Automatio

How to Scrape Action Network Sports Betting Data

Learn how to scrape Action Network for real-time betting odds, public splits, and expert picks. Build models with sharp money data and line movement trends.

Start Scraping Free
Action Network favicon
actionnetwork.comHard
Coverage:United StatesCanadaUnited KingdomGlobal
Available Data9 fields
TitlePriceLocationDescriptionImagesSeller InfoPosting DateCategoriesAttributes
All Extractable Fields
Game TitleLeague (NFL, NBA, etc.)Away Team NameHome Team NamePoint SpreadOver/Under TotalsMoneyline OddsPublic Betting PercentageTicket Count PercentageSharp Action IndicatorsExpert Pick RecommendationExpert Win/Loss RecordAuthor NamePublication DateSportsbook NameInjury Report Status
Technical Requirements
JavaScript Required
No Login
Has Pagination
No Official API
Anti-Bot Protection Detected
DataDomeCloudflareRate LimitingIP BlockingBrowser Fingerprinting

Anti-Bot Protection Detected

DataDome
Real-time bot detection with ML models. Analyzes device fingerprint, network signals, and behavioral patterns. Common on e-commerce sites.
Cloudflare
Enterprise-grade WAF and bot management. Uses JavaScript challenges, CAPTCHAs, and behavioral analysis. Requires browser automation with stealth settings.
Rate Limiting
Limits requests per IP/session over time. Can be bypassed with rotating proxies, request delays, and distributed scraping.
IP Blocking
Blocks known datacenter IPs and flagged addresses. Requires residential or mobile proxies to circumvent effectively.
Browser Fingerprinting
Identifies bots through browser characteristics: canvas, WebGL, fonts, plugins. Requires spoofing or real browser profiles.

About Action Network

Learn what Action Network offers and what valuable data can be extracted from it.

Market Authority in Sports Betting

Action Network is the leading sports betting media company providing real-time odds, expert analysis, and performance tracking. Owned by Better Collective, it serves as the primary hub for bettors looking to gain a technical advantage in the North American market. The platform aggregates lines from major legal sportsbooks, making it a critical source for market sentiment.

Value of Betting Data

The platform's data is uniquely valuable because it provides "Public Splits" and "Sharp Action" indicators. These metrics show where the general public is betting versus where professional gamblers (sharps) are placing their money. Scraping this data allows analysts to identify market value and reverse line movement that is often hidden behind complex interfaces.

Advanced Sports Analytics

By extracting data from Action Network, developers can feed live odds into predictive models, automate arbitrage detection, and audit the historical win rates of high-profile handicappers. The site contains structured data on injuries, weather conditions, and historical closing line values that are essential for any serious sports betting strategy.

About Action Network

Why Scrape Action Network?

Discover the business value and use cases for extracting data from Action Network.

Monitor real-time line movements to identify market discrepancies across different sportsbooks.

Track public betting splits versus professional sharp action to follow professional money flows.

Aggregate expert picks and historical performance data for ROI tracking and sentiment analysis.

Feed live odds data into automated arbitrage betting bots or predictive machine learning models.

Analyze historical closing line values (CLV) to evaluate the efficiency of sports betting markets.

Perform competitive research on sportsbook promotions and bonus codes across different states.

Scraping Challenges

Technical challenges you may encounter when scraping Action Network.

Aggressive anti-bot protection via DataDome requires advanced browser fingerprinting bypass and stealth techniques.

The site uses Next.js and dynamic loading, meaning data is often not present in the initial HTML source and requires JS rendering.

Frequent changes to the front-end CSS classes make selectors brittle and require constant maintenance of scraping scripts.

Aggressive rate limiting on high-traffic pages like 'Live Odds' can lead to immediate IP blacklisting if not carefully managed.

Scrape Action Network with AI

No coding required. Extract data in minutes with AI-powered automation.

