iramler/slu_score_module_development
Mar 2025 – Mar 2025
1 Month active
Languages Used
MarkdownPythonR
Technical Skills
Data AnalysisData VisualizationPandasPlotninePythonR
Brendan Karadenes
PROFILE
Brendan Karadenes
Bekara developed a data-driven player statistics analysis feature for the iramler/slu_score_module_development repository, focusing on PWHL performance trends by age and position. Using Python, R, and Jupyter notebooks, Bekara created scripts and visualizations that enabled detailed exploration of player profiles to inform scouting and optimization decisions. The work included resolving a data loading issue by updating the R script to reference the correct dataset path, ensuring analyses are reproducible across environments. This project demonstrated solid skills in data analysis and visualization, with thoughtful attention to reliability and reproducibility, resulting in a robust foundation for ongoing player evaluation workflows.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
877
Activity Months1
Your Network
23 people
Work History
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 performance summary for iramler/slu_score_module_development: Delivered data-driven PWHL statistics analysis feature and fixed data loading path, enabling reliable, reproducible analyses to inform performance optimization and scouting decisions.
2 Commits • 1 Features
Mar 1, 2025March 2025 performance summary for iramler/slu_score_module_development: Delivered data-driven PWHL statistics analysis feature and fixed data loading path, enabling reliable, reproducible analyses to inform performance optimization and scouting decisions.
March 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture70.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonR
Technical Skills
Data AnalysisData VisualizationPandasPlotninePythonRR ProgrammingSeabornTidyverse
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