iramler/slu_score_module_development
Apr 2026 – Apr 2026
1 Month active
Languages Used
R
Technical Skills
R programmingdata analysisdata visualizationstatistical analysis
deeri
PROFILE
Deeri
Developed and launched a Diving Scores Analytics module within the iramler/slu_score_module_development repository, enabling comprehensive exploration, analysis, and visualization of FINA World Junior Championships diving scores. Leveraging R programming, data analysis, and statistical visualization techniques, the module exposes scoring patterns and potential judge biases while supporting statistical comparisons among divers. The implementation delivers an end-to-end analytics pipeline, providing actionable insights for performance reviews and improvements in judging quality. All functionality was introduced through a dedicated module update, focusing on robust data processing and clear visual outputs. The work demonstrates depth in statistical analysis and effective use of R for sports analytics.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
3,234
Activity Months1
Your Network
22 peopleShared Repositories
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iramlerMember
Work History
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026: Delivered a new Diving Scores Analytics module within iramler/slu_score_module_development, enabling exploration, analysis, and visualization of FINA World Junior Championships diving scores. The feature exposes scoring patterns, potential judge biases, and supports statistical comparisons among divers, delivering data-driven insights for performance reviews and judging quality improvements. Implemented via a dedicated module update commit to launch the analytics capabilities.
1 Commits • 1 Features
Apr 1, 2026April 2026: Delivered a new Diving Scores Analytics module within iramler/slu_score_module_development, enabling exploration, analysis, and visualization of FINA World Junior Championships diving scores. The feature exposes scoring patterns, potential judge biases, and supports statistical comparisons among divers, delivering data-driven insights for performance reviews and judging quality improvements. Implemented via a dedicated module update commit to launch the analytics capabilities.
April 2026
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
R
Technical Skills
R programmingdata analysisdata visualizationstatistical analysis
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