Using Airtable to Track and Analyze NYT Letter Boxed Puzzle Data Need Structure & Automation Advice

Hi everyone 👋

I’m building an Airtable base to track and analyze daily puzzles from the NYT Letter Boxed game by The New York Times, and I’d love some advice on optimizing my structure and automations.

Here’s what I’m currently managing in my base:

• Daily puzzle date

• The 12-letter grid (grouped by sides)

• Valid solution words

• Two-word solutions (minimum solve goal)

• My solve time

• Community solutions collected from different sources

• Difficulty level (manual tag for now)

What I’m Trying to Improve:

1. Better relational structure
   Right now, I have one main table for daily puzzles and another for words/solutions. I’m using linked records, but I’m not sure if I should normalize further (e.g., separate table for individual words across multiple days).

2. Automation ideas
   I’d like to:

   • Automatically tag puzzles as “Solved in 2 words”

   • Track average solve time per week

   • Possibly auto-calculate difficulty based on word count or uncommon letter usage

3. Performance optimization
   As the dataset grows (I’m logging daily), I want to make sure the base stays fast and scalable.

If anyone has built a structured tracking system for games, word puzzles, or recurring datasets, I’d really appreciate seeing how you approached:

• Table architecture

• Rollups & formulas

• Automation best practices

• Dashboard-style interfaces

I’m happy to share a simplified version of my base structure if that helps.

Thanks in advance! 😊