# swar/nba_api

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3,441 stars · 687 forks · Python · mit

## Links

- GitHub: https://github.com/swar/nba_api
- awesome-repositories: https://awesome-repositories.com/repository/swar-nba-api.md

## Topics

`analysis` `api-client` `basketball-stats` `endpoint-analysis` `http-client` `jupyter-notebooks` `nba` `nba-api` `nba-stats` `nba-stats-api` `python` `python3` `sports-stats` `stats`

## Description

This project is a Python library that wraps official NBA endpoints to retrieve player, team, and game statistics as structured data. It serves as a programmatic interface for fetching professional basketball league records and real-time scoreboards via HTTP requests.

The library integrates with Pandas to transform raw JSON responses from sports servers into DataFrames for statistical analysis and data science. It functions as a data retrieval utility for tracking league-wide performance trends and scouting professional basketball players.

The tool covers a broad range of capabilities including the retrieval of player career statistics and live game scores. It also provides search and indexing functionality to locate players and teams using identifiers or text patterns.

## Tags

### Data & Databases

- [Sports Data Clients](https://awesome-repositories.com/f/data-databases/sports-data-clients.md) — Functions as a programmatic interface for fetching professional basketball league records and real-time scoreboards.
- [Sports Statistics Retrieval](https://awesome-repositories.com/f/data-databases/sports-statistics-retrieval.md) — Fetches professional basketball statistics and records from official league endpoints as structured data. ([source](https://github.com/swar/nba_api/blob/master/docs/nba_api/stats/examples.md))
- [Data Analysis](https://awesome-repositories.com/f/data-databases/data-analysis.md) — Gathers professional basketball statistics and records to identify patterns for sports analytics projects.
- [JSON-to-DataFrame Conversion](https://awesome-repositories.com/f/data-databases/dataframe-integration/json-to-dataframe-conversion.md) — Transforms raw JSON responses from sports servers into Pandas DataFrames for statistical analysis and data science.
- [DataFrame Conversions](https://awesome-repositories.com/f/data-databases/json-to-database-model-transformation/dataframe-conversions.md) — Transforms raw JSON responses into structured Pandas DataFrames for statistical analysis and data science.
- [Sports Scouting & Research](https://awesome-repositories.com/f/data-databases/sports-scouting-research.md) — Enables scouting by searching and filtering player and team information to identify talent trends.
- [Sports Statistics Tracking](https://awesome-repositories.com/f/data-databases/sports-statistics-tracking.md) — Provides automated retrieval of real-time game scores and league activity to monitor professional basketball performance.
- [Entity Search & Indexing](https://awesome-repositories.com/f/data-databases/entity-search-indexing.md) — Locates professional players using identifiers, activity status, or name-based text patterns. ([source](https://github.com/swar/nba_api/blob/master/docs/nba_api/stats/examples.md))
- [Sports Data APIs](https://awesome-repositories.com/f/data-databases/sports-data-apis.md) — Offers the detailed player profiles and historical metrics necessary for building sports-centric applications and websites.

### Business & Productivity Software

- [Game Score Trackers](https://awesome-repositories.com/f/business-productivity-software/game-score-trackers.md) — Provides a programmatic interface to access real-time game data and live scoreboards. ([source](https://cdn.jsdelivr.net/gh/swar/nba_api@master/README.md))
- [Sports Statistics Trackers](https://awesome-repositories.com/f/business-productivity-software/sports-statistics-trackers.md) — Provides a utility for monitoring professional league rankings and performance trends for basketball scouting.
- [Team Retrieval](https://awesome-repositories.com/f/business-productivity-software/team-collaboration-management/team-retrieval.md) — Programmatically retrieves lists of professional teams based on identifiers, abbreviations, or geography. ([source](https://github.com/swar/nba_api/blob/master/docs/nba_api/stats/examples.md))

### Development Tools & Productivity

- [Python API Clients](https://awesome-repositories.com/f/development-tools-productivity/rest-apis/rest-api-clients/python-api-clients.md) — Provides a native Python library for interacting with official NBA RESTful endpoints via an object-oriented interface.

### Game Development

- [Professional Athlete Analytics](https://awesome-repositories.com/f/game-development/player-performance-analytics/professional-athlete-analytics.md) — Retrieves historical performance data and career totals for individual NBA players. ([source](https://cdn.jsdelivr.net/gh/swar/nba_api@master/README.md))

### Networking & Communication

- [Bot Detection Bypass](https://awesome-repositories.com/f/networking-communication/request-header-configuration/request-header-overrides/bot-detection-bypass.md) — Employs techniques to mimic legitimate browser behavior and headers to avoid being blocked by automated bot detection.
- [Proxy Routing](https://awesome-repositories.com/f/networking-communication/request-proxies/proxy-routing.md) — Distributes outgoing requests across a set of proxy servers to avoid IP-based rate limiting.