WhoScored turns every touch of a match into a live rating out of 10, then hangs a named strength, weakness and style of play on each side. We extract WhoScored data on your cadence.
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You name the competitions, the seasons and the surfaces, and we build the collectors around them. ScrapeIt writes the parsing logic against WhoScored markup, runs it on the cadence you set - live through a matchday, once after the settling window closes, or a full historical backfill - and hands back a sample before the full pass. Anti-bot handling, proxy rotation and CAPTCHA solving are part of the service, because the site sits behind a challenge that turns away plain automated clients and the collectors have to behave like real browsers.
We collect what the game itself produces: appearances, events, ratings and results for professional footballers. Contact details and private life stay out of scope. Nothing behind a login is touched either, so the WhoScored Plus value-bets tool and anything else gated by an account is ruled out before the quote rather than promised and quietly dropped.
We extract WhoScored data surface by surface and keep the platform's own column names, so every row traces back to its page.
Delivery is CSV, JSON, XLSX or a load into your warehouse, with the capture moment on every row.
The rating is the house currency, and it pays to know how it is built before storing it. It runs out of 10 from a 6.0 baseline, is computed from over 200 raw statistics weighted by where on the pitch an event happened and how it ended, and refreshes every 30 seconds in play. Five minutes after the whistle the provider revises the underlying statistics and the rating moves with them. At full time the figure also picks up adjustments for goals scored, goals conceded and a clean sheet, scaled by position and minutes played. Keep the live series and the settled figure in separate columns or they will never reconcile.
Characteristics are labels, not numbers. Every player and team carries Strengths and Weaknesses graded Very Strong, Strong, Weak or Very Weak - passing, key passes, dribbling, finishing, through balls and crossing for a player; attacking down the wings, counter attacks, protecting the lead and defending set pieces for a team - beside a Style of Play list in the platform's own phrasing, from likes to cut inside to possession football and consistent first eleven. They are worked out against league averages over the latest two seasons, and several fold raw measures together.
Around that sit surfaces nobody else arranges the same way: formation records with the id, the name from 442 to 343d, the captain, the minute range and the slot each shirt filled; referee tables giving fouls per game, penalties, yellows and reds both for and against a club; previews with a predicted eleven, a missing-players table whose reason travels in an icon title, and a written verdict.
WhoScored is a football analytics site run from London, and every figure on it rests on Opta data. That shapes what a WhoScored scraper can reach: the event data comes from Opta, and the ratings and characteristics on top are the platform's own.
Coverage and depth are two separate questions here. The tournament menu currently carries 433 competitions across 114 regions, from the Premier League down to regional and continental minor cups, and scores, fixtures, lineups and tables run across all of them. Event detail does not. The competitions that carry it are named in the player comparison filter, 46 of them: the top five European leagues, the senior English tiers below them, Eredivisie, Liga Portugal, Super Lig, MLS, Copa Libertadores, the European club competitions and the major national-team tournaments. Anywhere else a player row shows apps and goals with N/A in the minutes, shots, pass success and rating columns. The scores data marks the split itself with an isOpta flag on the stage and a matchIsOpta flag on the fixture, so a crawl can tell in advance which games repay a deep pass.
Addresses are numeric and predictable. A match lives at /matches/{id}/{tab}/ with tabs for live, livestatistics, matchreport, preview and betting; a team at /teams/{id}/{tab}/ with fixtures, statistics, refereestatistics and archive; a player at /players/{id}/{tab}/ with matchstatistics, fixtures and history; a season at /regions/{region}/tournaments/{tournament}/seasons/{season}/stages/{stage}/{tab}/. The trailing slug is decoration: it is translated on the language subdomains while the numeric id stays put, so ids are the join key and the slug never is.
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€199 / one-time
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Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan details →The reason to scrape WhoScored is that ratings, events and tables sit on the same pages under the same ids. A single top-flight fixture yields the match header, both lineups, team and player totals, roughly 1,500 event rows with pitch coordinates and qualifiers, and a minute-by-minute rating for every player. The same player and team ids carry those rows into season aggregates, characteristics, formation records and referee tables, so a scouting model, an opposition report and a fantasy tool can all be built from one joined dataset.
The rating series and the Strengths, Weaknesses and Style of Play labels are WhoScored's own, so this is the one place to collect them, and they are far easier to compare across players, teams and seasons once they sit as rows next to the events they summarise.
The site is built for reading, not for bulk. Player tables page ten rows at a time and team tables twenty, the headline statistics screens cover only the top five leagues, there is no export button, and deeper views are drawn by script after load. So a WhoScored scraping plan is sliced by competition, season and stage id, not by scrolling.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt runs the WhoScored scraper as a managed service. Our team builds the collectors, watches them as the site changes and repairs them when it does. You receive files or an endpoint - CSV, JSON, XLSX or a database drop - with nothing to install and no infrastructure to keep alive. Clients come for scouting models, opposition analysis, fantasy football tooling and media research, and each takes a different slice of the same site.
Yes. The ScrapeIt WhoScored API returns player ratings with the minute-by-minute rating series, lineups, match events with pitch coordinates, team and player match totals and season aggregates as JSON from an endpoint we host, refreshed on the schedule you set. The same data also comes as CSV or XLSX files or straight into your database, with a capture timestamp on every row.
The header first: venue, attendance, referee, kick-off in local time and UTC, half-time and full-time scores, formation, manager and squad average age. Then lineups with shirt number, position code, height, weight, age, substitution minute and the man-of-the-match flag. Then team and player totals - shots by outcome, possession, touches, passes and key passes, tackles, interceptions, clearances, aerials, dribbles, dispossessions, errors, fouls, offsides and keeper saves. Underneath sit the event rows with pitch coordinates and qualifiers, and the minute-by-minute rating series for each player.
Two different depths, and mixing them up is the usual mistake. Detailed statistics, ratings and player comparison currently cover eighteen seasons, starting from 2009/10. Results, fixtures and league tables reach further: the Premier League season picker currently runs back to 1999/2000, and other competitions vary. Season and stage ids sit in the address, so a backfill is a finite list of pages rather than an open crawl. Tell us the competitions and the years and we will say which of the two depths you actually get for each one before any work starts.
As often as the source moves, and it moves fast: live ratings recalculate every 30 seconds, and scores, lineups and in-play totals shift with them. The catch is settlement. The data provider revises statistics about five minutes after the final whistle, the man-of-the-match star lands ten minutes after full time, and further corrections can follow later. So we usually run a live pass for the in-play series and a second settled pass after the revision window, then deliver both with a capture timestamp on every row so you can see which figure is which.
Yes. We work only on pages a signed-out visitor can open and we do not log in; from them we collect match headers, lineups, events, ratings, season statistics and tables. We collect only publicly available data - everything a visitor can see on WhoScored - and we collect it legally. We take the playing record of professional footballers, not their contact details or private life.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
WhoScored data from €169/month. Free project assessment, reply within 1 business day.
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