Data Analysis
Athletics Performance Analysis
Analyzed basketball and volleyball performance data in R and Excel to generate visual summaries and metrics for coaching staff.
- R
- Excel
The figures below are illustrative examples. No private athlete information is shown.
Overview
Coaches make decisions fast, so my goal was to turn raw game and practice records into summaries they could read in a minute: what is working, what is not, and where to focus next.
I took basketball and volleyball performance data, cleaned it in R and Excel, and produced visual summaries and metrics built around the questions coaching staff actually ask.
Data
Team performance data for basketball and volleyball, organized in Excel and analyzed in R. Individual athlete details are kept private; the summaries focus on team-level patterns.
Analysis
- Game-by-game performance trends across the season to show momentum and slumps
- Comparison of home and away performance to see how much venue matters
- Breakdowns of key team metrics into consistent, readable summaries for coaches
Visualizations
The summaries include season trend lines, per-game metric charts, and comparison views built to be readable at a glance.
What I Learned
Sports data taught me that the audience matters as much as the analysis. A coach does not want a statistical report; they want one clear answer. Designing for that reader changed how I choose and simplify visualizations.