Cricket (ODI/T20) & Tour de France stats from a Custom GPT connected to 3 live databases.

Published: September 17, 2025

Ask it a natural-language question. It queries the right DB and gives you the answer. It's a live connection to three separately hosted Postgres databases - Supabase, Neon & Aiven.

The GPT dynamically shifts connections to analyze 340 MB of data spanning 2.5 million rows in six tables across the 3 databases - 122-year history for Tour de France, and 22 years for Cricket across 7,596 matches.

The Databases (Live Data)

supabase_postgres → ODI ball-by-ball (2003→2025) / 1.5M rows
neon_postgres → T20 ball-by-ball (2005→2025) / 1M rows
aiven_postgres → Tour de France riders + stages (men 1903→2025; women 2022→2025)

What it Does

Computes player stats (runs, strike rate, averages)
Builds rankings (top scorers, best bowlers, most wins)
Summarizes Tour history (winners, distance, avg speed)
Produces charts & run statistical analysis with python

Try it yourself - sample questions

The GPT has starter prompts. Ask things like:

Cricket: "Top 10 ODI strikers by total runs off the bat, with matches, overs, and run rates per match/over. Add two charts for run rates."
Tour de France: "Show Tour de France winners from 2015–2025 with distance, time, and average speed. Also, chart the riders with 3+ wins in history."

Custom GPT = practical analytics tool

UI + agent + Python sandbox out of the box. Efficient + cost effective
Use for automations, report generators, and database applications
Live examples: www.tigzig.com → GPT section (top menu)

Customize & Deploy

FastAPI backend powers any custom front end, BI tool, or internal app.
Open-source - repo and docs include architecture, action schema, and deployment steps.
Auth: Bearer API key in this GPT. OAuth supported for role-based access and RLS (row level security)

Best used with an AI agent