Clustering NBA Players Based on Offensive Advanced Stats
-
Updated
Jun 9, 2020 - Jupyter Notebook
Clustering NBA Players Based on Offensive Advanced Stats
An RESTful API that allows users to obtain statistics for an individual NBA player against a specific team in the NBA. This type of data is particularly useful for daily fantasy games
NbaStatsPro is an app that tracks an individual's favorite NBA player statistics. The app uses NBA's statistic API. Statistics such as points per game, assist per game, rebounds per game are displayed.
This repository is a system to grade NBA players based on stats that correlate to winning games, obtained from machine learning.
NBA database in C#
Unsupervised Clustering Algorithm for clustering NBA player types beyond the traditional 5 positions utilized in the NBA: 1) Point Guard 2) Shooting Guard 3) Small Forward 4) Power Forward 5) Center.
NBA Player Traditional Statistics (from 1996-97 to 2022-23)
A wrapper site for NNNBA
Predict the best lineup combination for each NBA team based on player clusters and and historical 5-man lineup performance.
A Front-End project to show the hot shooting points of NBA players to help analysis.
visualization course project
Analysis of NBA player stats and salaries of the 2016-17 for the 17-18 season
Compare 2 basketball players by reading/comparing NBA stats in an Excel sheet.
An implementation of six degrees of separation for mutual NBA teammates.
Hover on an NBA player's name on any web page to quickly view their career stats. Thousands of active users across Chrome, Firefox, Opera, and Edge.
Add a description, image, and links to the nba-players topic page so that developers can more easily learn about it.
To associate your repository with the nba-players topic, visit your repo's landing page and select "manage topics."