Sports Data Scraper — Live Scores, Stats & Schedules 🚀

⚽ Extract live sports data from 30+ sports — football, basketball, tennis, F1, MMA, esports. 15 operations, one clean dataset per run.

Perfect for sports analysts, fantasy sports developers, betting researchers, and data scientists who need structured sports data at scale.

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🔎 What is the Sports Data Scraper — and when should you use it?

The Sports Data Scraper turns tournaments, teams, players and matches across 30+ sports into clean, structured rows you can filter, export and feed straight into a spreadsheet, database or AI agent. No account, no portal API key, no browser automation to maintain.

Use it when you need: fixtures and results with scores, league tables with home-only and away-only splits, squads, transfers, and team and player profiles. For a single match you get lineups with formations, a minute-by-minute goal and card timeline, per-statistic breakdowns and pre-match odds by market. Live scores cover what is in play right now in football, basketball, tennis, ice hockey, MMA and motorsport.

Use something else when: you want one sport covered in depth. Use Football API Scraper for 18 football-only operations, with expected goals, squad market values and contract-end dates. Use Basketball API Scraper for basketball box scores with points, rebounds, assists and plus-minus, plus conference standings. Use Tennis Point-by-Point Scraper for every point of a tennis match in play order, plus the match and set statistics. Use Sports Betting Odds Scraper for moneyline, spread and totals lines from 8+ bookmakers side by side. Live scores here run on football, basketball, tennis, ice hockey, MMA and motorsport. Other sports still work for tournament search, fixtures, tables and match detail.

🤖 Use with AI agents

Already connected to the Apify MCP server? Just ask for this Actor by name: sian.agency/sports-data-scraper

Your agent can pay for its own runs. This Actor is eligible for agentic payments, so an agent can discover it, run it and settle the bill over x402 (USDC on Base) or Skyfire — without an Apify account or API token of its own. Billing is the same either way: per successful row, never for errors.

Otherwise copy this prompt into Claude, ChatGPT, Cursor or any MCP-enabled assistant:

I want structured data across 30+ sports using the Apify Actor `sian.agency/sports-data-scraper`.

Use it when I need: fixtures and results with scores, league tables with home-only and away-only splits, squads, transfers, and team and player profiles. For a single match you get lineups with formations, a minute-by-minute goal and card timeline, per-statistic breakdowns and pre-match odds by market. Live scores cover what is in play right now in football, basketball, tennis, ice hockey, MMA and motorsport.

Don't use it when: you want one sport covered in depth — use football-api-scraper or basketball-api-scraper or tennis-point-by-point-scraper or sports-betting-odds-scraper instead.

How to call it: set `operation` to one of
  searchTournaments -> needs `query` (a competition name), returns Tournament IDs
  tournamentSeasons -> needs `tournamentId`, returns Season IDs
  seasonEvents      -> needs `tournamentId` + `seasonId`, paginated with `page` and `maxPages`
  standings         -> needs `tournamentId` + `seasonId` (+ `standingsType`: "total", "home" or "away")
  teamDetails       -> needs `teamId`
  teamSquad         -> needs `teamId`
  teamTransfers     -> needs `teamId`
  teamEvents        -> needs `teamId`, paginated
  playerDetails     -> needs `playerId`
  matchDetails / matchIncidents / matchLineups / matchStatistics / matchOdds
                    -> each needs `eventId`, taken from any seasonEvents, teamEvents or liveScores row
  liveScores        -> needs `sport`: "football", "basketball", "tennis", "ice-hockey", "mma" or "motorsport".

Start with this input:
{
  "operation": "searchTournaments",
  "query": "Premier League"
}

Ask me which sport and competition I care about, and whether I want fixtures, a league table, or one match in detail, then run the Actor and summarise the results as a table.

Things you can ask your agent for:

• Find the Serie A tournament ID, pull this season's fixtures, and list every match that ended in a draw.
• Take this match ID and give me the lineups, the goal and card timeline, and the full match statistics.
• Show me which basketball games are in play right now and what the scores are.

