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Summary

The main goal of this project was to prove our hypothesis that increased stress leads to poorer game performance in college basketball players. We first created a Structural Equation Model (SEM) using survey and tracking data to capture the relationship between three latent variables: physical readiness, emotional readiness, and game_performance. The SEM confirmed our hypothesis and showed that players who were more physically and emotionally ready tended to perform better in games.

Next, we build a second SEM model with only physical and emotional readiness and used extracted the predicted scores from this model. We then built a dashboard to track emotional readiness for each player over time.

Files

  • write_up.pdf
    • This is our full-write up for this project
  • full_model_semopy.py
    • This file creates the full SEM in Phyton using the Semopy package
  • readiness_only.R
    • This file creates the readiness only model in R using the Lavaan package. The data needed for this is created in stress_only_data.py.
  • readiness_report.Rmd
    • This creates a dashboard to visualize the readiness scores using Shiny App. The data needed for this is created in stress_only_data.py
  • stress_only_data.py
    • This creates the data used by readiness_only.R and readiness_report.Rmd

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UVA MSDS Capstone Project

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  • Python 82.0%
  • R 18.0%