⚽ Flashscore Sports Data API

58 record types · 40 sports · 18 modes — one actor.

Live scores, fixtures, results, stats, lineups, H2H, standings, team & player profiles, transfers, injuries, odds from 130+ bookmakers, rankings, news — normalized, deduplicated, warehouse-ready from $0.001/result.

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Why this instead of the 10+ fragmented actors on Apify?

Search Apify for "flashscore" and you'll find a dozen actors that each do one thing — live football, basketball live, tennis fixtures, team stats, H2H, results… each with its own schema, its own scheduling, its own monitoring.

This actor replaces all of them.

	This actor	Fragmented alternatives
Sports	40	1–5 per actor
Record types	58	3–15 per actor
Actors to install	1	8–12
Unified schema	✅	❌ each is different
Odds coverage	130+ bookmakers, 48 geos	0–20 bookmakers
Cost estimate before paying	✅ dryRun	❌
Budget cap	✅ hard USD cap	❌
Warehouse-ready	✅ dedupeKey + schemaVersion	❌ post-processing required

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Try it in 30 seconds

Two ways to start cheaply:

• Apify free tier — small experiments typically cost $0.02–$0.04.
• Estimate first, pay later — add "dryRun": true to any input. The actor returns the projected cost in RUN_SUMMARY.estimatedBillingEvents with zero data charges.

Empty input → live football matches, safe defaults:

{}

Today's fixtures across any sport:

{
  "mode": "matchesByDate",
  "sports": ["football"],
  "dateFrom": "2026-05-22",
  "dateTo": "2026-05-22",
  "maxItems": 200
}

Full match details — events + stats + lineups in one bundled record ($0.008):

{
  "mode": "matchDetails",
  "targetUrls": ["https://www.flashscore.com/match/<id>/"],
  "include": { "events": true, "statistics": true, "lineups": true }
}

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What you get

Module	Records	Price
Live + fixtures + dates	match_basic	$0.0010
Match details + stats	match_detail, match_events, match_statistics, match_lineups, match_h2h, match_commentary, match_video_highlights, match_momentum	$0.0030
Premium bundle	match-full — summary + events + stats + lineups in one record. 33% cheaper than buying each separately ($0.012 → $0.008)	$0.0080
Standings	competition_standings, standing_row	$0.0006
Teams	team_profile, team_squad, team_matches, team_transfers, team_standings, team_news_feed	$0.0025
Players	player_profile, player_career_stats, player_transfers, player_injury_history, player_match_record	$0.0025
Competitions	competition_profile, competition_matches, competition_draw, competition_archive	$0.0025
News	news_article (full body), match_news, team_news_feed	$0.0025
Rankings + calendars	ranking_row (ATP, WTA, FIFA, OWGR…), season_calendar (ATP, WTA, PGA, F1…)	$0.0025
Discovery	search_result, country, competition, featured_competition	$0.0025
Odds (opt-in)	match_odds — 20 mainstream bookmakers (bet365, Betfair, William Hill, Unibet…) in one record per match. Add "include": {"odds": true}	$0.0050

40 supported sports: football, tennis, basketball, hockey, american-football, baseball, handball, rugby, cricket, golf, darts, snooker, boxing, mma, motorsport, cycling, esports, volleyball, beach-volleyball, badminton, table-tennis, field-hockey, water-polo, aussie-rules and 16 more.

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Odds: 130+ bookmakers, 48 markets

No other Flashscore actor on Apify comes close. The default primary preset returns 20 mainstream international bookmakers in a single record per match. Scale up as needed:

Preset	Geos	Bookmakers
primary (default)	1 (GB)	20 incl. bet365, Betfair, William Hill, Ladbrokes, Unibet
balanced	14	~50
extended	20	~80
global	28	~100
max	48	130+ incl. DraftKings, FanDuel, Betano, Bwin, Winamax, Betsson

Enable with "include": {"odds": true}. Each preset costs $0.005 per match per geo.

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Real-world cost examples

Scenario	What gets billed	Cost
Premier League matchday — 10 matches, full bundle	10 × match-full	$0.08
Today's fixtures, all 40 sports	~500 × match-basic	$0.50
Live football, every 5 min, full Saturday (6 runs)	1,200 × match-basic	~$1.20
Champions League round of 16 — full bundle	16 × match-full	~$0.13
Weekly Premier League standings	20 × standing-row	$0.012
50 matches with odds (default preset, 20 books)	50 × match-full + 50 × odds-record	$0.65
Single player deep dive — profile + career + transfers + injuries	~4 × entity-profile	$0.01

Add "dryRun": true to any input to get a projected cost estimate at zero charge before committing.

