Create graphs from NBA.com's play by plays
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Updated
Aug 10, 2018 - JavaScript
Create graphs from NBA.com's play by plays
NBA data presented in graphical form for easily comparing players: www.bballgraphs.com
Track the Salary Cap Value for all 30 NBA Teams
This is a very basic sample using chart js and dataframe js to visualize details on the huge upset in 2015-2016 NBA finals
Predicting NBA results with Machine Learning models.
Sketching basketball movements over time.
Previsione dei punteggi ottenuti nell'intero campionato NBA 2015/2016, utilizzando la regressione di Poisson che tiene conto della forza offensiva e difensiva delle squadre coinvolte in ogni partita
A python package built on the top of nba_api client API to help users to extract and analyse NBA data
This is my first data analytics project. I've tried to answer questions: Which NBA player scored the most points, had the least injuries and earned the least. It was fun to see many different ways to illustrate data.
Experimenting with K-means clustering on NBA players from '21-'22 season
Attempts to predict NBA success of NCAA basketball prospects. More info will be added as this project progresses
Models and visualises distance and shot data for the 2021-22 NBA season, allowing users to search for players, teams and positions. Also allows users to weight the models with attempts.
A conceptual dashboard to visualize Expected Possession Value (EPV) in the NBA.
BA Stats is an official platform provided by the National Basketball Association (NBA) that offers a comprehensive collection of statistical data related to NBA games, players, and teams. This resource provides a detailed analysis of player performances, team standings, and game outcomes. Users can explore a wide range of statistics
Project done in Java (Processing). Reads from large basketball dataset and simulates the game as if in real time.
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