Трансферы и рыночная стоимость футболистов РФ и СНГ avatar

Трансферы и рыночная стоимость футболистов РФ и СНГ

Pricing

from $1.07 / 1,000 трансферы и рыночная стоимость футболистов рф и снг

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Трансферы и рыночная стоимость футболистов РФ и СНГ

Трансферы и рыночная стоимость футболистов РФ и СНГ

Данные Transfermarkt по игрокам сборной России и СНГ — рыночная стоимость, трансферная история, статистика по клубам. 25+ полей: клуб, позиция, возраст, контракт, агент. Без логина и прокси. Prefill игроков сборной (Головин, Миранчук, Оздоев) для CIS-аналитиков и fantasy-платформ.

Pricing

from $1.07 / 1,000 трансферы и рыночная стоимость футболистов рф и снг

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Developer

Vitalii Bondarev

Vitalii Bondarev

Maintained by Community

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1

Monthly active users

7 days ago

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transfermarkt-scraper-ru — Transfermarkt Scraper for Russian & CIS Football

Config-only clone of the existing Transfermarkt scraper. The scraping logic is unchanged.

Purpose

This Apify actor transfermarkt-scraper-ru retrieves Transfermarkt player data for Russian and CIS football profiles. It collects identity, club, position, age, nationality, current and historical market value, contract, agent, transfer history, and club statistics. Transfer-history and market-value history may be optional depending on input. Built for CIS sports analytics and fantasy football use cases.

Target audience

Developers, analysts, and product teams working with Russian and CIS football data who need structured player records from Transfermarkt without changing how the underlying scraper works.

Input example

{
"playerUrls": ["263918", "255450", "137206"]
}

These IDs correspond to players verified against transfermarkt.com: Aleksandr Golovin (Transfermarkt player ID 263918), Aleksei Miranchuk (ID 255450), and Magomed Ozdoev (ID 137206).

Output fields

Typical player records may include:

  • Identity (name, Transfermarkt ID)
  • Club
  • Position
  • Age
  • Nationality
  • Current market value
  • Historical market value (optional)
  • Contract details
  • Agent
  • Transfer history (optional)
  • Club statistics

Usage

  1. Open the actor transfermarkt-scraper-ru on Apify.
  2. Provide player identifiers in playerUrls (as in the input example above).
  3. Run the actor and download the dataset of player records.

No changes to scraping logic are required or applied; configuration targets Russian/CIS-oriented player sets.

Pricing

$3.00 per 1,000 player records.

Data quality and responsible use

  • Player examples above (Aleksandr Golovin, Aleksei Miranchuk, Magomed Ozdoev) are verified against transfermarkt.com.
  • Respect Transfermarkt terms of service and applicable laws.
  • Use scraped data responsibly; do not overload the source or republish bulk data without permission.
  • Optional fields (transfer history, market-value history) may be empty when not available or not requested.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

  • schema version, Actor name and build number;
  • UTC start and finish hour (not a precise timestamp);
  • run duration, number of results and time to the first result, each as a coarse range;
  • whether the result was empty, the end status, and an error type from a fixed list;
  • memory setting and counts of charged events;
  • names of the input fields you set, never their values;
  • the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

  • the result limit you asked for (a range, when the input has one) and what share of it was delivered;
  • results delivered per input item you listed (a range);
  • output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
  • how the run was started (console, API, schedule, webhook, another Actor);
  • how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
  • if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
  • a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.