# Youtube Most Replayed Scraper (`scrapelabsapi/youtube-most-replayed-scraper`) Actor Scrape YouTube Most Replayed moments instantly with this YouTube Most Replayed Scraper ▶️ Extract peak replay timestamps, engagement patterns, video insights, and audience behavior data with ease 📊 Perfect for content analysis, trend spotting, and video optimization 🔍🚀 - **URL**: https://apify.com/scrapelabsapi/youtube-most-replayed-scraper.md - **Developed by:** [ScrapeLabs](https://apify.com/scrapelabsapi) (community) - **Categories:** Videos, Developer tools, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $19.99/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 ### What does YouTube Most Replayed Scraper do? The YouTube Most Replayed Scraper is a smart tool that lets you extract data from YouTube’s Most Replayed feature—the heatmap above the progress bar showing the most watched or rewatched parts of a video. Instead of guessing what viewers love, you get structured insights into the exact moments that spark engagement. Unlike the general Apify YouTube Scraper, which pulls full video and channel data, this scraper focuses on replay intensity and heatmap analytics. Developers sometimes turn to the YouTube Most Replayed API or even GitHub scrapers as alternatives, but this tool is faster and more user-friendly. Versions exist for iOS, download-ready builds, and other integrations, making it versatile for creators, marketers, or researchers. ### What YouTube Most Replayed Scraper can I extract? When you use the YouTube Most Replayed Scraper, you’re not just pulling random numbers—you’re creating a structured YouTube dataset that captures both video metadata and audience behavior. This makes it perfect for creators, marketers, or researchers who want to go beyond surface-level stats and understand how to scrape YouTube videos for deeper insights. Here’s a breakdown of the core fields you can extract: | Data Type | Details Extracted | | --- | --- | | Video ID | Unique identifier of the video | | Channel Name/Owner | Who published the video | | Title | Full video title | | Views | Total view count | | Likes | Number of likes (if available) | | Comments | Comment count | | Upload Date | Exact and relative date | | Replay Segments | Start/end times of most replayed parts | | Heatmap Data | Intensity score for replay frequency | | Engagement Metrics | Most rewatched sections vs. less engaged parts | This structured approach allows you to filter, compare, and analyze data across multiple videos—whether you’re studying the YouTube record for most views, analyzing YouTube rewinds ranked, or finding the highlights in trending videos. #### Key Features of YouTube Most Replayed Scraper * ⚡ Fast & efficient – optimized for large datasets and bulk video processing. * 📊 Replay heatmap extraction – captures normalized intensity scores for every segment. * 📂 Export options – JSON, CSV, Excel, and API-ready outputs. * 🔗 API integration – works with the YouTube Most Replayed API and automation workflows. * 📈 Bulk video support – process multiple URLs in one run. Compared to the Apify YouTube Scraper, which captures broad video/channel details, this scraper zooms in on audience behavior—giving you clarity on what viewers actually replay the most. ### How to use YouTube Most Replayed Scraper Using the YouTube Most Replayed Scraper is simple—you don’t need to be highly technical to get started. Just follow a few straightforward steps and you’ll have structured replay heatmap data in minutes. #### Step-by-Step Guide 1. Log in to Apify – Create a free account or sign in. 2. Select the Actor – Search for “YouTube Most Replayed Scraper” in the Apify store. 3. Enter Input Data – Paste your YouTube video URL(s) into the input field. You can add one or multiple links. 4. Choose Options – Decide if you want extra metadata like views, likes, or comments. 5. Run the Actor – Hit Start and let the scraper extract replay heatmap segments automatically. 6. Download Results – Export your dataset in JSON, CSV, Excel, or API-ready formats. #### ⬇️ Input Example ```json { "maxRetries": 3, "requestTimeoutSecs": 20, "urls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ] } ```` #### ⬆️ Output Example ```json [ { "videoId": "dQw4w9WgXcQ", "title": "Rick Astley - Never Gonna Give You Up (Official Video) (4K Remaster)", "channelOwner": "Rick Astley", "viewCount": "1694624700", "likes": "18549049", "comments": "2.4M", "dateText": "Oct 24, 2009", "relativeDate": "15 years ago" } ] ``` For automation, you can connect the scraper with the YouTube Most Replayed API, Zapier, or Google Sheets. Some creators also use YouTube Most Replayed Scraper iOS apps or download-ready builds for on-the-go analysis. This flexibility makes it a must-have tool for content optimization and trend tracking. ### 🎯 Why scrape YouTube Most Replayed Scraper? #### 1. Content Creators – Find the Highlights Creators can instantly identify the most replayed segments and repurpose them into Shorts, reels, or teasers. This saves guesswork and helps grow engagement. #### 2. Marketers – Competitor Analysis By scraping replay heatmaps, marketers see what hooks work in competitor videos. This insight fuels better campaign strategies and messaging. #### 3. Researchers – Audience Engagement Insights Replay spikes highlight emotional or controversial moments. Researchers can use this structured data to study viewer psychology and behavior trends. #### 4. Trend Analysis – Viral Patterns The scraper makes it easier to track the most replayed YouTube video, compare with YouTube record views in a day, or analyze YouTube rewinds ranked for cultural trends. #### 5. Editors – Save Time Editors skip full replays and jump straight into replayed timestamps. This means faster highlight reels and more efficient editing workflows. ### How many results can you scrape with YouTube Most Replayed Scraper? The number of results you can scrape with the YouTube Most Replayed Scraper depends largely on the video itself. Each video is broken into replay segments and heatmap points, so the output scales with video length and viewer activity. A short clip may return a handful of replay timestamps, while a long-form video could generate hundreds of data points. Typical limits: - Standard videos: 50–200 replay segments - Long-form content (30+ minutes): 300+ data points - Shorts or low-view videos: very few or no replay heatmaps Key factors that affect results: - 📏 Video length – longer videos generate more replay intervals. - 👀 Popularity – videos with higher views unlock richer heatmap data. - 🔥 Heatmap availability – YouTube only shows the “Most Replayed” graph if the video has enough engagement. - 🖥️ Proxies – using residential proxies helps ensure consistent scraping without blocks. For bulk scraping, you can queue multiple video URLs in a single run. This makes it easier to build structured datasets across multiple channels or categories. While each video has its natural replay data limit, scaling across playlists or trending videos provides powerful insights into viewer habits and viral trends. ### How much will scraping YouTube Most Replayed Scraper cost you? The YouTube Most Replayed Scraper is one of the most affordable ways to extract replay heatmap data. You can get started for as little as $5 per month, which is more than enough for small to mid-scale projects. Here’s how pricing usually works: - Base Plan – $5/month for light users who only need to analyze a manageable number of videos. - Scaling Up – If you’re scraping hundreds or thousands of videos, you may need higher Apify credits depending on workload. - Pay-as-you-go Flexibility – Costs scale with the resources you consume, so you only pay for what you scrape. This model makes it budget-friendly for creators, marketers, and researchers who want accurate replay insights without investing in expensive enterprise software. Whether you’re tracking a single highlight or analyzing the most replayed YouTube video across multiple channels, the $5/month plan gives you structured, export-ready data at a price almost anyone can afford. ### Is it legal to scrape YouTube Most Replayed Scraper? #### 🔹 YouTube Terms of Service YouTube’s Terms discourage automated scraping, but the Most Replayed feature is public data. Scraping it for research or analysis is less risky than trying to access private or hidden information. #### 🔹 Ethical Scraping Practices Always stick to publicly available data—such as replay heatmaps, timestamps, views, and metadata. Avoid scraping personal user data, hidden emails, or restricted content. #### 🔹 GDPR and Data Privacy Replay metrics and heatmaps are non-personal data, so they typically don’t raise GDPR concerns. Problems arise only if you attempt to scrape identifiable user data, like detailed comments tied to accounts. #### 🔹 Best Practice Summary - ✅ Safe: Replay timestamps, heatmap intensity, video stats - ❌ Risky: Private emails, hidden account info, personal identifiers - ⚖️ Rule: Treat scraping as analytics, not data harvesting ### What are other YouTube Most Replayed Scraper tools? If you want to scrape specific YouTube data, you can use any of these dedicated scrapers with fewer settings to change and faster results. Just enter one or more YouTube URLs and click to scrape. | Apify YouTube Scraper | YouTube Most Replayed API | | --- | --- | | YouTube Scraping GitHub Repos | YouTube Channel Finder | | AI YouTube Scrapers | YouTube Comments Scraper | | YouTube Shorts Scraper | YouTube Video Scraper by Hashtag | # Actor input Schema ## `urls` (type: `array`): 📝 Paste one or more YouTube watch URLs. One per line. At least one URL is required. ## `proxy` (type: `object`): ⚡ Proxy is off by default. If the site blocks the request, the actor turns on Apify Residential proxy and stays on it. Configure here to customize. ## Actor input object example ```json { "urls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "proxy": {} } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("scrapelabsapi/youtube-most-replayed-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("scrapelabsapi/youtube-most-replayed-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).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 scrapelabsapi/youtube-most-replayed-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapelabsapi/youtube-most-replayed-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Youtube Most Replayed Scraper", "description": "Scrape YouTube Most Replayed moments instantly with this YouTube Most Replayed Scraper ▶️ Extract peak replay timestamps, engagement patterns, video insights, and audience behavior data with ease 📊 Perfect for content analysis, trend spotting, and video optimization 🔍🚀", "version": "1.0", "x-build-id": "kDukwWBNeHWOcAGAb" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapelabsapi~youtube-most-replayed-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapelabsapi-youtube-most-replayed-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapelabsapi~youtube-most-replayed-scraper/runs": { "post": { "operationId": "runs-sync-scrapelabsapi-youtube-most-replayed-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapelabsapi~youtube-most-replayed-scraper/run-sync": { "post": { "operationId": "run-sync-scrapelabsapi-youtube-most-replayed-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "urls" ], "properties": { "urls": { "title": "🔗 YouTube video URLs", "type": "array", "description": "📝 Paste one or more YouTube watch URLs. One per line. At least one URL is required.", "default": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "items": { "type": "string" } }, "proxy": { "title": "🛡️ Proxy (optional)", "type": "object", "description": "⚡ Proxy is off by default. If the site blocks the request, the actor turns on Apify Residential proxy and stays on it. Configure here to customize.", "default": {} } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```