How It Works

1

Describe What You Need

Tell the AI what data you want to extract from Action Network. Just type it in plain language — no coding or selectors needed.

2

AI Extracts the Data

Our artificial intelligence navigates Action Network, handles dynamic content, and extracts exactly what you asked for.

3

Get Your Data

Receive clean, structured data ready to export as CSV, JSON, or send directly to your apps and workflows.

Why Use AI for Scraping

Bypasses complex DataDome and Cloudflare anti-bot measures automatically without custom code.
Utilizes a visual no-code selector to easily target nested betting tables and dynamic odds widgets.
Enables scheduled runs to capture fast-moving betting lines during peak hours like NFL Sunday mornings.
Integrates proxy rotation out of the box to avoid IP bans during high-frequency data extraction.
Start Scraping Free
No credit card requiredFree tier availableNo setup needed

AI makes it easy to scrape Action Network without writing any code. Our AI-powered platform uses artificial intelligence to understand what data you want — just describe it in plain language and the AI extracts it automatically.

How to scrape with AI:
  1. Describe What You Need: Tell the AI what data you want to extract from Action Network. Just type it in plain language — no coding or selectors needed.
  2. AI Extracts the Data: Our artificial intelligence navigates Action Network, handles dynamic content, and extracts exactly what you asked for.
  3. Get Your Data: Receive clean, structured data ready to export as CSV, JSON, or send directly to your apps and workflows.
Why use AI for scraping:
  • Bypasses complex DataDome and Cloudflare anti-bot measures automatically without custom code.
  • Utilizes a visual no-code selector to easily target nested betting tables and dynamic odds widgets.
  • Enables scheduled runs to capture fast-moving betting lines during peak hours like NFL Sunday mornings.
  • Integrates proxy rotation out of the box to avoid IP bans during high-frequency data extraction.

No-Code Web Scrapers for Action Network

Point-and-click alternatives to AI-powered scraping

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape Action Network. These tools use visual interfaces to select elements, but they come with trade-offs compared to AI-powered solutions.

Typical Workflow with No-Code Tools

1
Install browser extension or sign up for the platform
2
Navigate to the target website and open the tool
3
Point-and-click to select data elements you want to extract
4
Configure CSS selectors for each data field
5
Set up pagination rules to scrape multiple pages
6
Handle CAPTCHAs (often requires manual solving)
7
Configure scheduling for automated runs
8
Export data to CSV, JSON, or connect via API

Common Challenges

Learning curve

Understanding selectors and extraction logic takes time

Selectors break

Website changes can break your entire workflow

Dynamic content issues

JavaScript-heavy sites often require complex workarounds

CAPTCHA limitations

Most tools require manual intervention for CAPTCHAs

IP blocking

Aggressive scraping can get your IP banned

No-Code Web Scrapers for Action Network

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape Action Network. These tools use visual interfaces to select elements, but they come with trade-offs compared to AI-powered solutions.

Typical Workflow with No-Code Tools
  1. Install browser extension or sign up for the platform
  2. Navigate to the target website and open the tool
  3. Point-and-click to select data elements you want to extract
  4. Configure CSS selectors for each data field
  5. Set up pagination rules to scrape multiple pages
  6. Handle CAPTCHAs (often requires manual solving)
  7. Configure scheduling for automated runs
  8. Export data to CSV, JSON, or connect via API
Common Challenges
  • Learning curve: Understanding selectors and extraction logic takes time
  • Selectors break: Website changes can break your entire workflow
  • Dynamic content issues: JavaScript-heavy sites often require complex workarounds
  • CAPTCHA limitations: Most tools require manual intervention for CAPTCHAs
  • IP blocking: Aggressive scraping can get your IP banned