Machine-readable API, MCP config and OpenAPI definition for this Actor are published at apify.com/sian.agency/sports-data-scraper.md.

📋 Overview

Sports Data Scraper is your all-in-one sports data pipeline. No API key management, no complex integrations — pick an operation, provide IDs, and get clean structured data instantly. Covers football (soccer), basketball, tennis, Formula 1, MMA, esports, and 25+ more sports.

Why professionals choose us:

• ✅ 30+ Sports Covered: Football, basketball, tennis, F1, MMA, esports, cricket, rugby, and more
• ⚡ 15 Operations: Tournaments, seasons, fixtures, league tables, squads, transfers, player and team profiles, plus match detail, lineups, incidents, statistics, odds and live scores
• 🎯 Clean Structured Data: Every row comes with curated camelCase fields + raw upstream data
• 💰 Pay-Per-Result: Only charged for successful extractions — errors are free
• 💎 No API Key Needed: We handle the upstream — just configure and run
• 🔄 Pagination Built-In: Automatically fetches multiple pages for events and match history

✨ Features

• 🔍 Tournament Search: Find any tournament across 30+ sports by keyword
• 📅 Season Discovery: Browse all seasons within a tournament
• ⚽ Match Events: Extract full match schedules with scores, teams, and status
• 🏅 Team Profiles: Get detailed team info — name, country, sport, logos
• 🏟️ Team Match History: Paginated match history for any team
• 👤 Player Profiles: Extract player details — name, position, nationality, team
• 📄 Smart Pagination: Automatically fetch multiple pages with configurable limits
• 🔁 Auto-Retry: Exponential backoff on transient errors (429, 502, 503, 504)
• 📊 HTML Reports: Every run generates a visual summary report
• 📥 Multiple Exports: JSON, CSV, Excel — export directly from Apify dataset

🎬 Quick Start

Extract sports data in three simple steps. No configuration needed.

# Search for tournaments
curl -X POST https://api.apify.com/v2/acts/sian.agency~sports-data-scraper/runs?token=[YOUR_TOKEN] \
-d '{"operation":"searchTournaments","query":"Premier League"}'

🚀 Getting Started (3 Simple Steps)

Step 1: Choose Your Operation

Select from 15 operations. Start with searchTournaments if you have no IDs yet — every other operation takes an ID that an earlier call returns.

Step 2: Provide IDs or Keywords

Use tournament names for search, or IDs (from previous runs) for detailed lookups. IDs chain naturally: search → seasons → events → teams → players.

Step 3: Run and Download

Get clean structured data in seconds. Export as JSON, CSV, or Excel directly from the Apify dataset.

That's it! In under 10 seconds, you'll have:

• Tournament listings with sport and category data
• Season histories with year and name
• Match events with scores, teams, timestamps, and round info
• Team profiles with country, short name, and logos
• Player profiles with position, nationality, and team affiliation

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📥 Input Configuration

Field	Type	Required	Description
operation	string	Yes	Data extraction operation to run
query	string	For searchTournaments	Search keyword for finding tournaments
tournamentId	integer	For tournamentSeasons, seasonEvents	Tournament ID from search results
seasonId	integer	For seasonEvents	Season ID from tournamentSeasons results
teamId	integer	For teamDetails, teamEvents	Team ID from seasonEvents results
playerId	integer	For playerDetails	Player ID from teamDetails results
eventId	integer	For all match* operations	Match ID from seasonEvents, teamEvents or liveScores
standingsType	string	No	Which league table for standings: total, home or away (default: total)
sport	string	No	Which sport liveScores returns (default: football)
page	integer	No	Starting page for paginated ops (default: 0)
maxPages	integer	No	Max pages to fetch for paginated ops (default: 5, max: 50)

Operations:

