+234 improvement
Back to proof
BYU Basketball AI Workflow
A scheduling analytics and executive briefing workflow that turned NCAA data, committee thresholds, and staff constraints into weekly decision support.
Synthetic public view Schedule intelligence workflow
Source data
Committee thresholds
Scenario model
Staff brief
NCSOS 293 -> 59NET 46 -> 9Q1/Q2 0-2 -> 5-1
+37 improvement
resume-strength shift
Problem
Schedule planning was high stakes, data-heavy, and difficult to translate into staff-ready decisions quickly.
What I Designed
Mapped NCAA committee thresholds, schedule constraints, comparison cohorts, output formats, and weekly decision cadence before using AI coding assistance to help implement repeatable workflows.
Validation
Created domain checks for quadrant classification, schedule scenarios, source consistency, and executive-ready summaries so non-technical operators could trust the recommendations.
Adoption
Delivered staff-ready recommendations and reporting that were used in real planning decisions, then iterated based on operator feedback.
Positioning note
This work is framed as AI-assisted implementation. My ownership is problem definition, workflow design, evaluation criteria, validation, rollout, user feedback, and adoption. Coding-heavy pieces were built with AI coding assistance.