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title: Building a soccer coaching app on Databricks | daily.dev
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# Building a soccer coaching app on Databricks

**[databricks](https://daily.dev/sources/databricks)** · 9 min read · 4 upvotes · 0 comments

## Summary

Coach's Corner is a soccer coaching application built entirely on Databricks that processes 51 million rows of match tracking data (25 fps from 19 feeds) into a sub-second interactive 2D/3D bench tool. The architecture uses Lakeflow Auto Loader for NDJSON ingestion, Spark Declarative Pipelines with 46 data quality expectations across bronze/silver/gold tiers, and liquid clustering for 1-3 second query response times. Two serving paths are deliberately separated: Lakebase (Postgres-backed) handles millisecond-latency replay reads, while DBSQL handles bursty analytical queries. AI features include a Genie natural-language-to-SQL scout interface, Vector Search for similar player lookups, and an Agent Bricks supervisor that orchestrates Genie, Vector Search, a Unity Catalog xG model, and Claude via the Unity AI Gateway to generate opponent dossiers. All model calls are traced in MLflow with deterministic fallbacks. The post frames this as a blueprint for closing the 'usability gap' in high-frequency operational data across any industry.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.databricks.com/blog/building-soccer-coaching-app-databricks>

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---

Tags: [#backend](https://daily.dev/tags/backend), [#ai-agents](https://daily.dev/tags/ai-agents), [#apache-spark](https://daily.dev/tags/apache-spark), [#databricks](https://daily.dev/tags/databricks)

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