Metacritic Scraper — Game, Movie, TV & Music Reviews and Scores

Extract Metascores, user scores, critic and user reviews, and full title metadata from Metacritic.com — the web's most-cited review aggregator for games, movies, TV shows, and music albums.

Two modes: search Metacritic's catalog by title, or pull full details from any specific Metacritic URL. Pay-per-result pricing. Output ships as JSON, CSV, or Excel.

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Why Scrape Metacritic?

Metacritic is the canonical aggregator for entertainment reviews — every major game studio, film distributor, and TV network watches Metascores closely because they correlate with sales, awards, and audience adoption. But Metacritic offers no public API, and the site's pages don't surface their underlying structured data in a machine-friendly way.

The pain points:

• No public API — researchers, journalists, and fans have to scrape or click manually
• Critic reviews and user reviews live on different pages, with different score scales (0–100 for critics, 0–10 for users)
• Comparing scores across many titles requires structured data, not screenshots
• Game release lists span dozens of platforms — manually consolidating them is slow
• Metascores update over time as more critics review a title, so a one-off snapshot misses the picture

This actor handles all of it. Submit a search query (across all categories or filtered to games/movies/TV/music) or a specific Metacritic URL, and it returns clean structured records.

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What You Get

Search mode

Returns a list of titles matching your query, each with:

• Title — the official Metacritic title
• Metascore — aggregate critic score (0–100)
• User score — aggregate user score (0–10)
• Release date — when the title was released
• Category — game, movie, tv, or music
• Platform (games) — PC, PS5, Xbox Series X, Switch, etc.
• Genre — primary genre tags
• URL — the Metacritic detail page URL
• Image — cover/poster URL
• Critic count — how many critic reviews are tallied
• User count — how many user reviews are tallied
• Description — short summary

Detail mode

For a specific Metacritic URL (any title page), returns everything the search mode returns plus:

• Full critic reviews — list of { critic, publication, score, quote, date, url } objects
• Full user reviews — list of { username, score, body, date } objects
• Cast and crew (movies, TV) — directors, lead actors, showrunners
• Developer / publisher (games) — studio and publishing label
• Network (TV) — original broadcast network
• Artist (music) — recording artist and label
• All platforms (games) — every platform the title is released on
• Content rating — ESRB, MPAA, or equivalent
• Score distribution — how reviews break down across positive / mixed / negative

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Use Cases

1. Entertainment industry research

Studios, publishers, and analysts track Metascores as a leading indicator of commercial performance. Pull a quarter's worth of game releases by platform and compute average Metascore against sales data — the correlation is strong enough to inform marketing spend allocation.

2. "Best of" lists and comparison content

Run an entertainment site? Schedule a weekly run on the latest releases by category, sort by Metascore, and update your "Best Games of 2026" or "Top New Movies This Month" article automatically. Ranking by an authoritative third-party score is more credible than your own opinions.

3. Personal recommendation engines

Build a recommendation app that filters by Metascore + user score gap (titles critics love but users hate, or vice versa), genre, and platform availability. Useful for differentiating from generic recommendation engines.

4. Awards-prediction modeling

Game-of-the-Year contenders correlate strongly with their Metascore. Pull the year's top-30 games by Metascore and use that as a candidate pool for awards-prediction or press coverage.

5. Streaming and library curation

Streaming services and game subscription services (PS Plus, Game Pass) curate their libraries based partly on Metascore. Pull the catalogue of a service, cross-reference Metascores, and visualize the average quality of what's available — useful for content strategy.

6. Academic media research

Researchers studying critical reception, audience-vs-critic divergence, or shifts in genre quality over time need structured Metascore data. This actor produces citation-ready datasets without manual extraction.

7. Publisher and studio competitive intelligence

A studio's Metascore trajectory across its last 5 releases is a public quality signal. Track competitor studios over time and identify quality regressions or surges that often precede strategic moves.

8. Fan-site automation

Run a fan site for a game, movie, or TV show? Schedule a daily run to detect new reviews, score changes, or fresh critic quotes. Update your homepage automatically — readers love seeing live data.

