Prediction Market Arbitrage Api

Find arbitrage opportunities across Polymarket and Kalshi prediction markets via AIsa API. Scan sports markets for cross-platform price discrepancies, compare real-time odds, verify orderbook liquidity. Use when user asks about: prediction market arbitrage, cross-platform price differences, sports betting arbitrage, odds comparison, risk-free profit, market inefficiencies.

Find arbitrage opportunities across Polymarket and Kalshi via AIsa API.

Setup

bash

export AISA_API_KEY="your-key"

Get a key at aisa.one ($0.01/query, pay-as-you-go).

Workflow

Finding arbitrage involves these steps:

1. Scan matching markets across platforms (scan for bulk, match for specific)
2. Review spreads — the tool calculates price differences automatically
3. Verify liquidity — use prediction_market_client.py orderbooks to check depth before acting

Quick Examples

Scan a sport for arbitrage

bash

# Scan all NBA markets on a date — shows spreads automatically
python3 {baseDir}/scripts/arbitrage_finder.py scan nba --date 2025-04-01

Analyze a specific market

bash

# By Polymarket slug
python3 {baseDir}/scripts/arbitrage_finder.py match --polymarket-slug <slug>

# By Kalshi ticker
python3 {baseDir}/scripts/arbitrage_finder.py match --kalshi-ticker <ticker>

Verify liquidity before acting

bash

# Check orderbook depth on both sides
python3 {baseDir}/scripts/prediction_market_client.py polymarket orderbooks --token-id <id>
python3 {baseDir}/scripts/prediction_market_client.py kalshi orderbooks --ticker <ticker>

Commands

arbitrage_finder.py — Automated Detection

bash

python3 {baseDir}/scripts/arbitrage_finder.py scan <sport> --date <YYYY-MM-DD> [--min-spread <pct>] [--min-liquidity <usd>] [--json]
python3 {baseDir}/scripts/arbitrage_finder.py match --polymarket-slug <slug> [--min-spread <pct>] [--min-liquidity <usd>] [--json]
python3 {baseDir}/scripts/arbitrage_finder.py match --kalshi-ticker <ticker> [--min-spread <pct>] [--min-liquidity <usd>] [--json]

Sports: nba, nfl, mlb, nhl, soccer, tennis.

prediction_market_client.py — Raw Market Data

Use for manual price checks and deeper analysis.

bash

# Search markets
python3 {baseDir}/scripts/prediction_market_client.py polymarket markets --search <kw> --status open --limit 5
python3 {baseDir}/scripts/prediction_market_client.py kalshi markets --search <kw> --status open --limit 5

# Get prices (use token_id / market_ticker from markets output)
python3 {baseDir}/scripts/prediction_market_client.py polymarket price <token_id>
python3 {baseDir}/scripts/prediction_market_client.py kalshi price <market_ticker>

# Cross-platform sports matching
python3 {baseDir}/scripts/prediction_market_client.py sports by-date <sport> --date <YYYY-MM-DD>
python3 {baseDir}/scripts/prediction_market_client.py sports matching (--polymarket-slug <slug> | --kalshi-ticker <ticker>)

# Orderbook depth
python3 {baseDir}/scripts/prediction_market_client.py polymarket orderbooks --token-id <id>
python3 {baseDir}/scripts/prediction_market_client.py kalshi orderbooks --ticker <ticker>

Understanding Arbitrage

Arbitrage exists when the combined cost of all mutually exclusive outcomes across platforms is less than 1.0:

"Yes" at 0.40 on Polymarket + "No" at 0.55 on Kalshi = cost 0.95, guaranteed payout 1.00 → 5.3% profit.

Always verify orderbook depth — a spread without liquidity is not executable.

Security & Permissions

Requires: AISA_API_KEY environment variable.

All operations are read-only via HTTPS GET to api.aisa.one. Arbitrage spreads are calculated locally. No trades executed, no wallets connected, no personal data sent beyond the API key. Every response includes usage.cost and usage.credits_remaining.

Full docs: AIsa API Reference.