Team Shooting Stars: Proposal
Contents
Background & Motivation
The National Basketball Association (NBA) is one of the most famous sports league in the world. It consists 30 men basketball teams (where 29 in the US, 1 in Canada) which was founded in 1940s, named BAA (Basketball Association of America). Then it changed to the current name of NBA after merging with NBL (National Basketball League) in 1949. NBA plays are generally fast-paced, physically intensive where audience find it fascinating to watch. NBA also represents the best basketball play standard in the world. Joining NBA is the ultimate dream for a professional basketball player.
As NBA fans, our group would like to analyse on player’s statistics and team’s performance to clear our doubts like how the play styles of NBA basketball have been changed over the last 10 years. We would apply different visualization tools and graphics to gain in-depth analysis.
Project Description
The aim of this project is to get deeper knowledge into the current trend in NBA and what makes a team succeed, so the questions we are going to answer are:
1. Is the role of centre becoming less and less important NBA?
2. Are 3-point-shooting teams more likely to win through the past ten years?
3. What is the most important quality of a championship team?
4. Is there a indicator of a player’s best performance in career?
5. What make 2011 Dallas mavericks and 1996 Houston Rockets win the championship?
Data Set Selection
We retrieved our data from Basketball Reference. The data is in CSV format where each game contains two CSVs files. For example, the following two CSVs represent the box scores of Cleveland Cavaliers vs Golden States Warriors on June 19, 2016:
Moreover, we also can retrieve a specific player's game statistics in a certain timeline from this site:
For our VA project, we plan to retrieve all players data in the past 10 years. We would also categorize the game statistics according to the game type (normal season, playoff, finals). The data size is quite large so we will use JMP to do data transformation and combination.
Schedule
| Academic Studying Week | Task | Done By | Status | |||
| Week 7 | ||||||
| 1 | Brainstorm project topic and scope | Everyone | Completed | |||
| Week 8 | ||||||
| 1 | Formulate ideas | Everyone | Completed | |||
| 2 | Consulting Prof | Everyone | Completed | |||
| 3 | Deciding on tools/techniques to use | Everyone | Completed | |||
| 4 | Upload detail project proposal | Everyone | Completed
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| Week 9 | ||||||
| 1 | Data preparation, consolidation, preprocessing and cleaning | Everyone | Not Completed | |||
| Week 10 | ||||||
| 1 | Update Wiki page | Everyone | Not Completed | |||
| 2 | Study Treemap | Not Completed | ||||
| 3 | Study Multi-Series Line Chart | Not Completed
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| Week 11 & 12 | ||||||
| 1 | Web App Developer | Everyone | Not Completed | |||
| Week 13 | ||||||
| 1 | Do poster, presentation preparation | Everyone | Not Completed | |||
| Week 14 | ||||||
| 1 | Presentation | Everyone | Not Completed | |||
| Week 15 | ||||||
| 1 | Submission of project poster | Everyone | Not Completed | |||
| 2 | Submission of final project paper and artifacts | Everyone | Not Completed | |||
| Week 16 | ||||||
| 1 | Visual Analytics Poster Night | Everyone | Not Completed | |||
TOOLS
Our team decided to use the tools such as JMP, Tableau, d3,js for doing the following analysis:
| Visualization | Description |
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PRIOR WORK & REFERENCES
- Success Factors in NBA:
- The length and success of NBA careers:
- Coates, Dennis; Oguntimein, Babatunde. International Journal of Sport Finance 5.1 (Feb 2010): 4-26.
- Racial Discrimination among NBA referees:
