DraftKings & FanDuel Arbitrage with Python

Not all sportsbooks move their lines at the same speed. This tutorial demonstrates how to use the Terminal Software API to specifically isolate mispriced targets on DraftKings and FanDuel.

Environment Setup

We will use standard Python libraries to parse the JSON array returned by the Recon Engine.

pip install requests pandas

Targeted API Query

Pass your unkey token to the matrix. The engine automatically aggregates the math, so we only need to extract the final Expected Value metric.

import requests
import pandas as pd

API_KEY = "term_live_YOUR_KEY_HERE"
headers = {"Authorization": f"Bearer {API_KEY}"}

data = requests.get("https://api.terminalsoftware.online/v1/sports/edges", headers=headers).json()
df = pd.DataFrame(data)

Cross-Book Filtration

We will filter our DataFrame to strictly return high-value edges (+EV > 3.0%) that specifically exist on either DraftKings or FanDuel, ignoring the rest of the global market.

# Define our target books
target_books = ['draftkings', 'fanduel']

# Filter the matrix
prime_edges = df[(df['sportsbook'].str.lower().isin(target_books)) & (df['ev'] > 3.0)]

print("=== PRIME BOOKMAKER TARGETS ===")
for index, row in prime_edges.iterrows():
    book = row['sportsbook'].upper()
    print(f"[{book}] Strike: {row['target']} | Market: {row['market']} | Edge: +{row['ev']}%")

By narrowing your bot's focus to specific bookmakers, you can route your automated bet slips faster and manage your bankroll with extreme precision.