Women's Lacrosse Analytics

Research Overview

I analyzed D3 women's lacrosse team and individual stats to uncover what most strongly correlates with wins, then built dashboards coaches and players can actually use.

The Question

Which stats best predict win percentage? How do team archetypes differ (pace, defense-first, efficiency)?

Data & Methods

Collection: Selenium scraping from NCAA/3rd-party stat sites; CSV normalization.
EDA: Correlation analysis; goals/game surfaced as strongest predictor of win%.
Clustering: KMeans on standardized team features to identify archetypes.
Viz: Tableau dashboards for coaches/players; interactive filters by team, season, position.

Key Findings

Goals per game had the strongest correlation with win percentage; ground balls had the weakest.
Archetypes emerged (e.g., high-tempo offenses vs. low-tempo, defense-anchored teams).

Visualization & Analysis

Created comprehensive Tableau dashboards with interactive filters for coaches and players to explore team performance data. The dashboards included drill-down capabilities by team, season, and position, making the analysis accessible to non-technical stakeholders.

The visualizations helped identify key performance indicators and team archetypes that weren't immediately obvious from raw statistics. This data-driven approach provided actionable insights for coaching strategies and player development.

Outcome

Delivered dashboards and a write-up used for a final data analysis project; set groundwork for future player-level models.