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Documentation changes to README #274

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29 changes: 28 additions & 1 deletion README.md
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[Basketball Reference](http://www.basketball-reference.com) is a great site (especially for a basketball stats nut like me), and hopefully they don't get too pissed off at me for creating this.

I initially wrote this library as an exercise for creating my first `PyPi` package - hope you find it valuable!
I initially wrote this library as an exercise for creating my first `PyPi` package - hope you find it valuable!

## Introduction

The Basketball Reference Scraper is a tool designed to collect and translate basketball data from Basketball Reference, a comprehensive online resource for basketball statistics.
By leveraging their freely available service, this scraper extracts detailed information from seasons starting from the 1999-2000 NBA season and beyond.
This data can be translated into a usable API, making it accessible for integration into various applications, analytics tools, and dashboards.
The scraper simplifies the process of obtaining player stats, team records, and game results, offering a streamlined solution for basketball enthusiasts, analysts, and developers looking
to work with high-quality historical data.

## Background

This library was originally developed as part of another python project aimed at estimating NBA player productivity, with a focus on enhancing performance predictions in daily fantasy sports. for independent developers or smaller projects.
To address this, the library leverages publicly available data from Basketball Reference, a comprehensive and free online resource for NBA statistics. By using web scraping techniques, the library translates this data into a more usable API format. This allows for real-time analysis of player performance metrics, including advanced statistics, game logs, and season averages, enabling users to build predictive models.
In addition to the cost-saving benefits, this library makes player data accessible in a highly flexible format, providing valuable insights for sports analytics professionals, daily fantasy sports enthusiasts, and researchers alike.

Basketball Reference is a popular and comprehensive online resource for basketball statistics and historical data. It is part of the larger Sports Reference family of websites, which includes similar platforms for other major sports such as baseball and football. Basketball Reference provides a wide range of data on both NBA and WNBA players, teams, and games, covering multiple eras of professional basketball.

Key features include:

Player Statistics: Detailed stats for all players, including career totals, per-game averages, advanced metrics (like Player Efficiency Rating, Win Shares, etc.), and more.
Team Data: Historical and current stats for NBA teams, including win-loss records, playoff performance, and roster information.
Game Logs: Box scores and in-depth analysis of individual games.
Advanced Metrics: Sophisticated statistical measures such as True Shooting Percentage, Box Plus-Minus, and others, often used in advanced analytics.
Historical Data: Information on seasons, drafts, awards, and milestones from past decades, making it a go-to for sports historians and statisticians.
Tools: Interactive tools for searching, sorting, and comparing players or teams based on various criteria.
Because of its depth and reliability, Basketball Reference is often used by sports analysts, journalists, fantasy sports players, and even NBA teams for reference and research.

## Documentation

For documentation about installing the package and API methods see [the documentation page](https://jaebradley.github.io/basketball_reference_web_scraper/).


## Contributors

Thanks to [@DaiJunyan](https://github.com/DaiJunyan), [@ecallahan5](https://github.com/ecallahan5),
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