Twitterbot. Because box scores don't tell the full story 🏀
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Updated
Nov 13, 2022 - Python
Twitterbot. Because box scores don't tell the full story 🏀
Data visualization of NBA(National Basketball Association)
End-to-end project to predict basketball player points. (regression problem)
Visualization web app built with Plot.ly and Dash, a framework that uses React.js and Flask, to view NBA statistics in a simple fashion with graphs and charts
NBA scoreboard web scraping using Python's selenium and Bucks 10 first games analysis
Classification on the Kobe Bryant Shot Selection dataset (https://www.kaggle.com/c/kobe-bryant-shot-selection/data) using Decision Trees
A comparison between the 2008-09 and 2018-19 NBA season comparing shot locations for individual players and leaguewide.
Python Tkinter Graphical User Interface to generate heat-maps of current NBA player shooting trends.
This is a python program that uses selenium to web scrape stats from https://www.basketball-reference.com and then displays a graph of an NBA player's career averages using Matplotlib.
🏀 NBA Hometown Heroes is a data visualization made with D3.js showing the places that NBA players help put on the map.
Carried out predictive analysis on the latest NBA 2020 games data to predict the winners/lossers of the NBA 2020 season. Used linear regression in python to develop a winning equation, matplotlib to develop charts and google api to create heat map.
Dataset Analysis on Sports
NBA Player HUD RShiny Application
A PyMySQL-based console app designed to provide insightful statistics and graphs based on data fetched from the NBA.com APIs.
NBA Player Statistics Visualization
predicting contracts for 2020 nba free agents
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