FanDuel DFS slates and salaries API

Pull today's FanDuel DFS slates and salaries next to the prop lines for the same players.

Slates

Salary cap, start time, game count and player count per slate and sport.

Players

Salary, position, team, fantasy points per game and injury status, highest salary first.

Filters

Position, team and injured, with paging.

What it returns now

Real rows, 5 min delay, as of 3:25 PM ET

{
  "data": [
    {
      "id": "136257",
      "sport": "CFB",
      "label": "Fri Main",
      "starts_at": "2026-11-07T00:00:00.000Z",
      "salary_cap": 60000,
      "games": 5,
      "started": false,
      "players": 346,
      "players_read_at": "2026-11-06T18:18:33.788Z"
    }
  ]
}

Endpoints and parameters

Code

curl "https://fanduelapi.com/api/v1/dfs/slates?sport=NBA&started=false" \
  -H "Authorization: Bearer $FANDUEL_API_KEY"

import os, requests

r = requests.get(
    "https://fanduelapi.com/api/v1/dfs/slates",
    params={"sport": "NBA", "started": "false"},
    headers={"Authorization": f"Bearer {os.environ['FANDUEL_API_KEY']}"},
)
r.raise_for_status()
body = r.json()
print(body["meta"])          # plan, delay_seconds, as_of, source_status
for row in body["data"][:5]:
    print(row)

Keys look like fd_.... Keep one in the FANDUEL_API_KEY environment variable on your server, never in browser code. Every response's meta says which plan answered, how far behind it is and how fresh the collection is.

Which plans include it

• FreeIncluded, 5 minutes behind
• DeveloperIncluded, real time
• ProductionIncluded, real time
• ScaleIncluded, real time

Read from the plans on the pricing page. Every request counts against the monthly and per-minute allowance; request quotas explains how.

Works well with

• Players and resultsJoin each FanDuel line to what actually happened, and train on graded outcomes instead of guesses./api/v1/players
• Props feedRead the whole player prop board in one call, already normalised, with where each line opened./api/v1/props
• CSV and NDJSON exportsLoad a slate or a season of line history straight into pandas, DuckDB or a spreadsheet./api/v1/export