jdpipping/summer-lab
Jun 2025 – Jun 2025
1 Month active
Languages Used
HTMLRStan
Technical Skills
BootstrappingClusteringConfidence IntervalsData AnalysisData VisualizationMachine Learning
dbukasa
PROFILE
Dbukasa
Drew Bukasa developed a cross-sport analytics platform in the jdpipping/summer-lab repository, integrating NBA and NCAA basketball analytics, NFL predictive modeling, baseball park-effect inference, and betting strategy simulations. He implemented reproducible workflows using R and Stan, focusing on statistical modeling, clustering, and simulation. The platform featured core models for basketball team strength and free throw confidence intervals, NFL outcome prediction, and baseball park bias analysis, all supported by robust data visualization. By delivering five new features and maintaining code quality with routine updates, Drew enabled scalable, testable analytics that improved forecasting and risk assessment for sports analytics and betting applications.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
16Total
Bugs
0
Commits
16
Features
5
Lines of code
2,754
Activity Months1
Your Network
40 peopleWork History
June 2025
16 Commits • 5 Features
Jun 1, 2025June 2025: Delivered a cross-sport analytics platform in jdpipping/summer-lab, combining NBA/NCAA analytics, NFL predictive modeling, baseball park-inference, betting-strategy simulations, and music data analysis. Implemented reproducible workflows via R scripts/notebooks (08_Drew.R, 09_Drew.R, 11_Drew.Rmd, 12_Drew.Rmd, 18_Drew.R, 19_Drew.R) and core analytics: NBA four factors, NCAA FG analysis, team strength estimation, and free throw confidence intervals; NFL outcomes and win probabilities; park effects with permutation/parametric tests and visualizations; Kelly Criterion betting simulations; clustering and PCA on Spotify features. Result: a scalable, testable analytics suite enabling data-driven decisions for sports analytics and betting, with improved forecasting and risk assessment. Maintained code quality with routine updates and minor fixes; no major bugs reported this month.
16 Commits • 5 Features
Jun 1, 2025June 2025: Delivered a cross-sport analytics platform in jdpipping/summer-lab, combining NBA/NCAA analytics, NFL predictive modeling, baseball park-inference, betting-strategy simulations, and music data analysis. Implemented reproducible workflows via R scripts/notebooks (08_Drew.R, 09_Drew.R, 11_Drew.Rmd, 12_Drew.Rmd, 18_Drew.R, 19_Drew.R) and core analytics: NBA four factors, NCAA FG analysis, team strength estimation, and free throw confidence intervals; NFL outcomes and win probabilities; park effects with permutation/parametric tests and visualizations; Kelly Criterion betting simulations; clustering and PCA on Spotify features. Result: a scalable, testable analytics suite enabling data-driven decisions for sports analytics and betting, with improved forecasting and risk assessment. Maintained code quality with routine updates and minor fixes; no major bugs reported this month.
June 2025
Activity
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Quality Metrics
Correctness82.6%
Maintainability80.0%
Architecture78.8%
Performance73.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
HTMLRStan
Technical Skills
BootstrappingClusteringConfidence IntervalsData AnalysisData VisualizationMachine LearningR ProgrammingRegression AnalysisSimulationStan ModelingStatistical AnalysisStatistical ModelingXGBoost
Repositories Contributed To
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