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Modes

The actor supports two modes:

Mode	What it does	Required inputs
search	Search Metacritic by query, optionally filtered by category	query, category, maxItems
detail	Fetch full title details from a specific Metacritic URL	url

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Input Parameters

Parameter	Type	Required	Default	Description
action	string	Yes	search	One of search or detail
query	string	Conditional	halo	Search query (used in search mode)
url	string	Conditional	—	Metacritic title URL (used in detail mode)
category	string	No	all	Filter by category — all, games, movies, tv, or music
maxItems	integer	No	20	Max results in search mode (1–100)

Example — search games

{
  "action": "search",
  "query": "halo",
  "category": "games",
  "maxItems": 25
}

Example — search movies

{
  "action": "search",
  "query": "dune",
  "category": "movies",
  "maxItems": 10
}

Example — search across all categories

{
  "action": "search",
  "query": "the matrix",
  "category": "all",
  "maxItems": 30
}

Example — get full detail from a URL

{
  "action": "detail",
  "url": "https://www.metacritic.com/game/the-last-of-us/"
}

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Output Examples

Search-mode result

{
  "title": "The Last of Us Part II",
  "metascore": 93,
  "userScore": 5.7,
  "category": "game",
  "releaseDate": "2020-06-19",
  "platform": "PlayStation 4",
  "genre": ["Action", "Adventure"],
  "url": "https://www.metacritic.com/game/playstation-4/the-last-of-us-part-ii",
  "image": "https://www.metacritic.com/static-media/example.jpg",
  "criticCount": 121,
  "userCount": 198432,
  "description": "Five years after their dangerous journey across the post-pandemic United States..."
}

Detail-mode result

{
  "title": "The Last of Us",
  "metascore": 95,
  "userScore": 9.2,
  "category": "game",
  "releaseDate": "2013-06-14",
  "developer": "Naughty Dog",
  "publisher": "Sony Computer Entertainment",
  "platforms": ["PlayStation 3", "PlayStation 4", "PC"],
  "rating": "M (Mature)",
  "criticReviews": [
    {
      "critic": "Game Informer",
      "publication": "Game Informer",
      "score": 100,
      "quote": "A virtuoso piece of storytelling and a triumph of emotional craft.",
      "date": "2013-06-05",
      "url": "https://www.gameinformer.com/example-review"
    }
  ],
  "userReviews": [
    {
      "username": "exampleuser",
      "score": 10,
      "body": "An absolute masterpiece. The voice acting alone is worth the price of admission.",
      "date": "2014-01-12"
    }
  ],
  "scoreDistribution": {
    "positive": 98,
    "mixed": 2,
    "negative": 0
  }
}

Datasets can be exported as JSON, CSV, XML, or Excel from the Apify console, or fetched programmatically via the dataset API.

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Calling the Actor Programmatically

Python — apify-client

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

# Search across games
run = client.actor("cryptosignals/metacritic-scraper").call(run_input={
    "action": "search",
    "query": "elden ring",
    "category": "games",
    "maxItems": 10,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['title']} ({item.get('platform','?')}) — Metascore: {item['metascore']}")

Python — pull full reviews from a URL

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("cryptosignals/metacritic-scraper").call(run_input={
    "action": "detail",
    "url": "https://www.metacritic.com/movie/dune-part-two",
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['title']} — Metascore {item['metascore']}, User {item['userScore']}")
    for r in item.get("criticReviews", [])[:5]:
        print(f"  [{r['score']}] {r['critic']}: {r['quote'][:100]}...")

Python — bulk score tracking

from apify_client import ApifyClient
import pandas as pd

client = ApifyClient("YOUR_APIFY_TOKEN")

queries = ["elden ring", "baldurs gate 3", "starfield", "alan wake 2", "spider-man 2"]
all_results = []

for q in queries:
    run = client.actor("cryptosignals/metacritic-scraper").call(run_input={
        "action": "search",
        "query": q,
        "category": "games",
        "maxItems": 5,
    })
    all_results.extend(client.dataset(run["defaultDatasetId"]).list_items().items)

df = pd.DataFrame(all_results)[["title", "metascore", "userScore", "platform"]]
print(df.sort_values("metascore", ascending=False))