Code Examples

import requests
from bs4 import BeautifulSoup

# Note: This basic request will likely be blocked by DataDome without advanced headers/proxies
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36'
}

def scrape_action_news():
    url = 'https://www.actionnetwork.com/nfl/odds'
    try:
        response = requests.get(url, headers=headers)
        response.raise_for_status()
        soup = BeautifulSoup(response.text, 'html.parser')
        # Example: Find all game titles on the odds page
        games = soup.find_all('h3')
        for game in games:
            print(f'Matchup found: {game.get_text(strip=True)}')
    except requests.exceptions.RequestException as e:
        print(f'Blocked by Anti-Bot or Error: {e}')

if __name__ == '__main__':
    scrape_action_news()

When to Use

Best for static HTML pages where content is loaded server-side. The fastest and simplest approach when JavaScript rendering isn't required.

Advantages

  • ●Fastest execution (no browser overhead)
  • ●Lowest resource consumption
  • ●Easy to parallelize with asyncio
  • ●Great for APIs and static pages

Limitations

  • ●Cannot execute JavaScript
  • ●Fails on SPAs and dynamic content
  • ●May struggle with complex anti-bot systems

How to Scrape Action Network with Code

Python + Requests
import requests
from bs4 import BeautifulSoup

# Note: This basic request will likely be blocked by DataDome without advanced headers/proxies
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36'
}

def scrape_action_news():
    url = 'https://www.actionnetwork.com/nfl/odds'
    try:
        response = requests.get(url, headers=headers)
        response.raise_for_status()
        soup = BeautifulSoup(response.text, 'html.parser')
        # Example: Find all game titles on the odds page
        games = soup.find_all('h3')
        for game in games:
            print(f'Matchup found: {game.get_text(strip=True)}')
    except requests.exceptions.RequestException as e:
        print(f'Blocked by Anti-Bot or Error: {e}')

if __name__ == '__main__':
    scrape_action_news()
Python + Playwright
import asyncio
from playwright.async_api import async_playwright

async def scrape_odds():
    async with async_playwright() as p:
        # Launching with stealth-like behavior is necessary for Action Network
        browser = await p.chromium.launch(headless=True)
        context = await browser.new_context(user_agent='Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36')
        page = await context.new_page()
        
        await page.goto('https://www.actionnetwork.com/nba/odds')
        # Wait for the specific odds container to load via JavaScript
        await page.wait_for_selector('div[class*="OddsTable"]')
        
        # Extract data using JS evaluation
        game_info = await page.eval_on_selector_all('div[class*="GameName"]', 'elements => elements.map(e => e.innerText)')
        
        for game in game_info:
            print(f'NBA Matchup: {game}')
            
        await browser.close()

asyncio.run(scrape_odds())
Python + Scrapy
import scrapy

class ActionSpider(scrapy.Spider):
    name = 'action_spider'
    start_urls = ['https://www.actionnetwork.com/nfl/odds']

    def parse(self, response):
        # Action Network requires a JS-rendering middleware like Scrapy-Playwright
        # This example assumes the middleware is configured
        for matchup in response.css('div.odds-row'):
            yield {
                'team': matchup.css('span.team-name::text').get(),
                'spread': matchup.css('div.spread-value::text').get(),
                'moneyline': matchup.css('div.moneyline-value::text').get()
            }

        # Handling basic pagination for article archives
        next_page = response.css('a.next-page-link::attr(href)').get()
        if next_page:
            yield response.follow(next_page, self.parse)
Node.js + Puppeteer
const puppeteer = require('puppeteer-extra');
const StealthPlugin = require('puppeteer-extra-plugin-stealth');
puppeteer.use(StealthPlugin());

(async () => {
  const browser = await puppeteer.launch({ headless: true });
  const page = await browser.newPage();
  
  // Navigate to odds page and wait for network to settle
  await page.goto('https://www.actionnetwork.com/nfl/odds', { waitUntil: 'networkidle2' });
  
  // Target the game header elements
  const results = await page.evaluate(() => {
    const items = Array.from(document.querySelectorAll('h3'));
    return items.map(item => item.innerText);
  });
  
  console.log('Found Games:', results);
  await browser.close();
})();

What You Can Do With Action Network Data

Explore practical applications and insights from Action Network data.

