Ball4life Proposal V1

Proposal

Poster

Application

Research Paper

Version 1

Version 2

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INTRODUCTION

The National Basketball Association (NBA) is a men’s professional basketball league in North America. Comprising of 30 teams (29 in the United States and 1 in Canada), it is one of the 4 major professional sports leagues in the United States and Canada. Furthermore, it is widely regarded as the premier basketball league in the world, with many fans touting it as the hardest league with the world’s best players competing in it.

With an average NBA team being valued at US$1.9 billion, the NBA continues to generate earnings in the hundreds of millions. This, coupled with growing fan bases in China, Philippines, Vietnam and Europe ensures that the NBA will be able to provide entertaining and competitive basketball games for all their fans.

PROBLEM & MOTIVATION

Despite the success of the NBA in global markets, it remains relatively obscure in our local society. Many Singaporeans play a variety of sports and know of many famous athletes both worldwide and locally, such as:

International:

• Cristiano Ronaldo: Soccer
• Lionel Messi: Soccer
• Roger Federer: Tennis

Local:

• Table Tennis: Feng Tianwei
• Swimming: Joseph Schooling

However, few to no Singaporeans could say out even the name of an NBA player, apart from Michael Jordan, who has retired 16 years ago in 2003. However, there has been an increase in interest in the sport, as more and more locals begin to be associated with the sport.

Therefore, the team wishes to teach and showcase the insights behind each NBA game for the rising pool of basketball enthusiasts. This will serve to allow basketball enthusiasts get a better appreciation of the game, and help players with their basketball skills by providing them with actionable insights on how to improve their game. This will be done through data visualisation insights derived from the premier players and teams of the NBA.

OBJECTIVE

This visualisation aims to provide insights into the following:

1. What is the key attribute to help basketball teams win games
2. Is height truly essential to be a good basketball player
3. Which type of shot will make you a more efficient player

SELECTED DATABASE

The Data Sets we will be using for our analysis and for our application is listed below:

Dataset/Source	Rationale Of Usage
NBA Player Profile	Having the profile statistics (eg. Height, Weight) of an NBA player will allow us to accurately assess if there is indeed any correlation between his player profile and his ability to be a good player.
NBA Team Breakdown	This will help us to determine which are the teams that consistently outperform other teams, and through analysis allow us to determine the key aspects that gives each team their edge.
NBA Player Scoring Breakdown	This will help us to properly segment each player into different categories based on various metrics, which will ultimately help us to determine what are the things that each player does that best maximizes their abilities.

BACKGROUND SURVEY

We did basic background research on some existing visualizations or dashboards we could drive inspirations from or make it better. Below are a few visuals we found:

References to Existing Visualizations	Key Takeaways
Title: NBA Shot Tracker Link: http://www.estherbaek.com/NBAShotTracker/	Feedback Clear illustration of insights on player’s field goal percentage Simple and intuitive UI to better engage audiences Too little information, would require more information to better understand individual’s game
Title: Player Analysis Link: https://shotline.peterbeshai.com/p/1415	Feedback Detailed breakdown of player’s efficiency rate in the 2 key offensive tools Leveraged on time-series data to better understand player’s growth or decline Too little information, would require more information to better understand individual’s game
Title: Best Draft Class Link: https://towardsdatascience.com/basketball-analytics-the-best-draft-class-13a6eac0cdb5	Feedback Could have included trend line to predict next round of best draft class There is a lack of filter to show what are the factors being considered in efficiency

PROPOSED STORYBOARD

With a clearer idea of what we want after looking at a few visualization examples, we came up with a few storyboard ideas.

Proposed Storyboard	Description
	Homepage This page will display a brief overview of our motivation and list down the key areas which the visualisation will address. This provides a first touch point for users and sets the user journey in an organised manner.
	Understanding Efficiency of James Harden The visualization in this page will
	This implements the shooting efficiency of an NBA athlete on the court to measure where does he perform the best in
	This graph draws inspiration from a ternary graph to implement a rating based on a few factors, such as: Height Weight Offensive Efficiency Defensive Efficiency

CHALLENGES

Challenges	Mitigation Plan
Data Extraction from Web Sources/Pages.	Refine web scraping techniques to write automated scripts to scrape from NBA web pages
Data Cleaning and Transformation	Assign each team member with a data source to clean Organize team meeting to collate it into desired form
Lack of Experience with R and ShinyR	Go through available DataCamp courses Refers to online documentation and past examples to learn

TIMELINE

TOOLS/TECHNOLOGIES

COMMENTS

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