Operation	Description	Required Input
searchTournaments	Search tournaments by keyword	query
tournamentSeasons	List seasons for a tournament	tournamentId
seasonEvents	Match events for a tournament season (paginated)	tournamentId, seasonId
teamDetails	Team profile	teamId
teamEvents	Team match history (paginated)	teamId
playerDetails	Player profile	playerId
standings	League table, total/home/away	tournamentId, seasonId
teamSquad	Squad list for a team	teamId
teamTransfers	Transfers in and out	teamId
matchDetails	One match, full detail	eventId
matchLineups	Confirmed lineups and formations	eventId
matchIncidents	Goals, cards and substitutions minute by minute	eventId
matchStatistics	Match statistics, split by half	eventId
matchOdds	Pre-match odds	eventId
liveScores	Every match in play right now	nothing

Example — Search Tournaments:

{
  "operation": "searchTournaments",
  "query": "Premier League"
}

Example — Season Events (paginated):

{
  "operation": "seasonEvents",
  "tournamentId": 17,
  "seasonId": 52186,
  "maxPages": 3
}

Example — Player Details:

{
  "operation": "playerDetails",
  "playerId": 336579
}

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📤 Output

Results are saved to the Apify dataset with 20+ fields per row including:

Field	Type	Description
tournamentId	integer	Unique tournament identifier
tournamentName	string	Tournament/competition name
seasonId	integer	Season identifier
seasonName	string	Season name (e.g. "2024/2025")
eventId	integer	Match/event identifier
eventName	string	Match/event name
startTime	integer	Match start time (Unix timestamp)
homeTeam	object	Home team details (id, name, shortName, slug)
awayTeam	object	Away team details (id, name, shortName, slug)
homeScore	integer	Home team score
awayScore	integer	Away team score
matchStatus	object	Match status details
teamId	integer	Team identifier
teamName	string	Team name
teamCountry	object	Country info
playerId	integer	Player identifier
playerName	string	Player name
playerPosition	string	Playing position
_operation	string	Operation that produced this row
_fetchedAt	string	ISO timestamp
status	string	Row status: "success" or "error"

Example — Search Tournaments output:

{
  "tournamentId": 17,
  "tournamentName": "Premier League",
  "tournamentSlug": "premier-league",
  "sport": { "name": "Football", "slug": "football" },
  "category": { "name": "England", "slug": "england" },
  "_operation": "searchTournaments",
  "_fetchedAt": "2026-05-28T00:10:00.000Z",
  "status": "success"
}

Example — Season Events output:

{
  "eventId": 12345678,
  "eventName": "Arsenal vs Chelsea",
  "startTime": 1748395200,
  "homeTeam": { "id": 42, "name": "Arsenal", "shortName": "ARS" },
  "awayTeam": { "id": 38, "name": "Chelsea", "shortName": "CHE" },
  "homeScore": 2,
  "awayScore": 1,
  "matchStatus": { "type": "finished" },
  "roundInfo": { "round": 28 },
  "_operation": "seasonEvents",
  "_fetchedAt": "2026-05-28T00:12:00.000Z",
  "status": "success"
}

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💼 Use Cases & Examples

1. 🏆 Sports Analytics Dashboard

Build real-time analytics dashboards for 30+ sports leagues worldwide.

Input: Tournament search → season events (paginated) Output: Match results, scores, team performance data, round info Use: Feed live data into Tableau, Power BI, or custom dashboards for league-wide performance tracking.

2. 🎯 Fantasy Sports Data Feed

Power fantasy sports platforms with up-to-date player and team data.

Input: Player details + team match history (paginated) Output: Player positions, nationalities, team affiliations, historical match data Use: Calculate player form, fixture difficulty, and team strength metrics for fantasy scoring models.

3. 📊 Betting Odds Research

Gather historical match results and team form for betting analysis.

Input: Season events (multiple pages) + team events Output: Historical scores, home/away performance, round-by-round results Use: Build predictive models with historical performance data across leagues and tournaments.

4. 📰 Live Score Aggregation

Build live score aggregation services across multiple sports.

Input: Season events for multiple tournaments Output: Match status, scores, start times, team details Use: Aggregate live match data from football, basketball, tennis, F1, and more into a unified feed.

