.bids[0:5]'

# 3. Pull last 4 hours of snapshots for time-series analysis
curl -s "https://api.resolvedmarkets.com/v1/markets/<condition_id>/snapshots?limit=500" \
  -H "X-API-Key: rm_your_key" | jq '.snapshots[0]'

Use cases

  • In-game probability research. Reconstruct minute-by-minute implied probabilities through the final quarter of close games and benchmark against win-probability models.
  • Spread compression studies. Measure how spreads tighten as resolution approaches — Polymarket sports markets often see sub-cent spreads in the last minutes of play.
  • Cross-market arbitrage signals. Compare Polymarket discrete-outcome prices against centralized sportsbooks, in-play odds feeds, or DraftKings markets where regulation allows.
  • AI agent reporting. Wire the MCP server into a Claude or ChatGPT agent and ask "what was the implied probability of the Lakers winning at the start of the 4th quarter on game X?"

Frequently asked questions