Athlete Performance Analytics
Individual GPS load monitoring, readiness profiling, and position-group benchmarking — built from raw sensor data to athlete-facing dashboard. Each athlete accesses their own encrypted personal page; no individual data is shared across athletes.
Technology Stack
System Capabilities
Session Load Monitoring
Every GPS-tracked practice and game session is parsed, normalised, and stored. Player Load, high-speed distance, and acceleration/deceleration efforts are tracked per session across the full season.
Readiness & Battery Tracking
Weekly practice accumulation is expressed as a percentage of the athlete's own game-day capacity (2.5× reference game load). Colour-coded zones flag high, moderate, and building-load weeks at a glance.
Position-Group Benchmarks
Athlete outputs are compared against anonymous position-group averages. No individual teammate data is exposed — only aggregated norms with mean and standard deviation.
Token-Secured Personal Pages
Each athlete receives a unique, unguessable URL and a personal PIN. Data is verified server-side before any content is rendered — raw JSON files are never accessible via HTTP.
How It Works
- 1
GPS session exports are parsed from Catapult OpenField and ingested into a normalised Parquet store.
- 2
A Python ETL pipeline enriches each session with athlete identifiers, position-group norms, and scenario classification (practice, game, recovery).
- 3
Per-athlete JSON snapshots are generated — each containing only that athlete's own session history and anonymised group benchmarks.
- 4
A Next.js server validates each athlete's token and PIN before any data reaches the browser.
- 5
Interactive charts render workload history, readiness gauges, and position-group comparisons entirely client-side from the verified payload.
Interested in working together?
Based in Toronto. Open to performance consulting, data-systems projects, and S&C roles in professional sport.
Loenhart Health →