Difference between revisions of "Team Shooting Stars: Proposal"
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==<div style="background: #000000; padding: 13px; font-weight: bold; text-align:center; line-height: 0.3em; text-indent: 20px;font-size:26px; font-family:Britannic Bold"><font color= #ffffff> Project Description</font></div>== | ==<div style="background: #000000; padding: 13px; font-weight: bold; text-align:center; line-height: 0.3em; text-indent: 20px;font-size:26px; font-family:Britannic Bold"><font color= #ffffff> Project Description</font></div>== | ||
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:<br/> | 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:<br/> | ||
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+ | ==<div style="background: #000000; padding: 13px; font-weight: bold; text-align:center; line-height: 0.3em; text-indent: 20px;font-size:26px; font-family:Britannic Bold"><font color= #ffffff> TOOLS </font></div>== | ||
+ | |||
+ | *# Tableau: | ||
+ | *#* Treemap | ||
+ | *#* Sunburst Charts | ||
+ | *#*Parallel Plots | ||
+ | *# QGIS: | ||
+ | *#* Geospatial Analysis: To see if there’s any correlation between | ||
+ | *# JMP: | ||
+ | *#* Clustering Analysis | ||
+ | *#* Logistic Regression: The outcome of the analysis will usually be based on a success or failure of the game. Hence to do a regression analysis on factors for success of a game, we need to use logistic regression as the dependent variable is categorical in nature | ||
+ | *#* Time Series Analysis: Basketball Reference consists of 5 years’ worth of dataset. Thus it’s worth doing a time series analysis on player performance, team performance, change in player’s role and several other factors | ||
+ | |||
+ | ==<div style="background: #000000; padding: 13px; font-weight: bold; text-align:center; line-height: 0.3em; text-indent: 20px;font-size:26px; font-family:Britannic Bold"><font color= #ffffff> PRIOR WORK & REFERENCES </font></div>== | ||
+ | #Success Factors in NBA: | ||
+ | ##http://www.basketball-reference.com/about/factors.html | ||
+ | #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: | ||
+ | ##http://ww2.amstat.org//Chapters/boston/nessis07/presentation_material/Justin_Wolfers.pdf |
Revision as of 15:57, 9 October 2016
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?
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
| |||
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
| ||||
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
- Tableau:
- Treemap
- Sunburst Charts
- Parallel Plots
- QGIS:
- Geospatial Analysis: To see if there’s any correlation between
- JMP:
- Clustering Analysis
- Logistic Regression: The outcome of the analysis will usually be based on a success or failure of the game. Hence to do a regression analysis on factors for success of a game, we need to use logistic regression as the dependent variable is categorical in nature
- Time Series Analysis: Basketball Reference consists of 5 years’ worth of dataset. Thus it’s worth doing a time series analysis on player performance, team performance, change in player’s role and several other factors
- Tableau:
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: