Архитектура высоконагруженных сервисов футбольной статистики

Architecture of high-load football statistics services

Contents

What is a football statistics API and how does it work

A football statistics API is a programming interface that provides structured access to data about matches, tournaments, teams, and players. The developer does not parse websites or build their own network of scouts. They make an HTTP request to a ready-made REST API and receive a response in JSON format with already normalized and verified data. This is how a sports API is structured on the platform api-sport.ru, where football, basketball, tennis, hockey, table tennis, esports, and other sports are available in one interface.

Technically, the workflow looks like this: your application sends a request to an endpoint of the type /v2/football/matches 1. to the domain 2. api.api-sport.ru. 3. The API key is specified in the header, which authenticates you and applies limits. The provider’s backend aggregates data from its own sources, enriches it with additional statistics, bookmaker odds, and service information. After that, the API returns a compact JSON response with the necessary fields: current score, minute of the match, lineups, detailed statistics, live events, odds, and much more.

4. For high-load projects, not only the completeness of data is important, but also the predictability of the interface’s operation. The sports events API is designed as a stateless service, conveniently scalable horizontally, and supports strict versioning (for example, 5. /v2/6. ). Standard HTTP methods are used at the protocol level (GET for reading, in the future — POST/PUT for your internal services), and responses are cached and optimized. In the near future, WebSocket channels for push updates and AI services for advanced analytics will be added to the REST approach. api-sport.ru 7. [h3]Example of a simple request to the football statistics API[/h3].

8. A modern football statistics API should cover the entire cycle of product needs: from scheduling to in-depth post-match analysis. Through a sports API based on a specification similar to OpenAPI for

curl -X GET "https://api.api-sport.ru/v2/football/matches?date=2025-09-03" \
  -H "Authorization: YOUR_API_KEY"

What data about football matches can be obtained through the football statistics API

9. , you can obtain a list of tournaments and seasons, match schedules, league tables, lineups, and player profiles. For this, endpoints are used. 2. api.api-sport.ru, You can get a list of tournaments and seasons, match schedules, tournament tables, lineups, and player profiles. For this, endpoints are used. /v2/{sportSlug}/categories, /v2/{sportSlug}/tournament/{tournamentId}, /v2/{sportSlug}/tournament/{tournamentId}/seasons, /v2/{sportSlug}/teams, /v2/{sportSlug}/players. All data comes in JSON, already linked to the identifiers of tournaments, seasons, teams, and players, which simplifies integration.

For football projects, live data about matches is especially important. The endpoint /v2/football/matches with filters by date, tournament, team, or status returns not only the score and status of the match but also the field currentMatchMinute, an array liveEvents (goals, cards, substitutions, penalties, added time) and an extended block matchStatistics. It contains dozens of metrics: ball possession, shots, xG-like information, duels, interceptions, saves, passes, and much more. Additionally, in the match object, highlights are available (highlights) and bookmaker odds through an array oddsBase, where options for outcomes and odds dynamics are stored for each betting market.

Such data depth allows building recommendation systems, analytical dashboards, predictive models, and advanced betting products. You can connect live events with odds to highlight line changes, analyze market movement, and automate trading. Detailed statistics by periods (ALL, 1ST, 2ND) enable you to calculate your own metrics: pressing indices, attack models, intensity indicators, and much more based on a single universal API.

[h3]Example of obtaining detailed statistics and match odds[/h3]

fetch('https://api.api-sport.ru/v2/football/matches/14570728', {
  headers: { Authorization: 'YOUR_API_KEY' }
})
  .then(r => r.json())
  .then(match => {
    const stats = match.matchStatistics;
    const oddsMarkets = match.oddsBase;
    console.log('Текущая минута:', match.currentMatchMinute);
    console.log('Статистика владения мячом:', stats[0].groups[0]);
    console.log('Рынок 1X2:', oddsMarkets.find(m => m.group === '1X2'));
  });

Overview of popular services and providers of football statistics APIs

The market for football data providers is conditionally divided into global and niche providers. The former includes large international companies that collect statistics worldwide, enter into agreements with leagues, and sell feeds mainly to large media holdings and bookmakers. Their solutions differ in coverage and historical depth but are often complex to connect, have high minimum budgets, and are aimed at international legal entities.

The second segment consists of specialized API services focused on ease of integration, transparent pricing, and quick launch. Providers like the platform by the sports events API api-sport.ru, emphasize REST interface with clear endpoints, Russian-language documentation, support for popular sports, and betting opportunities. In one API, you get football, hockey, basketball, tennis, table tennis, esports, and other disciplines. This reduces development costs: there is no need to integrate multiple heterogeneous feeds and bring data to a unified format.

When choosing a provider, it is important to look not only at the list of leagues but also at the API architecture: versioning, SLA for updating live data, stability of the JSON schema, support for odds and additional entities. For high-load projects, response speed and the ability to horizontally scale on the provider’s side are critical. It is convenient when all sports are available under a single path pattern /v2/{sportSlug}/..., as in the API based on 2. api.api-sport.ru. This allows for writing a generalized client and easily adding new sports as the product grows.

[h3]Example of a request for a list of supported sports[/h3]

curl -X GET "https://api.api-sport.ru/v2/sport" \
  -H "Authorization: YOUR_API_KEY"

Architecture of a high-load football statistics service based on external APIs

A high-load football statistics service is built as a multi-tier system, where the external sports API acts as a source of «raw material,» and your microservices serve as the layer of business logic and preprocessing. An integration module with the data provider (for example, with REST API 2. api.api-sport.ru) is located on the external contour. It is responsible for calling the endpoints /v2/football/matches, /matches/{matchId}, error handling, retry requests, logging, and adapting the format to internal models. From this layer, data is sent to a message queue (Kafka, RabbitMQ, NATS) or an event bus, from where workers pick it up.

The next level consists of enrichment and normalization services. They link matches with internal identifiers of tournaments and clients, calculate additional metrics, filter out unnecessary fields, and form aggregates for quick frontend responses. The result is stored in specialized repositories: relational databases for transactional data (matches, teams, users), time-series or NoSQL for live statistics and event logs. At this level, a proprietary internal API (BFF or public API) is implemented, through which your web products and mobile applications access the already prepared data.

The frontend layer (websites, mobile applications, partner widgets) communicates only with your API, not directly with the external provider. This allows for controlling the load, caching popular requests, and applying your own authorization rules. As the audience grows, each layer scales horizontally: several instances of integration services, a queue cluster, database replication, separate clusters for reading and writing. In the future, WebSocket channels and AI services connected to the same stream of live data from 2. api.api-sport.ru, will be able to send updates and forecasts in real-time to all subscribed clients.

[h3]Example of a worker that periodically synchronizes matches[/h3]

const fetch = require('node-fetch');
async function syncMatches() {
  const res = await fetch('https://api.api-sport.ru/v2/football/matches?status=inprogress', {
    headers: { Authorization: 'YOUR_API_KEY' }
  });
  const data = await res.json();
  // здесь вы сохраняете матчи в свою БД или очередь
  console.log('Обновлено матчей:', data.totalMatches);
}
setInterval(syncMatches, 15 * 1000); // обновление каждые 15 секунд

Designing a football statistics REST API: endpoints, data formats, and authorization

The own REST API for football statistics should be predictable and compatible with the practices of external providers. A good approach is to inherit the path structure from the basic sports API: use versioning (/v1/, 5. /v2/), explicit indication of the sport (/v2/football/matches) and clear resources (матчи, команды, игроки, турниры). Filters are implemented through query parameters: дата, tournament_id, team_id, status, similar to how it works in /v2/{sportSlug}/matches on the provider’s side.

The response format is usually JSON with a uniform schema: a root object with request metadata and nested entities. Fields should have stable names to avoid breaking clients during updates. For sensitive operations and consumption tracking, API key authorization is used. The key is passed in the header Authorization, and its issuance and management can conveniently be moved to a separate service or personal account. In the case of using an external sports data provider, the key can be obtained through the personal account api-sport.ru, and then proxy requests through your backend.