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Use it from your app

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('joaobrito/flashscore-sports-data-api').call({});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

const live = items.filter(row => row.recordType === 'match_basic');
console.log(`${live.length} live matches`);
// { recordType, matchId, homeTeamName, awayTeamName, homeScore, awayScore, status, ... }

Python

from apify_client import ApifyClient
import os

client = ApifyClient(token=os.environ["APIFY_TOKEN"])
run = client.actor("joaobrito/flashscore-sports-data-api").call(run_input={})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    if item["recordType"] == "match_basic":
        print(item["homeTeamName"], "vs", item["awayTeamName"], item["status"])

Get your APIFY_TOKEN at console.apify.com/account/integrations.

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What a record looks like

Every record carries recordType, source, sourceUrl, scrapedAt, schemaVersion, and a stable dedupeKey — safe to replay, trivial to upsert into Postgres, BigQuery, or Snowflake.

{
  "recordType": "match_basic",
  "source": "flashscore",
  "sport": "football",
  "matchId": "4I23FiTQ",
  "country": "England",
  "competitionName": "Premier League",
  "startTime": "2026-05-22T19:00:00.000Z",
  "status": "1st Half",
  "statusCategory": "live",
  "homeTeamName": "Home FC",
  "awayTeamName": "Away FC",
  "homeScore": 1,
  "awayScore": 0,
  "scrapedAt": "2026-05-22T19:23:45.000Z",
  "schemaVersion": "2.0.0",
  "dedupeKey": "match_basic:football:4I23FiTQ"
}

statusCategory is a cross-sport bucket (scheduled · live · paused · finished · postponed · cancelled) so you filter consistently across all 40 sports with the same field.

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All 18 modes

Mode	What it does
live	Live + same-day matches by sport
matchesByDate	Fixtures + results in a date range
matchDetails	Per-match deep dive: events, stats, lineups, H2H, commentary, highlights, odds
team	Team profile, squad, recent + upcoming matches, transfers, news
player	Player profile, career stats, transfers, injuries, last matches
competition	Profile, fixtures, results, archive, draw, leaderboard, participants
standings	League / competition standings tables
h2h	Head-to-head data for a match or team pair
news	News articles by locale / category — metadata + full body
rankings	ATP, WTA, FIFA, OWGR, FedExCup rankings
seasonCalendars	ATP, WTA, PGA, F1 season calendars
search	Public discovery search by query (teams / players / competitions)
topSearch	Popular discovery suggestions
countries	Country / category catalog, optionally expands to competitions
featuredCompetitions	Editorial top competitions per sport
newsLocales	Catalog of available Flashscore News locales
newsCategories	Catalog of categories per locale
bookmakers	Public bookmaker name catalog by geo

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Controls

Parameter	Description
mode	One of the 18 modes above
sports	Array of sport identifiers (40 supported)
targetUrls	Public Flashscore URLs of matches, teams, players, competitions
include.*	events, statistics, lineups, h2h, commentary, highlights, momentum, odds, news
maxItems	Cap per run — default 50, safety net against runaway runs
dryRun	true → project cost, emit zero billable records
ACTOR_MAX_TOTAL_CHARGE_USD	Hard USD cap; run halts gracefully at 95%

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Build a historical archive

Use Apify Scheduler to run this actor on a daily or hourly cron. The dataset accumulates across runs and the dedupeKey on every record makes upserts trivial — you get a clean, append-only historical table even though the actor only scrapes the present. A daily matchesByDate job over a few months gives you a solid fixture-and-result archive for backtesting.

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Know before you buy

• Latency: 1–3 seconds wall-clock per request, polling-based. Not suitable for sub-second live trading or WebSocket push feeds.
• No SLA: best-effort unofficial extractor. Build retries and a cached fallback into your pipeline.
• Cross-run billing: re-running the actor against the same matches re-bills per the Apify PPE model — dedupeKey is for your upsert idempotency, not for skipping charges.
• Public data only: no login bypass, no CAPTCHA, no paywall.

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Support

Open an issue on the Apify Actor page:

Run ID:
Input used:
Affected URL or matchId:
Expected vs. actual:
RUN_SUMMARY warning category (if any):

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Unofficial extractor. Not affiliated with, endorsed by, or sponsored by Flashscore or Livesport.