5. 🗄️ Team & Player Database

Build comprehensive databases of teams and players across sports.

Input: Team details + player details (chained from search results) Output: Team names, countries, logos, player positions, nationalities Use: Populate a sports encyclopedia or directory with structured data from 30+ sports.

6. 📈 League Season Analysis

Track full season progression — fixtures, results, and standings data.

Input: Tournament seasons → season events (max pages: 50) Output: Complete fixture list with scores, round numbers, timestamps Use: Analyze season patterns, identify upset trends, and track title races across leagues.

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🔗 Integration Examples

JavaScript/Node.js

import { ApifyClient } from 'apify-client';

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

// Search for tournaments
const run = await client.actor('sian.agency/sports-data-scraper').call({
  operation: 'searchTournaments',
  query: 'Premier League'
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]);

Python

from apify_client import ApifyClient

client = ApifyClient('YOUR_TOKEN')

# Get season events (paginated)
run = client.actor('sian.agency/sports-data-scraper').call(
    run_input={
        'operation': 'seasonEvents',
        'tournamentId': 17,
        'seasonId': 52186,
        'maxPages': 3
    }
)

for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item)

cURL

curl -X POST 'https://api.apify.com/v2/acts/sian.agency~sports-data-scraper/runs?token=YOUR_TOKEN' \
-H 'Content-Type: application/json' \
-d '{"operation": "searchTournaments", "query": "Champions League"}'

Automation Workflows (N8N / Zapier / Make)

1. Trigger: Schedule (daily/hourly) or webhook
2. HTTP Request: Call actor API with operation + IDs
3. Process: Handle JSON results — filter, transform, enrich
4. Action: Save to database, send notifications, update dashboards

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📊 Performance & Pricing

FREE Tier (Try It Now)

• Full feature access — all 15 operations available
• Test with real data, same quality as paid
• No credit card required
• Perfect for evaluation and small projects

PAID Tier (Production Ready)

• Unlimited results per run with pagination
• Pay-per-result: only charged for successful extractions
• Faster processing, no rate limits
• Priority support

💰 Transparent pricing — only pay for successful results

🔗 View current pricing

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❓ Frequently Asked Questions

Q: How many results can I extract per run? A: Paginated operations (seasonEvents, teamEvents) support up to 50 pages per run. Single-result operations (teamDetails, playerDetails) return one detailed result per run.

Q: Which sports are covered? A: 30+ sports including football (soccer), basketball, tennis, Formula 1, MMA, esports, cricket, rugby, handball, volleyball, baseball, ice hockey, and more.

Q: What output formats are available? A: JSON, CSV, Excel — export directly from the Apify dataset. All formats include the same structured fields.

Q: How do I find tournament/team/player IDs? A: Chain operations naturally: searchTournaments → tournamentSeasons → seasonEvents → teamDetails → playerDetails. Each operation's output contains the IDs needed for the next.

Q: Do I need an API key? A: No. The actor handles upstream authentication. Just configure your Apify token and run.

Q: Is historical data available? A: Yes. Use seasonEvents to get past match results and teamEvents for historical team performance.

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🐛 Troubleshooting

"No tournaments found" error

• Try broader search terms (e.g., "Premier" instead of "Premier League 2024/2025")
• Check spelling of tournament names
• Some regional tournaments may use local language names

"Team/Player not found" error

• Verify the ID is correct — get IDs from seasonEvents or teamDetails outputs
• The ID may refer to a delisted or inactive entity

Empty results on paginated operations

• The season or team may have no upcoming events — try a different season
• Some tournaments only have events during their active season

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⚖️ Is it legal to scrape data?

Our actors are ethical and do not extract any private user data. They only extract publicly available sports data — tournament schedules, match results, team rosters, and player statistics. We believe our actors, when used for ethical purposes, are safe to use.

However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

You can also read Apify's blog post on the legality of web scraping.

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🤝 Support

Join our active support community

• For issues or questions, open an issue in the actor's repository
• Check SIÁN Agency Store for more automation tools
• ✉️ apify@sian-agency.online

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