Odds Comparison Dashboard

Create a tool that compares betting lines across various sportsbooks to find the highest possible payout for any given game.

How to implement:

  1. 1Scrape live odds from sport-specific pages (e.g., /nba/odds).
  2. 2Map different sportsbook names to a unified internal ID.
  3. 3Identify the 'Best Price' for both the spread and moneyline.
  4. 4Refresh data every 2-5 minutes to ensure accuracy.

Use Automatio to extract data from Action Network and build these applications without writing code.

What You Can Do With Action Network Data

  • Odds Comparison Dashboard

    Create a tool that compares betting lines across various sportsbooks to find the highest possible payout for any given game.

    1. Scrape live odds from sport-specific pages (e.g., /nba/odds).
    2. Map different sportsbook names to a unified internal ID.
    3. Identify the 'Best Price' for both the spread and moneyline.
    4. Refresh data every 2-5 minutes to ensure accuracy.
  • Sharp Money Alert System

    Automate the detection of 'Sharp Action' by identifying games where the betting line moves against the public majority.

    1. Extract the Public % and Ticket % from the Action Network signals.
    2. Monitor for 'Reverse Line Movement' (line moves opposite of the heavy public side).
    3. Send automated Telegram or Discord alerts when a sharp signal is detected.
    4. Track the historical success rate of these specific signals.
  • Expert Performance Auditor

    Verify and track the historical accuracy of sports analysts and professional handicappers on the platform.

    1. Daily scrape the 'Picks' section to log all expert recommendations.
    2. Join this data with actual game results scraped from a sports API.
    3. Calculate ROI, win percentage, and profit/loss in units for each expert.
    4. Generate a leaderboard to identify the most reliable niche experts.
  • Predictive Injury Impact Model

    Analyze how specific player injuries correlate with line movements and final game outcomes.

    1. Scrape the 'Injury Report' pages for all active teams.
    2. Categorize player impact (Star, Starter, Role Player).
    3. Correlate injury announcements with immediate shifts in the point spread.
    4. Use the historical data to build a model that predicts line moves based on injury news.
More than just prompts

Supercharge your workflow with AI Automation

Automatio combines the power of AI agents, web automation, and smart integrations to help you accomplish more in less time.

AI Agents
Web Automation
Smart Workflows

Pro Tips for Scraping Action Network

Expert advice for successfully extracting data from Action Network.

Use high-quality residential proxies. DataDome is extremely effective at identifying and blocking data center IP ranges from AWS, GCP, and DigitalOcean.

Look for the <script id="__NEXT_DATA__"> tag in the HTML source. This contains a JSON object with the page's state, providing cleaner data than parsing HTML.

Scrape during high-traffic windows (like 9 AM to 12 PM EST on Sundays) for the most accurate 'closing' line data and public splits.

Rotate your User-Agent strings and implement randomized delays between requests to mimic human browsing patterns and avoid triggering DataDome.

Focus on the 'Odds' sub-directories (/nba/odds, /nfl/odds) as these pages have a more consistent structure compared to editorial articles.

Store your data in a time-series database like InfluxDB or TimescaleDB to effectively track how lines move from open to close.

Testimonials

What Our Users Say

Join thousands of satisfied users who have transformed their workflow

Jonathan Kogan

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.

Mohammed Ibrahim

Mohammed Ibrahim

CEO, qannas.pro

I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!

Ben Bressington

Ben Bressington

CTO, AiChatSolutions

Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!

Sarah Chen

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Jonathan Kogan

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.

Mohammed Ibrahim

Mohammed Ibrahim

CEO, qannas.pro

I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!

Ben Bressington

Ben Bressington

CTO, AiChatSolutions

Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!

Sarah Chen

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

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Frequently Asked Questions About Action Network

Find answers to common questions about Action Network