Correct HTTP codes and limits are equally important: 200 for successful responses, 400 for incorrect parameters, 401 for lack of authorization, 429 for exceeding limits. Rate limits, caching, and logging are configured at the API gateway level. This protects internal services from traffic spikes while maintaining a transparent integration model for your clients’ developers.

[h3]Example of a request with API key authorization[/h3]

curl -X GET "https://api.api-sport.ru/v2/football/matches?team_id=195801" \
  -H "Authorization: YOUR_API_KEY"

Scaling and caching the football statistics API under high load

To withstand load peaks during top matches and tournaments, the architecture of the football statistics API must actively use caching and horizontal scaling. The first level of cache is CDN and reverse-proxy (for example, Nginx, Cloudflare), which store the most frequent GET requests: schedules, tournament tables, lineups. For such data, a TTL can be set from a few seconds to minutes, as they are updated relatively rarely. Live matches, on the contrary, are cached very briefly (1–5 seconds) or not cached at all if absolute real time is required.

The second level is in-memory cache (Redis, Memcached) in the application. Here, the results of requests to external providers (for example, to 2. api.api-sport.ru) and frequently used aggregates for the frontend are stored. Such cache unloads both your database and the external API, reducing the number of requests and the risk of hitting limits. It is important to separate keys by sports and data types to avoid collisions and safely invalidate only the changed entities.

Horizontal scaling is achieved through a stateless approach to services and offloading state to external storage and queues. Several instances of the API gateway distribute traffic, while statistics processing workers listen to a common event queue. Databases are sharded by sports, regions, or clients. This approach allows for linear performance scaling by adding new nodes to the cluster as the number of simultaneously active users grows or the geography of the project expands.

[h3]Example of simple caching of a response from an external API[/h3]

const cache = new Map();
async function getMatchesCached(key, url) {
  const cached = cache.get(key);
  if (cached && Date.now() - cached.ts < 5000) {
    return cached.data;
  }
  const res = await fetch(url, { headers: { Authorization: 'YOUR_API_KEY' } });
  const data = await res.json();
  cache.set(key, { ts: Date.now(), data });
  return data;
}
// пример использования
getMatchesCached(
  'today-football',
  'https://api.api-sport.ru/v2/football/matches?date=2025-09-03'
).then(data => console.log(data.totalMatches));

Integrating the football statistics API into websites, mobile applications, and betting services

When integrating the football API into websites and applications, it is important to adhere to the principle of «thin client, smart backend.» The browser or mobile application should not directly access the external provider to avoid exposing the API key and losing control over the load. Instead, your backend is used, which calls the sports API, caches responses, combines several requests, and returns an adapted format to the frontend. For websites, this can be JSON endpoints for AJAX widgets and server-side rendering of pages, and for mobile applications, a single BFF layer optimized for their scenarios.

In betting services, integration is complicated by requirements for response time and data accuracy. It is necessary not only to display the score and goals but also to account for live statistics, odds movements, and betting market statuses. Using fields oddsBase, liveEvents и matchStatistics from matches obtained through /v2/football/matches, it is possible to automatically update the line, highlight dangerous moments, and filter suspended markets. Here, upcoming WebSocket channels and AI services of the platform are particularly useful. api-sport.ru, which in the future will allow receiving updates and forecasts almost without delays.

For the frontend, integration comes down to building convenient widgets: live scores, event timelines, player cards, matrix statistics tables, betting coupons. All of them can work on top of a single internal API that you build based on the sports provider’s database. This approach simplifies product development: it is enough to integrate once 2. api.api-sport.ru and then add new sports and features without significant changes to the architecture.

[h3]Example of a simple live score widget in JavaScript[/h3]

async function renderLiveScore(matchId) {
  const res = await fetch(`/api/my-football/matches/${matchId}`);
  const match = await res.json();
  const el = document.getElementById('live-score');
  el.textContent = `${match.homeTeam.name} ${match.homeScore.current} : ${match.awayScore.current} ${match.awayTeam.name}`;
}
setInterval(() => renderLiveScore(14570728), 10000);

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