SofaScore Scraper

Get live scores, fixtures, match statistics, lineups, players and odds from SofaScore as JSON or CSV, with no browser and no parsing.

SofaScore is one of the richest free sources of sports data: football, basketball, tennis, ice hockey, cricket, esports and more, with minute-by-minute incidents, advanced stats and player ratings. It has no official public API, and the site changes often, so scraping it yourself means a lot of maintenance.

This repo shows how to pull that data with the SofaScore Scraper on Apify, a hosted scraper you can run from the web UI or call from code. Every example here was run against the live site before being published.

Table of Contents

• What you can get
• Quick start
• Examples
• Input options
• Sample output
• Use cases
• FAQ

What you can get

Entity	Fields (highlights)
Matches	teams, scores (full-time, half-time, aggregate), status, start time, tournament, season, round, venue, referee, attendance, winner
Match details	statistics (possession, shots, xG, passes, ...), lineups with formations, incidents (goals, cards, substitutions), odds, fan votes, head-to-head
Teams	country, league, manager, stadium and capacity, colors, logo, recent form, squad
Players	position, jersey number, height, preferred foot, nationality, date of birth, market value, contract end, team
Tournaments	standings tables, seasons

Five ways in:

• search - look up teams, players, tournaments or matches by name ("Real Madrid", "Lionel Messi")
• url - paste any SofaScore team, player, match or tournament URL
• live - every match in progress right now, filtered by sport
• scheduled - all fixtures and results for a date (plus extra days ahead)
• incremental mode - on a schedule, only emit what changed since the last run

Quick start

No code: open the scraper page, type a team name, click Start, and download the results as JSON, CSV or Excel.

From code: get a free Apify API token, then:

git clone https://github.com/abotapi/sofascore-scraper && cd sofascore-scraper
export APIFY_TOKEN=<your token>

Examples

Python: search and save to CSV

examples/python/main.py

pip install "apify-client>=3"
python examples/python/main.py "Real Madrid" "Lionel Messi"

Saved 20 rows to sofascore.csv
- [team] Riverside FC (football, Exampleland)
- [player] Luca Brandt (football, Exampleland)
- [player] Sam Keller (football, Exampleland)

Node.js: live scores across sports

examples/node/index.mjs

cd examples/node && npm install && node index.mjs

football | Northgate United 1 - 1 Lakeside Rovers | 2nd half
basketball | Harbor City Hawks 58 - 61 Riverside Rays | 3rd quarter
tennis | A. Moreno 1 - 0 N. Lind | 2nd set

cURL: today's fixtures in one HTTP call

examples/curl.sh uses the run-sync-get-dataset-items endpoint, which starts the run, waits, and returns the items:

./examples/curl.sh > matches.json

Input options

Option	What it does
mode	search, url, live or scheduled
searchQueries / searchType	Names to look up; optionally restrict to team, player, tournament or match
urls	SofaScore page URLs to scrape directly
sports	Sports to include in live/scheduled mode, e.g. football, basketball, tennis
date / daysAhead	Which day's fixtures to fetch in scheduled mode, and how many extra days
includeStatistics, includeLineups, includeIncidents, includeOdds, includeVotes, includeH2H, includeStandings, includeSquad	Toggle the detail blocks you need; fewer blocks means faster runs
maxItems	Stop after this many results
incrementalMode	For scheduled runs: only output new or changed items

See the scraper page for the full list.

Sample output

Mock data with the same fields and types as real output (the values are made up): sample-output/sample.json · sample-output/sample.csv

{
  "type": "match",
  "sport": "football",
  "name": "Riverside FC - Harbor City",
  "homeTeam": "Riverside FC",
  "awayTeam": "Harbor City",
  "homeScore": 2,
  "awayScore": 1,
  "homeScoreHalftime": 1,
  "statusDescription": "Ended",
  "tournament": "Example Premier League",
  "venue": "Riverside Arena",
  "statistics": [{ "period": "ALL", "groups": [{ "groupName": "Match overview", "statisticsItems": [{ "name": "Ball possession", "home": "58%", "away": "42%" }] }] }],
  "url": "https://www.sofascore.com/..."
}

Use cases

• Sports analytics and betting models: historical results, xG and odds for backtesting
• Live score widgets and bots: poll live mode for a Discord, Telegram or Slack bot
• Fantasy sports: player form, ratings, lineups and injuries before the deadline
• Media and newsrooms: automated match reports from incidents and statistics
• AI agents: feed structured match data to an LLM instead of scraping HTML

FAQ

How much does it cost? You pay per result on Apify, and new accounts get free monthly credit that covers small projects. See the scraper page for current pricing.

Is scraping SofaScore allowed? The scraper only collects publicly visible data. Check SofaScore's terms and your local laws for your use case, especially for commercial redistribution.

Can I run it on a schedule? Yes. Create a schedule in Apify (e.g. every 5 minutes for live scores) and turn on incrementalMode to receive only changes.

Can I get the data somewhere other than JSON? Download CSV, Excel, XML or HTML from the run, or push it to Google Sheets, webhooks, Zapier, Make or n8n through Apify integrations.

Related

• Awesome Web Scrapers: a curated list of 360+ ready-to-run scrapers
• Sportsbook Odds Scraper: odds from 1xBet, Melbet and more

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_{The scraper is maintained by abotapi. Examples in this repo are MIT licensed. Not affiliated with SofaScore.}