Data Pipelines

Player Analytics Dashboards

Raw GPS coordinates and heart rate BPMs are useless without context. We engineer data warehouses and BI dashboards that aggregate physical, technical, and tactical data to provide coaches with longitudinal insights.

Architectural Features

  • Data Warehousing: Consolidating disparate data streams (Catapult, STATSports, subjective coach grading) into a unified Snowflake or BigQuery lake.
  • Predictive Modeling: Implementing Python-based regression models to forecast injury likelihood based on acute:chronic workload ratios.
  • Dynamic Visualization: Custom D3.js or Recharts implementation for interactive heatmaps, scatter plots, and spider charts in the browser.
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Recommended Tech Stack

Data Warehouse

Google BigQuery or Snowflake for highly performant, columnar OLAP querying of massive telemetry datasets.

ETL Pipeline

Apache Airflow or dbt (data build tool) to clean, transform, and normalize vendor-specific data exports.

Frontend Visualization

React heavily leveraging D3.js for custom, interactive biometric graphing that off-the-shelf BI tools cannot support.

Machine Learning

Python (Scikit-Learn/TensorFlow) microservices deployed via Docker for on-demand statistical modeling.