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Sports Data Scraper — Live Scores, Stats & Schedules

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Pricing

Pay per event

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Sports Data Scraper — Live Scores, Stats & Schedules

Sports Data Scraper — Live Scores, Stats & Schedules

Under maintenance

Sports data scraper covering 30+ sports — football, basketball, tennis, F1, MMA, esports. Extract tournament schedules, live scores, team stats, player profiles. Six operations, one clean dataset per run. No API key.

Pricing

Pay per event

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SIÁN OÜ

SIÁN OÜ

Maintained by Community

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1

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Sports Data Scraper — Live Scores, Stats & Schedules 🚀

SIÁN Agency Store Instagram AI Transcript Extractor TikTok AI Transcript Extractor Smart Idealista Scraper

⚽ Extract live sports data from 30+ sports — football, basketball, tennis, F1, MMA, esports. Six 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.


📋 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
  • Six Powerful Operations: Search tournaments, seasons, events, team details, match history, player profiles
  • 🎯 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 six operations: search tournaments, tournament seasons, season events, team details, team events, or player details.

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

📥 Input Configuration

FieldTypeRequiredDescription
operationstringYesData extraction operation to run
querystringFor searchTournamentsSearch keyword for finding tournaments
tournamentIdintegerFor tournamentSeasons, seasonEventsTournament ID from search results
seasonIdintegerFor seasonEventsSeason ID from tournamentSeasons results
teamIdintegerFor teamDetails, teamEventsTeam ID from seasonEvents results
playerIdintegerFor playerDetailsPlayer ID from teamDetails results
pageintegerNoStarting page for paginated ops (default: 0)
maxPagesintegerNoMax pages to fetch for paginated ops (default: 5, max: 50)

Operations:

OperationDescriptionRequired Input
searchTournamentsSearch tournaments by keywordquery
tournamentSeasonsList seasons for a tournamenttournamentId
seasonEventsMatch events for a tournament season (paginated)tournamentId, seasonId
teamDetailsTeam profileteamId
teamEventsTeam match history (paginated)teamId
playerDetailsPlayer profileplayerId

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
}

📤 Output

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

FieldTypeDescription
tournamentIdintegerUnique tournament identifier
tournamentNamestringTournament/competition name
seasonIdintegerSeason identifier
seasonNamestringSeason name (e.g. "2024/2025")
eventIdintegerMatch/event identifier
eventNamestringMatch/event name
startTimeintegerMatch start time (Unix timestamp)
homeTeamobjectHome team details (id, name, shortName, slug)
awayTeamobjectAway team details (id, name, shortName, slug)
homeScoreintegerHome team score
awayScoreintegerAway team score
matchStatusobjectMatch status details
teamIdintegerTeam identifier
teamNamestringTeam name
teamCountryobjectCountry info
playerIdintegerPlayer identifier
playerNamestringPlayer name
playerPositionstringPlaying position
_operationstringOperation that produced this row
_fetchedAtstringISO timestamp
statusstringRow 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"
}

💼 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.


🔗 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

📊 Performance & Pricing

FREE Tier (Try It Now)

  • Full feature access — all 6 operations available
  • Test with real data, same quality as paid
  • No credit card required
  • Perfect for evaluation and small projects
  • 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


❓ 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.


🐛 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

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.


🤝 Support

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