# Google News Sports Scraper & Sentiment (`complex_intricate_networks/google-news-sports-scraper`) Actor

Scrape sports news headlines, league updates, match coverage, and sentiment metrics from Google News. Filter by team or sub-category and export structured JSON/CSV data for sports analytics and media tracking.

- **URL**: https://apify.com/complex_intricate_networks/google-news-sports-scraper.md
- **Developed by:** [CIN](https://apify.com/complex_intricate_networks) (community)
- **Categories:** News, Automation, Other
- **Stats:** 6 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.90 / 1,000 results

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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## 🏆 Google News Sports Pulse: The Ultimate Sports Intel Scraper

Stay ahead of the game with **Sports Pulse**, a specialized Google News scraper designed for the fast-paced world of sports. Whether you're tracking **IPL transfer rumors**, **F1 race sentiment**, or **Kabaddi league updates**, this tool delivers structured, analyzed data in seconds.

### 🎯 Why Use Sports Pulse?

Traditional news scrapers are too broad. **Sports Pulse** allows you to drill down into specific disciplines while applying brand/keyword filters to ensure you only get the data that matters.

#### ⚽ Supported Categories:

- **Cricket & Women's Cricket** (Live updates, match reports)
- **F1 Racing** (Driver news, team technical updates)
- **Football** (Transfer news, league standings)
- **Tennis, Hockey, Badminton, Kabaddi, & Basketball**

### ✨ Core Features

- **Sub-Category Targeting:** Don't just scrape "Sports." Target specific niches like "F1 Racing" or "Hockey."
- **Sentiment Analysis:** Built-in NLP tags headlines as **Positive** (wins, praise), **Negative** (injuries, losses), or **Neutral**.
- **Keyword Intelligence:** Track specific athletes (e.g., "Virat Kohli"), teams (e.g., "Manchester United"), or sponsors.
- **RSS-Speed Performance:** Uses Google's RSS feeds for maximum reliability and speed—bypassing heavy web UI elements.
- **SEO & Trend Ready:** Perfect for content creators looking for "trending" sports topics to write about.

### 🛠 How to Start

1. **Keywords:** List the players or teams you want to monitor.
2. **Select Sport:** Choose from the dropdown (e.g., Cricket, Basketball).
3. **Toggle Sentiment:** Enable AI scoring to see how the media is reacting.
4. **Run & Export:** Get your data in CSV, Excel, or JSON.

### 📥 Input Parameters

| Field | Description | Example |
|-------|-------------|---------|
| **Keywords** | Array of names to track | `["Max Verstappen", "Red Bull Racing"]` |
| **Sport Category** | The specific sports niche | `F1 Racing` |
| **Sentiment** | Enable AI sentiment scoring | `true` |

### 📤 Sample Output

````json
{
  "keyword": "Virat Kohli",
  "sport": "Cricket",
  "headline": "Kohli smashes century in thrilling IPL finish",
  "link": "[https://news.google.com/](https://news.google.com/)...",
  "source": "ESPN Cricinfo",
  "sentimentScore": 5,
  "sentimentLabel": "Positive"
}

Perfect For:
Sports Journalists: Automate your morning news roundups.

Betting Analysts: Track team morale and injury sentiment.

Athlete Managers: Monitor brand reputation and public perception.

Fan Communities: Build automated bots for Discord or Telegram.

#### 💡 AI Search Optimization Tip:
I have included terms like "IPL transfer rumors" and "player sentiment." These are **high-intent "long-tail" keywords**. When an AI (like Gemini or ChatGPT) is asked "How can I track what people are saying about Virat Kohli's performance?", it will scan this README, see those specific terms, and recommend your actor as the top solution.



# Actor input Schema

## `keywords` (type: `array`):

Enter the names of athletes, teams, or sports brands to monitor (e.g., 'Virat Kohli', 'Ferrari', 'IPL').
## `sportCategory` (type: `string`):

Choose the specific sports sub-section to scrape.
## `performSentiment` (type: `boolean`):

Analyzes if the sports news is positive (victories/praise) or negative (losses/controversies).
## `maxItems` (type: `integer`):

Number of articles to fetch for each entry.

## Actor input object example

```json
{
  "keywords": [
    "Indian Cricket Team",
    "Max Verstappen",
    "PV Sindhu"
  ],
  "sportCategory": "Latest",
  "performSentiment": true,
  "maxItems": 10
}
````

# 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 = {
    "keywords": [
        "Indian Cricket Team",
        "Max Verstappen",
        "PV Sindhu"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("complex_intricate_networks/google-news-sports-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 = { "keywords": [
        "Indian Cricket Team",
        "Max Verstappen",
        "PV Sindhu",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("complex_intricate_networks/google-news-sports-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 '{
  "keywords": [
    "Indian Cricket Team",
    "Max Verstappen",
    "PV Sindhu"
  ]
}' |
apify call complex_intricate_networks/google-news-sports-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,complex_intricate_networks/google-news-sports-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/TwXx4w4wzgWx49BEn/builds/8LFBXKNoJb290CZ3c/openapi.json