We extract fixtures, live match events, league standings, player profiles, and team statistics from Soccerway. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Fixtures & Results objects from soccerway.com. All fields typed and schema-versioned.
"match_id": "4321098", "date_utc": "2024-05-12T15:00:00Z", "home_team": "Arsenal", "away_team": "Chelsea", "home_score": 2, "away_score": 1, "status": "FT"
| # | match_id | date_utc | competition_id | competition_name | home_team | away_team |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Match Events objects from soccerway.com. All fields typed and schema-versioned.
"event_id": "evt_99812", "minute": "44", "team_name": "Arsenal", "player_name": "Bukayo Saka", "event_type": "Goal", "goal_type": "Penalty", "card_colour": "None"
| # | event_id | match_id | minute | team_name | player_name | event_type |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for League Tables objects from soccerway.com. All fields typed and schema-versioned.
"rank": 1, "team_name": "Manchester City", "matches_played": 38, "wins": 28, "draws": 7, "losses": 3, "points": 91, "goal_difference": 62
| # | competition_id | season | rank | team_name | matches_played | wins |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Player Profiles objects from soccerway.com. All fields typed and schema-versioned.
"player_id": "p_12345", "known_as": "Lionel Messi", "nationality": "Argentina", "age": 36, "position": "Attacker", "height_cm": 170, "preferred_foot": "Left"
| # | player_id | first_name | last_name | known_as | nationality | dob |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Squad Rosters objects from soccerway.com. All fields typed and schema-versioned.
"team_id": "t_543", "player_name": "Martin Odegaard", "squad_number": 8, "position": "Midfielder", "appearances": 35, "goals": 8, "minutes_played": 3105
| # | team_id | season | player_id | player_name | squad_number | position |
|---|---|---|---|---|---|---|
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Our Soccerway scraper handles the complexities of global football data: live AJAX polling, timezone normalisation, historical pagination, and complex table structures.
Extract match schedules across thousands of domestic leagues, international tournaments, and youth competitions.
Capture goals, cards, substitutions, and minute-by-minute updates via continuous polling during live fixtures.
Paginate through decades of historical seasons to extract past results, final standings, and relegated teams.
Extract detailed player profiles including physical attributes, career history, nationality, and current club affiliation.
Compile historical matchups between specific teams, capturing win ratios, total goals, and recent form.
Extract stadium names, capacities, host cities, and assigned match officials for every recorded fixture.
Track points, goal differences, matches played, and form guides across standard leagues and complex group stages.
Monitor team rosters, squad numbers, player positions, and seasonal transfer movements.
Configure high-frequency extraction pipelines for live match days to feed downstream betting or media applications.
Brief in. Clean data out.
Provide target leagues, teams, or historical date ranges. We design the extraction schema together.
We configure Scrapy crawlers, handle timezone normalisation, and set up live polling logic for soccerway.com.
Schema validation, null-rate checks, and match-status verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Football data is highly dynamic. Here is how we maintain accuracy and resilience across thousands of concurrent matches.
Soccerway updates live matches via complex XHR requests rather than static HTML reloads. Our pipelines intercept and parse these JSON payloads directly, ensuring sub-minute latency for goals and cards without rendering overhead.
Soccerway dynamically adjusts kickoff times based on the requesting IP address. We strip local offsets and normalise all timestamps to UTC, preventing scheduling conflicts in your downstream applications.
Domestic leagues, knockout cups, and aggregate ties all use different DOM structures. Our selector strategy uses adaptable XPath chains to correctly identify group stages versus knockout brackets without breaking the pipeline.
Heavy pagination through historical seasons triggers IP blocks. We distribute requests across European residential proxy pools with strict concurrency limits to maintain continuous access.
We monitor match states (Postponed, Abandoned, FT, AET, PEN) to ensure anomalous fixture changes are flagged immediately, keeping your database accurate during unpredictable real-world events.
Quant teams feed historical results, goal distributions, and head-to-head records into predictive models to calculate probabilities.
Operators track player appearances, goals, cards, and minutes played to update fantasy point scoring in near real-time.
Publishers populate live score widgets, post-match reports, and historical trivia using structured data feeds.
Analysts track team form, tactical shifts, and league trends across multiple tiers of domestic football.
Scouts monitor career trajectories, physical attributes, and performance metrics across obscure global leagues.
Researchers analyse decades of match data to study home-field advantage, referee bias, and scoring patterns.
"Soccerway holds the most comprehensive global football archive on the web, but extracting live match events and historical tables requires continuous pipeline orchestration."
Most teams underestimate the investment required: reliable Soccerway scraping requires handling complex AJAX polling for live scores, timezone normalisation across 100+ countries, and continuous selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis.
Everything supported by our soccerway.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles historical crawling and deduplication. Playwright intercepts XHR payloads for live match events, bypassing the need to render heavy DOM elements continuously.
We maintain pools of residential ISPs to distribute load during peak weekend fixtures, preventing IP bans while scraping thousands of concurrent matches.
Pipelines run on AWS Lambda (burst polling) and ECS (sustained historical scraping). Airflow handles scheduling and dependency management.
Data delivered to where your team already works — no new tooling required.
About soccerway.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available factual data, such as football scores and historical results, is generally permissible. DataFlirt extracts only public, non-authenticated sports data. We do not extract personal user data or bypass authentication walls. Clients should review Soccerway's ToS and consult legal counsel for specific commercial use cases.
For live fixtures, our polling pipelines can achieve sub-minute latency. Data is pushed immediately via Webhook to your endpoints, making it suitable for live scoreboards or trading models.
We can extract data as far back as Soccerway's archives permit, which for major European leagues often spans multiple decades. Historical extractions are typically run as one-off bulk jobs before initiating continuous updates.
Yes. Soccerway serves kickoff times based on the visitor's IP address. Our pipelines strip local offsets and normalise all timestamps to UTC, ensuring consistency across your database.
We cover any competition listed on Soccerway, from the English Premier League and UEFA Champions League to regional youth divisions and international friendlies.
Absolutely. We provide a sample run of up to 100 recent fixtures as part of the pre-engagement scoping process, allowing you to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a historical dump of 20 seasons or a live polling feed for weekend fixtures, we scope, build, and operate the pipeline. Tell us what you need.
