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Activity Number:
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230
- Innovative STEAMS Methdology Over STEM
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Type:
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Topic Contributed
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Date/Time:
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Monday, July 29, 2019 : 2:00 PM to 3:50 PM
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Sponsor:
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Quality and Productivity Section
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Abstract #301710
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Presentation
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Title:
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STEAMS Approach on NBA Basketball Games
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Author(s):
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Alan Yao* and Mason Chen
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Companies:
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Mission San Jose High School, and Stanford Online High School and Mission San Jose High School, Stanford OHS
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Keywords:
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Sports Analytics;
STEAMS;
Neural Network;
Regression;
Clustering;
Physics
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Abstract:
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This paper adopts the STEAMS approach in NBA basketball games. Modern sports have to apply concepts of science to enhance their individual capabilities and team performances. The Magnus effect, the force of moving air around the ball will cause a concerted change in velocity and create a curved path, thus enhances the accuracy of three-point shots, which becomes more critical than even in NBA games. NBA offense and defense statistic data were downloaded from on-line using Python script. JMP software was used in this study to analyze the NBA’s statistic data and to develop linear regression and neural network models to predict the winning percentage of NBA teams. Artificial neural network modeling improved prediction accuracy of linear regression models.
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Authors who are presenting talks have a * after their name.
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