# Sports Betting Odds Scraper - NFL, NBA, MLB, NHL & Soccer (`fetchfinch/sports-odds-scraper`) Actor

Scrape live and upcoming sportsbook odds across NFL, NBA, MLB, NHL, NCAA, EPL, MLS, and more. Export normalized moneyline, spread, totals, decimal odds, American odds, and implied probability.

- **URL**: https://apify.com/fetchfinch/sports-odds-scraper.md
- **Developed by:** [Fetch Finch](https://apify.com/fetchfinch) (community)
- **Categories:** Sports, Developer tools, Automation
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 1,000 odds rows

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Sports Betting Odds Scraper - NFL, NBA, MLB, NHL & Soccer

Collect live and upcoming sportsbook odds across major football, basketball, baseball, hockey, and soccer competitions. Results are delivered as a clean dataset that is ready for analysis, dashboards, alerts, and automated workflows.

### How to use

1. Select one or more competitions.
2. Choose the markets and, optionally, specific sportsbooks.
3. Optionally set an event date range under Advanced options. Dates use UTC. If left empty, the Actor checks from today through the next 30 days.
4. Start the Actor and open the results in the Output tab.

The default configuration collects NFL moneyline, point spread, and total-points odds from all available sportsbooks.

### Supported markets

- Moneyline
- Point spread
- Total points

### Output

Each dataset row represents one event, market, sportsbook, and outcome. Common fields include:

- event and team names, abbreviations, and start time;
- competition, market, outcome, and sportsbook identifiers;
- decimal odds, American odds, implied probability, and line or total values;
- live status and collection timestamps.

A run summary is also available with row counts, event counts, cache usage, request counts, and any competition errors.

### Example tasks

Use the example tasks below to try common configurations without setting up the inputs yourself.

- [Get NFL moneyline, spread and totals odds](https://apify.com/fetchfinch/sports-odds-scraper/examples/nfl-main-markets)
- [Compare NFL moneyline odds by sportsbook](https://apify.com/fetchfinch/sports-odds-scraper/examples/nfl-moneyline-books)
- [Get MLB moneyline, spread and totals odds](https://apify.com/fetchfinch/sports-odds-scraper/examples/mlb-main-markets)

# Actor input Schema

## `competitions` (type: `array`):

Select one or more competitions. Each selected competition uses one Sportsbook API request.

## `marketTypes` (type: `array`):

Select the main markets to include. Filtering happens after the single competition request.

## `bookmakers` (type: `array`):

Optional sportsbook filter. Leave empty to include every sportsbook returned for the selected events.

## `startTimeFrom` (type: `string`):

Optional first event date in UTC. Leave empty to start at the beginning of today.

## `startTimeTo` (type: `string`):

Optional last event date in UTC. Leave empty to include the next 30 days.

## `maxEvents` (type: `integer`):

Maximum events per competition. Zero includes all events.

## `enableCache` (type: `boolean`):

Cache competition metadata and optional short-lived snapshots in a named Apify key-value store.

## `cacheStoreName` (type: `string`):

Persistent named key-value store used between runs. Keep this stable for scheduled collection.

## `competitionCacheTtlHours` (type: `integer`):

How long the competition catalog remains valid, in hours.

## `responseCacheTtlMinutes` (type: `integer`):

Cache complete odds responses for this many minutes. Keep at zero when every scheduled run must fetch fresh odds.

## `resolveCompetitionNames` (type: `boolean`):

Refresh the provider competition catalog so full names and slugs can also be entered. Costs one extra request on a cold catalog cache.

## `maxCompetitionsPerRun` (type: `integer`):

Safety cap on upstream competition requests.

## Actor input object example

```json
{
  "competitions": [
    "NFL"
  ],
  "marketTypes": [
    "MONEYLINE",
    "POINT_SPREAD",
    "POINT_TOTAL"
  ],
  "bookmakers": [],
  "maxEvents": 0,
  "enableCache": true,
  "cacheStoreName": "sports-odds-scraper-cache",
  "competitionCacheTtlHours": 24,
  "responseCacheTtlMinutes": 0,
  "resolveCompetitionNames": false,
  "maxCompetitionsPerRun": 5
}
```

# Actor output Schema

## `results` (type: `string`):

One row per event, market, sportsbook, and outcome.

## `summary` (type: `string`):

Run-level counts, cache usage, quota information, and any competition errors.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("fetchfinch/sports-odds-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("fetchfinch/sports-odds-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call fetchfinch/sports-odds-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,fetchfinch/sports-odds-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/wfzQ60I1Fgj1iwp6p/builds/fid0FWRnQgSpZOYxr/openapi.json