Node.js — apify-client

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('cryptosignals/metacritic-scraper').call({
    action: 'search',
    query: 'oppenheimer',
    category: 'movies',
    maxItems: 5,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(t => console.log(`${t.title} — ${t.metascore} (${t.userScore})`));

cURL — direct API call

curl -X POST \
  "https://api.apify.com/v2/acts/cryptosignals~metacritic-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "action": "search",
    "query": "the matrix",
    "category": "movies",
    "maxItems": 10
  }'

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Pricing

This actor uses Pay-per-event pricing — you only pay for results you actually receive. No charges for failed runs or compute time.

• Cost: per-result pricing as listed on the actor's pricing page
• Free tier: Apify's free plan includes $5/month of platform credits — enough to scrape thousands of titles
• Cost examples:

Use case	Items	Approximate cost
One-off lookup	10 titles	< $0.10
Weekly trending check	50/week	~$0.50/week
Reviews monitoring	200 detail pages/month	~$5/month
Research dataset	5,000 titles	~$50

See Apify pricing →

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FAQ

Is scraping Metacritic legal?

Scraping publicly visible data — pages anyone can view without logging in — is generally considered lawful in many jurisdictions. The U.S. Ninth Circuit's hiQ v. LinkedIn (2022) decision held that scraping publicly accessible data does not violate the Computer Fraud and Abuse Act. This actor only collects data from Metacritic's publicly visible review pages. Always consult your own legal counsel for your specific use case.

Do I need a Metacritic account or API key?

No. Metacritic doesn't offer a public API, and the actor doesn't use one. It works with the publicly visible web pages — no login required.

What's the difference between Metascore and user score?

• Metascore (0–100) is Metacritic's aggregate score based on professional critic reviews. It uses a weighted average that gives more weight to higher-credibility publications.
• User score (0–10) is the average score from registered Metacritic users. It can diverge significantly from the Metascore — sometimes critics love a title that audiences pan (or vice versa).

Both are returned by the actor for every title.

How fast is it?

Search mode typically completes in 5–20 seconds. Detail mode (which pulls all reviews) takes 10–30 seconds per URL. Multiple runs can execute in parallel using Apify's concurrent-run feature.

Can I get score change history?

The actor returns the current score at scrape time. To track changes over time, schedule recurring runs and store the results in your own database — Apify makes this trivial via webhook integrations.

What about platform-specific scores for games?

For games, the actor returns the platform-specific Metascore from the URL or search result. For example, "The Last of Us Part II" on PS4 has its own Metascore separate from any future remaster on PS5.

Can I schedule recurring scrapes?

Yes. Apify's built-in scheduler runs any cron expression — hourly, daily, weekly. Pipe results to a webhook, Google Sheets, Airtable, Slack, or your own database. Combine with Apify's Zapier and Make integrations for downstream automation.

What output formats are supported?

JSON, CSV, Excel, and XML are all supported in the Apify console. You can also fetch results programmatically via the dataset API.

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Why This Actor vs Alternatives?

• No login or API key. Metacritic doesn't offer a public API. This actor is the practical alternative.
• Both modes in one actor. Search and detail are unified — one input schema, one billing line.
• Pay-per-result. You only pay for items you actually receive. Failed runs cost zero.
• Apify-native integrations. Pipe results into Zapier, Make, Google Sheets, Airtable, Slack, or any of Apify's 50+ integrations.
• Maintained. The actor is updated when Metacritic evolves its layout.

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Related Actors From Web Data Labs

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• Rotten Tomatoes Scraper — Reviews and Tomatometer scores from Rotten Tomatoes
• Steam Scraper — Game data, reviews, and pricing from Steam
• YouTube Channel Scraper — Channel statistics and recent uploads

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About Web Data Labs

This actor is built and maintained by Web Data Labs — a team focused on production-grade web data extraction across jobs, e-commerce, social media, software reviews, and entertainment data. We publish 100+ public actors on the Apify platform, all pay-per-result.

Need a custom build, enterprise SLA, or private actor for your team? Reach out via web-data-labs.com or the Apify contact form.